Electric Integrated Resource Plan Public Service Company of New Mexico Prepared by the PNM Integrated Resource Planning Department

Transcription

1 Electric Integrated Resource Plan Public Service Company of New Mexico Prepared by the PNM Integrated Resource Planning Department July 2011

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3 SAFE HARBOR STATEMENT This document contains forwardlooking statements. Such statements are subject to a variety of risks, uncertainties and other factors, most of which are beyond the company s control, and many of which could have a significant impact on the company s operations, results of operations, and financial condition, and could cause actual results to differ materially from those anticipated. For further discussion of these and other important factors, please refer to reports filed with the Securities and Exchange Commission. The reports are available online at The information in this document is based on the best available information at the time of preparation. The company undertakes no obligation to update any forwardlooking statement or statements to reflect events or circumstances that occur after the date on which such statement is made or to reflect the occurrence of unanticipated events, except to the extent the events or circumstances constitute material changes in the Integrated Resource Plan that are required to be reported to the New Mexico Public Regulation Commission (NMPRC) pursuant to Rule New Mexico Administrative Code (NMAC).

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5 PNM IRP TABLE OF CONTENTS TABLE OF CONTENTS...I LIST OF TABLES AND FIGURES... IV PART I: SUMMARY, MOST COST EFFECTIVE PORTFOLIO AND ACTION PLAN 1 1. EXECUTIVE SUMMARY 1 THEMES AND OBSERVATIONS... 1 THE MOST COSTEFFECTIVE PORTFOLIO... 1 FOUR YEAR ACTION PLAN MOST COST EFFECTIVE RESOURCE PORTFOLIO 3 ELEMENTS OF THE MOST COST EFFECTIVE PORTFOLIO... 4 PORTFOLIO RISK AND MITIGATION STRATEGIES FOURYEAR ACTION PLAN FOUR YEAR ACTION PLAN ACTION PLAN ALTERNATIVES PART II: PROCESS AND TECHNICAL ANALYSIS INTEGRATED RESOURCE PLANNING APPROACH 19 IRP RULE REQUIREMENTS ABOUT THE INTEGRATED RESOURCE PLANNING PROCESS ADDITIONAL RESOURCE PLANNING REQUIREMENTS ENERGY EFFICIENCY REQUIREMENTS ENVIRONMENTAL REGULATIONS RENEWABLE ENERGY REQUIREMENTS STIPULATED AGREEMENTS SYSTEM RELIABILITY STANDARDS ANALYTICAL TECHNIQUES STATUS REPORT ON 2008 IRP PUBLIC ADVISORY (PA) PROCESS REVIEWING EXISTING SYSTEM RESOURCES 39 ENERGY EFFICIENCY RESOURCES EXISTING RATES AND TARIFFS EXISTING RENEWABLE RESOURCES EXISTING SUPPLYSIDE RESOURCES EXISTING PNMOWNED RENEWABLE RESOURCES EXISTING PNMCONTRACTED RENEWABLE RESOURCES EXISTING PNMOWNED SUPPLYSIDE RESOURCES REMOTE TO LOAD EXISTING PNMOWNED SUPPLYSIDE RESOURCES NEAR LOAD EXISTING, PURCHASED SUPPLYSIDE RESOURCES, REMOTE AND NEAR LOAD OPERATIONAL INFORMATION EXISTING RESOURCE ENVIRONMENTAL IMPACT WATER USE AT EXISTING PLANTS WATER SECURITY AT EXISTING PLANTS i

6 PNM IRP EXISTING TRANSMISSION EXISTING TRANSMISSION CAPABILITIES FORECASTING SYSTEM LOADS 73 SYSTEM LOAD FORECAST HISTORICAL COMPARISON OF LOAD FORECAST LOW LOAD FORECAST MID LOAD FORECAST HIGH LOAD FORECAST PLUGIN ELECTRIC VEHICLES (PEV) PROJECTED LOADS WITH EXISTING RESOURCES ENERGY EFFICIENCY RENEWABLE ENERGY COMPLIANCE SUPPLY SIDE FUELS ASSESSMENT 87 SUPPLYSIDE FUELS ASSESSMENT REVIEWING FUTURE RESOURCE OPTIONS 95 DEMAND SIDE RESOURCE OPTIONS DEMAND RESPONSE PROGRAMS SUPPLY SIDE RESOURCES RENEWABLE RESOURCE OPTIONS WATER FOR FUTURE PLANTS COST AND PERFORMANCE SUMMARY FOR NEW RESOURCE OPTIONS FUTURE RESOURCE COST SUMMARY TABLES SCENARIO ANALYSIS 121 SCENARIO ANALYSIS MODELING RESULTS OF SCENARIO ANALYSIS SCENARIO ANALYSIS CONCLUSIONS QUANTITATIVE ANALYSIS 150 ABOUT THE MONTE CARLO ANALYSIS OBSERVATIONS FROM RISK SIMULATIONS QUALITATIVE ANALYSIS 163 APPENDIX A GLOSSARY 169 ACRONYMS IRP TERMINOLOGY APPENDIX B LOAD FORECAST DATA 179 APPENDIX C TRANSMISSION 185 INTEGRATION OF VARIABLE ENERGY RESOURCES REGIONAL TRANSMISSION PLANNING AND COORDINATION GROUPS APPENDIX D RULES AND REGULATIONS 192 APPENDIX E STRATEGIST MODELING TOOL 193 ii

7 PNM IRP APPENDIX F STOCHASTIC RISK ANALYSIS DETAILS 195 APPENDIX G SCENARIO ANALYSIS RESULTS SUMMARIES 201 APPENDIX H ANALYSIS OF EXTERNALITIES AND LIFECYCLE COSTS 213 iii

8 PNM IRP LIST OF TABLES AND FIGURES TABLES Table 11. Resource Additions Table 21. PNM Most CostEffective Portfolio... 4 Table 22. Load and Resources (L&R) Table (IRP Rule E)... 5 Table 23. Gas Unit Diversity Chart... 8 Table Implementation Strategy Table 51. Status of 2008 IRP Action Plan Table 61. Community Meeting Participation and Values Table 62. Topics of IRP Working Group Meetings Table 63. PNM Stakeholders Participating in the IRP Public Advisory Process Table IRP Collaborative Outcomes Table 71. Demand Response Program Costs Table 72. Energy Efficiency and Demand Response Program Results Table 73. Energy Efficiency Program Results through December Table 73 (continued). Energy Efficiency Program Results through December Table 74. CustomerSited Renewable DG Program Growth Table 76. Contribution to Summertime Peak Table 75. Solar REC Incentive Program Categories and REC Rates Table 77. Existing System s Total Capacity Table 78. Historical Output of Algodones/Aztec Table 79. InService Dates of PV Facilities Table 710. NMWEC Historical Production and REC Allocations Table 711. SJGS Ownership by Unit Table 712. Ownership by Unit of PVNGS Table 713. PNM Contracted Resources Shown (IRP Rule C) Table 714. PNMOwned SupplySide Resources (IRP Rule C) Table 715. O&M Costs: Owned and Contracted Resources (IRP Rule C) Table 716. Environmental Impacts of PNM Owned and Contracted Resources Table 717. Water Intensities by Generation Type (Wet Cooled) Table 81. PNM System Peak Demand and Energy Comparison (WeatherNormalized) Table 82. Load Forecast Growth Rates Without Energy Efficiency Table 83. Calculated Market Population by County Table 84. Electric Vehicles Forecast Table 85. Charging Profile for PEVs Table 86. Load and Resources Table with MidLoad Forecast and Existing Resources Table 87. PNM System Load Factor Comparison Summary Table 91. Detailed Fuel Cost Assumptions Table 101. Distribution and Substation Losses by Demand and Energy Table 102. Load Reduction in Peak Demand and Energy Use for EE and DR Programs Table 105. Storage Technologies and Associated Costs Table 104. Electric Car Load Projections Table 106. Cost, reliability and environmental performance for new resource Options Table 106 (continued). Cost, reliability and environmental performance Table 107. General Maintenance Schedules Assumptions Table 108. Financial Assumptions, Incentives and Depreciation Figures iv

9 PNM IRP Table IRP Scenarios Table 112: Mid Load Scenario Analysis Summary Table 113. Low Load, High Load & MidLoad w/ Electic Vehicle Scenario Analysis Summary Table 114 Low, Mid, High and Mid with Electric Vehicle Load Forecast Comparison Table 115. Loss of Load Hours Comparison for Scenarios 4 and Table 116. NM GHG Cap Rule Estimated CO2 Limits for Scenario Table 117. NM GHG Rule Scenario Results Table 118. Scenario 6 RPS Compliance Scenarios Table 119. Scenario 16 RPS Compliance Sceanarios Table Scenario 2a Results Table 121. Carbon Prices Table C1. Existing Transmission Switching Stations Table C2. Existing Transmission Lines Table C3. Existing Joint OwnedTransmission Lines Table F1. Simulation Results ($000) 300 Monte Carlo Draws Table F2. Natural Gas Price Forecasts/Monte Carlo Simulation Mean Values Table F3. Wholesale Market Electricity Price Forecasts v

10 PNM IRP FIGURES Figure 21. Comparison of Resource Mix Figure 22. Comparison of Existing and Planned Energy Efficiency vs. EUEA Standard... 6 Figure 41. Planning Reserve Margin Formula Figure 71. Inclining Block Energy Rates Figure 72. LongTerm Availablity of Existing and Contracted SupplySide Resources Figure Fuel Mix Shown as Percentage of Kilowatt Hours Generated Figure 720. Overview of Existing System Representation During Peak Load Figure 721. WECC Path 47 and Figure 722. Transmission Import Limits Relative to Existing Northern NM Generation Figure 723. SNM Transmission System Figure 81. PNM s Electric Service Territory Map Figure 82. Total Retail Sales by FERC Classes Figure 83. Comparison of PNM Forecast Peak Demand for Electricity Figure 84. Proposed MidLoad Forecast with Existing Resources Figure 85. Projected Energy Efficiency Needed to Meet Minimum Compliance Figure 91. Map of New Mexico Renewable Energy Resource Potential Figure 92. Map of New Mexico Coal and Uranium Deposits Figure 101. Low Level Current and New Programs vs. EUEA Savings Requirements Figure 102. Middle Level Current and New Programs vs. EUEA Savings Requirements Figure 103. High Level Current and New Programs vs. EUEA Savings Requirements Figure 104. Aggressive Deployment of Energy Efficiency Programs Figure 105. Capital Costs per Kilowatt (in 2011 Dollars) of Resource Options Figure 111. Effects of 20 MW Load Management in Figure 112. Mid and High Gas Comparison Figure 113. CO 2 emission Cost Comparison Figure 114. Four Corners Retirement Comparison Mid Load Figure 115. Four Corners Retirement comparison High Load Figure 116. San Juan Retirement Comparison Mid Load Figure 117. San Juan Retirement Comparison High Load Figure 118. Coal Fly Ash Scenario Comparison High Load Figure 119. Energy Production During Water Curtailment Sensitivity Figure 121. Comparison of Actual Annual Peak Growth Demand Figure 122. Probality Distribtion for 2012 load Figure 123. Historical Gas Prices Figure 124. Probability Distribution of Gas Prices Figure 125. Gas and Electricity Price Relationship Figure 126. Plotting Portfolio Risk and Cost Measures Figure Draw Simulation Figure 128. CO2 Cost Example; RiskCost TradeOff Figure 129. RiskCost Indifference Figure 1210 Portfolios Including Coal Retirements Figure RPS Targets vs. Least Cost Portfolios vi

11 PNM IRP PART I: SUMMARY, MOST COST EFFECTIVE PORTFOLIO AND ACTION PLAN

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13 Executive Summary PNM IRP EXECUTIVE SUMMARY In accordance with New Mexico Administrative Code (NMAC), Integrated Resource Plan for Electric Utilities, PNM established a process to determine the most costeffective resource portfolio that meets regulatory requirements and energy needs for the planning period. The process requires consideration of studies, forecasts, and regulatory predictions together with historical data, existing resource availability, current regulation, and the costs associated with alternative portfolio solutions. Resource analysis considers both the short and long term cost impact to the customer, while reliably delivering the expected services and meeting other regulatory and operational requirements. THE IRP WORKING GROUP AND PROCESS The Integrated Resource Plan (IRP) Working Group was comprised of diverse individuals representing themselves, government entities, industry, advocacy organizations, and resource developers. PNM and the Working Group defined a set of variables to apply to 26 scenarios representing conditions that could occur over time. These included changing demand levels, fluctuations in fuel prices, carbon dioxide (CO 2) costs, and regulatory changes. Viable resource combinations were determined that would reliably satisfy the modeled constraints. The leastcost portfolio of resources for each scenario was chosen for further analysis. Stochastic risk analysis identified the expected customer costs and variability associated with the uncertainty surrounding system demand, fuel prices, CO 2 costs, and market prices. THEMES AND OBSERVATIONS A number of observations and themes emerged from the IRP Working Group discussions and the scenario analysis: Existing baseload resources are least cost even when considering environmental compliance uncertainty. Natural gas, in combination with energy efficiency and load management, is the least cost future resource additions. Renewable resources are added to meet regulatory requirements, but increase cost and degrade system operation. Environmental rules and regulations add significant costs to customers. THE MOST COSTEFFECTIVE PORTFOLIO The most costeffective portfolio meets electric system demand, provides acceptable system reliability and operational flexibility, meets renewable portfolio standard (RPS) and other regulatory requirements, and minimizes financial cost to the customer. Many of the planned resources are relatively small. Adding capacity in smaller increments allows PNM to meet growing demand and the required reserve margin, while avoiding lengthy periods of excess generation ahead of demand growth. The following table identifies the planned resource additions for the twenty year study period which, combined with existing resources, make up the most cost effective portfolio. 1

14 Executive Summary PNM IRP TABLE 11. RESOURCE ADDITIONS Year Resource MW MidForecast Energy Efficiency Renewable Resources Natural Gas Turbine Natural Gas Turbine Natural Gas Turbine Extend Load Management (LM) Renewable Resources Renewable Resources Natural Gas Turbine Natural Gas Turbine 177 ENERGY EFFICIENCY The most cost effective portfolio assumes continued growth of energy efficiency programs and participation levels based upon historical experience. Current programs are forecasted to meet the 2014 minimum Efficient Use of Energy Act (EUEA) goals of 411 gigawatt hours (GWh), with new programs totaling 593 GWh needed to meet the 822 GWh minimum in RENEWABLE RESOURCES The most cost effective resource portfolio meets Renewable Energy Act (REA) RPS requirements up to the established cost limits. PNM issued a request for proposals (RFP) for renewable resources in April 2011, and is currently evaluating proposals. PNM will continue to issue RFPs for renewable resources to meet regulatory requirements within the reasonable cost threshold (RCT) limits. REGULATORY UNCERTAINTY The most cost effective resource portfolio is sufficiently flexible to accommodate changing regulatory requirements including potential regulation of coal ash, greenhouse gas (GHG) emissions, and regional haze. Anticipated environmental regulations increase costs to customers and influence future resource selection but do not affect the longterm retention of existing resources. FOUR YEAR ACTION PLAN The most costeffective portfolio requires near term implementation of energy efficiency and load management (LM) programs and natural gas and renewable resource development. In addition, PNM will evaluate transmission solutions and potential technology solutions that may influence resource decision making during the next planning process. Implementation strategies include the following key actions: Develop LM programs to their full costeffective potential Develop renewable resources to comply with the REA requirements within the RCT Obtain New Mexico Public Regulation Commission (NMPRC) approval for energy efficiency programs, renewable procurements and natural gas additions Evaluate energy storage technologies Monitor technology improvements 2

15 Most Cost Effective Resource Portfolio PNM IRP MOST COST EFFECTIVE RESOURCE PORTFOLIO IRP Rule B(5) & G require identification of the most cost effective resource portfolio. PNM s most cost effective resource portfolio shown in Table 21, is the least cost alternative that meets system operational and reliability requirements for the mid load forecast and complies with the EUEA and REA within cost constraints. PNM considered both qualitative and quantitative risk. Existing generating facilities were identified as continuing to be longterm least cost resources. Since renewable resources were not least cost alternatives, they are included in the portfolio to meet regulatory requirements. Although the most cost effective portfolio details resource development over the next twenty years, the decision making emphasis is on resources required prior to The actions to implement this plan over the next four years are discussed in Section 3. The plan beyond 2017 is a guideline for resource development over the entire planning period and provides longterm direction for resource procurements. Scenario analysis concludes that PNM s existing coal, nuclear and natural gas baseload resources, in combination with new energy efficiency and wind, meet the twenty year baseload requirements and no new fossil fueled or nuclear baseload additions will be required. Such large scale projects would require longer planning periods and immediate siting and permitting actions. PNM will revisit resource development in 2017 and beyond in its 2014 IRP. The Scenario and Quantitative Risk sections identify and discuss alternative portfolios. Variations in resource selection resulting from potential changes in load, achievable energy efficiency and renewables, availability of resources, and operating costs are discussed in the Action Plan section. The most costeffective resource portfolio includes all existing resources since they are least cost. It should be noted that the Las Vegas, NM turbine is currently being decommissioned, and the Southwestern Public Service Company (SPS) Interruptible power purchase contract expired May 31, 2011; therefore, neither of these are included in the IRP resource portfolios beyond the spring of The scenario and financial risk analysis supports the continuation of all other existing resources, including: PNM owned coal, nuclear and natural gas plants Costeffectively securing the leased portions of Palo Verde Nuclear Generating Station (PVNGS) Costeffective continuation of contracts for DR programs, New Mexico Wind Energy Center (NMWEC), Delta Person, Valencia The most costeffective portfolio reflects the following attributes: Reliability obligations are met with a set of resources that have low overall system cost. Energy efficiency development exceeds EUEA minimum requirements within the context of the total resource cost (TRC) test. Renewable resources maximize diversity and RPS compliance within the RCT. Resources are sited and constructed within the constraints of the transmission system. Resources are appropriately sized to reduce operating costs and provide flexible operation to integrate additional renewable energy and meet operational requirements. 3

16 Most Cost Effective Resource Portfolio PNM IRP The portfolio increases resource diversity, balancing risks of natural gas price volatility and CO 2 costs (see Figure 21). All costs and benefits comparisons are based on net present value (NPV) calculations. These attributes meet the objective of the IRP process to develop a reliable, most costeffective resource portfolio that minimizes environmental impacts while retaining service quality and least cost measures. TABLE 21. PNM MOST COSTEFFECTIVE PORTFOLIO Year Resource MW Maintain Existing Resources: PVNGS, SJGS, Four Corners Power Plant, Reeves, Afton, Luna, Lordsburg, Solar, Solar w/battery Mid Energy Efficiency Renewable Resources Extend PVNGS Leases Natural Gas Addition Natural Gas Addition Natural Gas Addition Extend Load Management Renewable Resources Extend Delta Person Contract Renewable Resources Natural Gas Addition Natural Gas Addition Extend Valencia Contract Extend NMWEC Contract 204 ELEMENTS OF THE MOST COST EFFECTIVE PORTFOLIO Table 22 details the loads and resources (L&R) for the most cost effective resource portfolio and the mid load forecast. Alternative resource selection is further discussed in Section 3: FourYear Action Plan. 4

17 Most Cost Effective Resource Portfolio PNM IRP FirmDispatchable Resources TABLE 22. LOAD AND RESOURCES (L&R) TABLE (IRP RULE E) PUBLIC SERVICE COMPANY OF NEW MEXICO Total Load and Resource Projection (MW) for Summer Peak 2011 IRP Most Cost Effective Portfolio AOP Forecast Peak Demand 1,972 1,992 2,033 2,069 2,107 2,138 2,178 2,214 2,251 2,289 Projected Customer Sited PV (4) (9) (11) (12) (13) (13) (13) (13) (13) (13) Projected Energy Efficiency (17) (29) (41) (56) (68) (80) (88) (97) (107) (115) Net System Peak Demand Duty Cycle Four Corners B coal San Juan 1, 2, 3, 4 B coal Palo Verde Units 1 & 2 B nuclear Future Palo Verde Acquisitions B nuclear Reeves 1, 2, 3 P natural gas Afton CC I natural gas Luna I natural gas Lordsburg P natural gas Valencia (Purchase) P natural gas DeltaPerson (Purchase) P natural gas Future Natural Gas Additions P natural gas Demand Response Programs (Contract) P Future Demand Response (Contract) P Total 2,279 2,284 2,290 2,296 2,336 2,376 2,553 2,553 2,553 2,553 Firm Reserve Margin (MW) Firm Reserve Margin (%) 15.6% 14.7% 12.6% 10.9% 10.9% 11.1% 17.2% 15.3% 13.4% 11.5% NonFirm, Intermittent Resources NM Wind Energy Center (Purchase) wind PNM Solar Future Renewable Additions Total Reserve Margin including nonfirm (MW) Reserve Margin including nonfirm (%) 17.7% 18.0% 16.7% 16.2% 16.8% 17.6% 24.3% 22.7% 22.7% 21.0% The firm reserve margin is the difference between the forecast peak demand and the sum of the firmdispatchable resources. The nonfirm reserve margin is the difference between the net system peak demand and the sum of the firm and nonfirm resources. Intermittent resources may require additional regulating reserve margins. 5

18 Most CostEffective Resource Portfolio PNM IRP FIGURE 21. COMPARISON OF RESOURCE MIX Capacity 2030 Capacity Natural Gas, 38.74% Wind, 0.41% Solar, 0.65% Purchases, 4.10% Energy Efficiency, 3.64% Coal, 41.45% Wind, 0.85% Solar, 1.52% Purchases, 0.00% Energy Efficiency, 4.83% Coal, 31.40% Nuclear, 11.00% Natural Gas, 53.07% Nuclear, 8.33% ENERGY EFFICIENCY AND LOAD MANAGEMENT Scenario and financial risk analysis showed that given the probabilities of various fuel and CO 2 costs, energy efficiency is a leastcost resource. The mid level exceeds the EUEA minimum energy saving targets of 411 GWh by 2014 and 822 GWh by 2020, as shown in Figure 22, and is considered achievable. Additionally, energy efficiency contributes to peak demand reduction. These demand reductions are considered nonfirm in the L&R table (Table 22), until the actual reductions are measured and verified; however, after verification they are considered firm and embedded in the load forecast. Demand Response (at current program cost projections) is a lower cost resource than natural gas replacement resources. PNM will maximize the use of costeffective DR that can be considered a firm dispatchable resource based on characteristics of the program contracts. These resources are shown as firm dispatchable resources in the Load and Resources Table. All energy efficiency and LM programs must meet the EUEA requirements, including satisfying the TRC, and will be subject to Commission approval in program filings. FIGURE 22. COMPARISON OF EXISTING AND PLANNED ENERGY EFFICIENCY VS. EUEA STANDARD PNM Program Annual Energy Savings EUEA Minimum Standard Annual Energy Savings in GWh

19 Most CostEffective Resource Portfolio PNM IRP RENEWABLE ENERGY Scenario and financial risk analysis determined that renewable resources were not leastcost, except when conditions causing extreme operating costs arise, including extremely high fuel and CO2 costs. Nonetheless, renewable resources are included in the most costeffective portfolio up to the requirements of the REA. Renewable resources have lower risk exposure to high CO2 costs; however, renewable resources also can expose customers to daily price volatility, because the unpredictable intermittent nature of these resources requires the use of dispatchable resources, primarily natural gas to firmup the supply. Dispatchable resources have associated CO2 costs and fuel costs. The renewable resources identified in the most costeffective resource portfolio are wind and solar; PNM selected wind resources as leastcost renewable additions in the early timeframe, as they maximize renewable development under the RCT and also help offset the need for new baseload additions. Solar resource additions are selected in the later timeframe as a renewable least cost option when projected solar prices decline and their higher reserve margin contribution on summer peak outweigh the benefits of wind resources. PNM did not initially select other renewable technologies due to availability issues, but will continue to pursue these technologies for possible incorporation in future portfolios. The FourYear Action Plan section discusses the optimal implementation of additional renewable resources in the resource portfolio during the planning period. Renewable development will depend on the cost of existing renewable programs, the cost of renewable additions, and the price of fuel and other costs that can be avoided by the use of renewables. NATURAL GAS RESOURCES Initial portfolio analysis selected large natural gas resource additions to satisfy load and meet reserve margin requirements. Upon closer review, however, these largersized gas resource additions were rejected in favor of smallersized units based on qualitative operational factors that could not be explicitly included in the modeling. To balance the system to provide reliable service, meet North American Electric Reliability Council (NERC) standards, and even out the cost to the consumer, it is beneficial to have a variety of resources in the portfolio. This is especially important with the addition of intermittent renewable resources to meet the RPS, as these resources require the accompanying availability of fast start, dispatchable resources for regulation. To meet the operational requirements, the most costeffective portfolio includes smaller gas turbines that provide more flexible operation. By including diversely sized units in its portfolio, PNM can optimally respond to fluctuating operating conditions. The smaller aeroderivative units planned for are the most flexible gas turbines, as they can be started and stopped with minimum run times without cost penalties. Compared to larger, heavy frame gas turbines, they also can deliver better fuel efficiencies under operating conditions of varying dispatch. This lowers cost and improves operating capability. Meeting reserve margin requirements with smaller, incremental capacity also reduces capital costs. The diversity of existing and planned gas units is shown in Table 23. 7

20 Most CostEffective Resource Portfolio PNM IRP TABLE 23. GAS UNIT DIVERSITY CHART Installed Capacity in MW by Technology Technology Existing By 2030 Combined cycle Steam peaking Large Turbine peaking Medium Turbine peaking Aeroderivative peaking Total Natural Gas Capacity PORTFOLIO RISK AND MITIGATION STRATEGIES FINANCIAL PNM conducted an evaluation of the financial risk to consumers of various portfolios, which incorporated fuel price and load volatility and the effects of anticipated environmental regulations. PNM tested and measured the risk of cost variability using a Monte Carlo simulation analysis. As discussed in Section 12, PNM selected a 95% confidence level as the appropriate risk measure. The most cost effective portfolio balances least expected cost and least variable risk in a portfolio that meets necessary operating and compliance requirements. COMPETITIVE A qualitative risk may arise if PNM s costs rise inconsistently with those of other regional utilities, creating a competitive disadvantage in attracting and maintaining customers in PNM s service area and in making offsystem sales. For example, to the extent PNM s portfolio costs are increased by the need to satisfy state portfolio and environmental requirements that are more stringent than those imposed on neighboring utilities, PNM could face a reduction in customers or customer growth that could lead to even higher costs for remaining customers. New Mexico s new GHG Rules (discussed in Sections 4 and 11) are examples of local environmental requirements that will add costs to electricity production within the state and that could make it more difficult for New Mexico and its utilities to compete with their regional counterparts for economic development and wholesale sales opportunities. RELIABILITY AND RESERVE MARGIN REQUIREMENTS The most costeffective resource portfolio maintains the reserve margin above the minimum level of 13% from , when the contributions of renewables to meeting peak are included. If peak demand grows faster than the mid level projection, there is a risk that the reserve margin could fall below 13% and a potential that this could lead to penalties within WECC and NERC. To mitigate this risk, PNM is evaluating additional LM potential and completing siting studies so that 8

21 Most CostEffective Resource Portfolio PNM IRP the development of natural gas resources could be accelerated, if necessary. Peak demand reductions due to energy efficiency, which are significant during the planning period, may not reach forecasted levels. PNM includes energy efficiency in its nonfirm reserve margin calculation until those savings have been verified and embedded in the load forecast. This ensures that the portfolio will meet the required reserve margin, regardless of whether peak demand reductions from energy efficiency measures materialize as projected. The portfolio meets all existing state and regional reliability criteria and allows for reserve sharing with other utilities to enhance reliability for generation contingencies. TECHNOLOGY Advances in generation technology provide the potential for cost reductions and performance improvements for both renewable and traditional resources. Because it was assumed for modeling purposes that a larger natural gas turbine would have the same operating characteristics as the smaller aeroderivative turbines, most of the scenarios select larger turbines. This modeling assumption was based on recent developments in large turbine, heavy frame technology which has not yet been tested in actual utility operations. Therefore, for the most costeffective portfolio in the short term, PNM has selected aeroderivative technology, which is a proven technology that is known to deliver economic operating characteristics required for reliable system operation. The larger heavy frame turbine with the enhanced features is still needed for 2017, after the technology has matured and the operational characteristics are demonstrated. OPERATIONAL In the most costeffective resource portfolio, the smaller natural gas turbines add important operational flexibility to the system, which provides for efficient system regulation. As new renewable resources are developed for PNM resource requirements, additional operational flexibility will be required. The most costeffective portfolio included natural gas additions that were tailored to meet the operational requirements. PNM may also be required to provide regulation to Federal Energy Regulatory Commission (FERC) customers within PNM s balancing authority, which could modify the optimal quantity, size, and timing of natural gas resource additions. PNM will be conducting a siting study for future expansion to facilitate system response capability. In addition, PNM participates in regional planning groups to develop policies in which the balancing area can be expanded to reduce the regulation requirements on individual utilities, similar to the participation benefits in reserve sharing groups. TRANSMISSION CONSTRAINTS The resources identified in the most costeffective resource portfolio will be located within the Path 48 transmission constrained area. While this will not exacerbate constraint issues, it also does not resolve existing transmission constraints. PNM will continue working with a variety of regional planning groups on transmission expansion. The New Mexico GHG cap regulation is expected to further limit PNM s resource siting options and conflict with PNM s objective to site generating resources loadside within transmission contrained areas. PNM will need to analyze these issues further as part of a transmission study to identify the best strategies for resource siting and transmission expansion. 9

22 Most CostEffective Resource Portfolio PNM IRP FUEL SUPPLY The fuel supply section (Section 9) discusses the abundance of wind, solar, coal, and natural gas supplies in New Mexico. PNM is evaluating new wind and solar resources considering geographic diversity to reduce the risk of simultaneous loss of all renewable resources. Geographic dispersion improves PNM s ability to effectively operate the overall system when fluctuations of individual resources occur. To mitigate gas supply concerns, a majority of PNM s natural gas resources have access to multiple natural gas suppliers, and there is geographic diversity among plants. In developing the resources projected in the most cost effective portfolio PNM will employ the principles of geographic diversity and use of multiple gas supplies. Fuel supply risk for natural gas resources is greatest during the winter when there are other competing uses. As part of resource design for new natural gas facilities, PNM will evaluate what portion of the new resources should have dual fuel capability to mitigate winter fuel supply concerns. PRICE VOLATILITY Risk exposure to price volatility exists for all resources that rely upon gas, coal or nuclear fuel. Even renewable resources depend to an extent on such fuels because their intermittent output must be firmedup by regulation, which generally comes from natural gas and coal. PNM s diverse portfolio of coal, gas and nuclear resources mitigates the risk to customers due to the price volatility of any single fuel type. ANTICIPATED ENVIRONMENTAL REGULATIONS This IRP analyzes anticipated environmental regulations, as fully discussed in Section 4, The IRP Planning Approach and Section 11, Scenario Analysis. Even though the adoption of any new regulation is uncertain, the associated potential outcomes have been reduced. PNM s most costeffective portfolio minimizes cost and uncertainty of the total portfolio, even when considering uncertain environmental regulations. Environmental regulations may increase costs for capital investments and/or resource operations; paying these costs and continuing to operate the existing facilities represents the overall leastcost risk mitigation strategy. The cost of other alternatives would be much greater to PNM customers. 10

23 FourYear Action Plan PNM IRP I of the IRP Rule requires an action plan for a four year planning period from the date of the filing. 3. FOURYEAR ACTION PLAN FOUR YEAR ACTION PLAN PNM s fouryear action plan identifies the steps required in to implement the resource acquisitions in this 20 year IRP. This includes additions after 2015 that require actions during to ensure they are in place as scheduled. Since PNM s most cost effective portfolio does not require any large baseload additions with long development times, this action plan describes implementation of resources identified through PNM s 2014 IRP will provide an action plan for resources to be added through 2018 and beyond. PNM s current action plan is shown in Table 31. TABLE IMPLEMENTATION STRATEGY Implementation Strategy Action Timing and Status Fully Develop Energy Efficiency Potential 1. Evaluate energy efficiency as part of the process for preparing annual energy efficiency filings for the NMPRC. 2. Propose aggressive energy efficiency programs meeting the TRC test. 1. PNM is participating in a statewide potential study. PNM will use the study to benchmark the energy efficiency forecast and help identify additional program applications. 2. PNM received partial approval of programs filed September 15, Additional program filings will be made at least every two years or annually, depending on numerous factors such as actual performance of existing programs and identified potential for new offerings. Fully Develop Cost Effective Load Management Potential 1. Determine best strategy to extend existing programs beyond Investigate potential for additional demand response and technologies that can shift peak demand, such as thermal energy storage. 1. Preliminary discussions have been initiated with PNM's two existing contractors. 2. PNM will set schedules for initiating new contracts, prior to the need for a new gas turbine with the objective to delay the gas addition if enough potential exists, provided PNM receives NMPRC approval. 11

24 FourYear Action Plan PNM IRP Implementation Strategy Action Timing and Status Develop CostEffective Diverse Renewable Resources 1. Periodically issue RFPs to evaluate renewable resource availability and price 2. Annually file Renewable Energy Plans for NMPRC approval 1. PNM is currently evaluating the results of renewable RFP proposals submitted on June 10, PNM will issue additional RFPs for renewable resources in years when PNM requires additional resources to meet RPS and diversity requirements and when the RCT isn't exceeded. PNM filed a renewable plan on July 1, 2011 and will file additional plans every July 1st. Add Natural GasFired Resources to meet system requirements in Conduct preliminary site selection study encompassing all natural gas resource types. 2. Issue an RFP for natural gas resources to determine optimal technology, location, and ownership structure. 3. File for CCN approval from NMPRC for identified optimal gas resource(s) 1. Site scoping has been ongoing since 2008 IRP and will continue through Preparations for issuing an RFP have commenced. The RFP is anticipated to be issued no later than the first quarter of Initial preparations for a CCN have commenced. The CCN for additions is anticipated to be filed in Evaluate LongTerm Transmission Requirements 1. Monitor and participate in regional transmission development activities 2. Evaluate increased transmission import capability through PNM s transmission planning stakeholder process. 1. PNM will continue to participate in regional planning groups to monitor transmission expansion plans. As projects develop, PNM will evaluate how these improvements might influence future resource decisions. 2. To be evaluated in conjunction with the March 2012 transmission stakeholder process. 12

25 FourYear Action Plan PNM IRP Implementation Strategy Action Timing and Status Evaluate Storage Viability, Benefits, & Costs 1. Test and develop a report on ability of batteries to firm the dispatch of energy generated by PV systems. 2. Monitor industry research on broad spectrum of storage technologies. 1. System installation under construction. Testing will begin in the fall of Ongoing. Monitor Deployment of Smart Grid and Remote Metering 1. Monitor deployment by affiliate in Texas and evaluate lessons learned. 2. Monitor other industry participants to determine impacts and benefits of emerging grid and metering technologies 1. Currently following various pilot projects. 2. Ongoing. Monitor New Resource Technologies and Enhancements to Existing Technologies 1. Monitor advancements in resource technologies including modular nuclear reactors, carbon capture, gas efficiency improvements, renewable technology and efficiency improvements 1. Currently participating in industrywide research forums and working with resource manufacturers and developers. Monitor Deployment of Electric Vehicles 1. Monitor industry research regarding impacts and penetration of electric vehicles 1. Monitoring and research is ongoing. PNM will also prepare for the initial vehicle launches in New Mexico. Monitor, Evaluate and Negotiate Existing Resource Contracts 1. Extend SJGS fuel supply beyond PNM is currently working with existing supplier and investigating alternative sources. 2. Secure PVNGS leases 2. PNM is continuously monitoring opportunities to buy back additional PVNGS leases. 13

26 FourYear Action Plan PNM IRP ACTION PLAN ALTERNATIVES The IRP process identified several alternative paths for the action plan. These alternatives account for variations in system conditions that would require changes in resource type or timing. More extreme changes, outside the range of outcomes analyzed in this plan, could require a reevaluation of the overall plan and notification to the NMPRC. The action alternatives identified within the scope of this plan are described in the following paragraphs. LOAD GROWTH The growth rate of peak demand drives the new resource selection process. PNM analyzed a broad range of potential future peak demands. While the 20year differential between the high and low growth forecasts is 964 MW, the deviation by 2017 is nearly 300 MW, which represents a significant range in the amount of resources required within the action plan period. PNM s most cost effective portfolio provides resources for the most likely mid load forecast. Lower peak demand growth could delay a new natural gas resource to outside the action plan period. Higher peak demand growth could accelerate the need to add a natural gas resource by as much as two years. Such acceleration could require the implementation of highercost interim measures during the development and construction phases of a new plant, such as expanding LM, entering into shortterm PPAs (if available within transmission constraints), or developing resources that require shorter approval and construction timelines, such as solar resources. Higher peak demand growth would also trigger the addition of a baseload combined cycle natural gas generator in 2018, which could require additional development activities within the timeframe. JOINTLY OWNED FACILITIES Analysis shows that PNM s joint ownership of existing facilities, including its coal resources, is costeffective for PNM s customers; however, joint ownership also entails some risk. For example, if a joint owner chooses to discontinue its participation in a plant at the end of the term of a participation agreement, due to changes in regulations or for business reasons, PNM and other remaining owners would have to decide whether to expand their participation percentages in the facility, seek new owners, or retire the facility. If PNM s coal facilities were retired, or if existing leases at PVNGS were not secured for the plant life, the IRP indicates PNM would have to replace these resources with natural gas combined cycle generation, at a significant penalty in terms of cost to customers, and would have to initiate an evaluation process to replace the baseload resources. ENERGY EFFICIENCY Future energy efficiency programs are not specifically identified in this plan. Specific program development will be done within the context of the EUEA and the EE Rule, including adherence to the TRC test. As required by the EE Rule, PNM incorporates a public advisory process in its energy efficiency planning process. Each year, PNM evaluates energy efficiency programs using the most current avoided cost information and the same methodologies contained within this IRP. The IRP results show that the optimal level of energy efficiency program development depends on the input conditions, including load growth (both demand and energy), fuel prices, and CO 2 costs. Each year, 14

27 FourYear Action Plan PNM IRP the energy efficiency programs will reflect the most current assumptions for these parameters in applying the TRC test. Additionally, energy efficiency programs depend on NMPRC approval and public adoption. If more programs meet the TRC test, gain NMPRC approval, and achieve widespread public adoption, development of a natural gas turbine could be delayed. However, if fewer measures meet the TRC test, if the specific measures contribute less than anticipated to peak demand reductions, if the NMPRC approves fewer measures, or the public adopts measures at a slower pace than estimated, then natural gas generation may need to be accelerated, and PNM may need future natural gas combined cycle facilities in addition to natural gas turbines. LOAD MANAGEMENT LM programs are a subset of energy efficiency programs that must comply with the EUEA and EE Rule, including the TRC. PNM s plan includes load shifting through DR programs operated under two existing contracts. As these contracts expire and PNM requires additional resources, PNM will evaluate the potential for additional LM programs with the capability of delaying the acquisition of equivalent amounts of natural gas resources. RENEWABLE PROCUREMENTS Renewable additions in the action plan period were added exclusively for compliance with RPS mandates and in accordance with Rule 572 in its current form. If Rule 572 is modified, PNM will pursue renewable additions that are compliant with the modifications. PNM will also monitor price and availability of renewable resources and request approval of the leastcost alternatives that meet compliance requirements. NATURAL GAS ADDITION TIMING Energy efficiency, LM and renewables can impact the timing of the next natural gas resource; however, there is a limit to the effectiveness of these resources in delaying the need for new natural gas resources. PNM typically needs resources to meet summer peak requirements, but must also consider how resources meet all time periods including winter peaks. Load management and solar resources do not contribute to meeting the winter peak demand, and energy efficiency measures also impact winter peak differently than summer peak. Therefore, the timing of a natural gas resource can be delayed only as long as reliability criteria are met for both summer and winter peak conditions. Generally, the combination of LM and solar resources in excess of the 200 MW winter/summer differential will not delay new natural gas resources. Currently, LM and solar resources together contribute about 117 MW at the time of summer peak demand, making the effective amount of new resources that can delay a natural gas resource equal to 83 MW. LOSS OF EXISTING AVAILABLE RESOURCES This IRP assumes the availability of existing resources and contracts. Shortterm unavailability caused by forced outages is incorporated in the planning reserve margin and additionally covered via interutility reserve sharing agreements. Longterm unavailability caused by unforeseen events, such as extreme weather or the reduction or termination of an existing contracted resource, could necessitate adjustments to the overall plan. The loss of resources would necessitate replacement with other resources to be determined based on a variety of factors, including cost, risk, and 15

28 FourYear Action Plan PNM IRP reliability. Loss of LM, energy efficiency or renewable resources would require investigation to determine the availability and costeffectiveness of likekind resources that complied with regulatory requirements. Natural gas additions either combined cycle or peaking technologies, would be considered depending on the characteristics of the lost resource. NATURAL GAS AND CO2 COSTS The most cost effective resource portfolio withstands high variability in natural gas pricing and potential CO 2 costs. Variations in these costs within the anticipated range will not impact the action plan. The next new resource after costeffective energy efficiency and required renewables is natural gas. It would take very extreme increases in both natural gas prices and CO 2 costs or a radical decline in the costs to develop nuclear, coal, or renewables to shift the resource selection away from natural gas. Should any of these circumstances occur prior to the next IRP, PNM will reevaluate its resource selection and notify the Commission of any material changes and revisions to the action plan. 16

29 SECTION II PNM IRP PART II: PROCESS AND TECHNICAL ANALYSIS

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31 Integrated Resource Planning Approach PNM IRP INTEGRATED RESOURCE PLANNING APPROACH OVERVIEW PNM s integrated resource planning approach identifies the most costeffective portfolio of resources to fulfill the energy needs of customers over the twenty year period , which includes meeting the requirements of the EUEA and the REA. The Integrated Resources Plan Rule NMAC (IRP Rule) defines the most costeffective resource portfolio as one that comprises resources that minimize the net present value of revenue requirements proposed by the utility to meet electric system demand during the planning period consistent with reliability and risk considerations. The IRP rule and other acts and regulations governing this plan can be accessed via the internet, as listed in Appendix D. Reference IRP Rule section B, Contents of IRP for Electric Utilities. SCOPE This plan identifies a resource portfolio that meets the projected electric demands of PNM s jurisdictional electric customers over the next twenty years in the most costeffective way. The planning process identifies, on a macro level, resources that reliably meet system needs (including delivery) and regulatory obligations and that are least cost. The supporting analyses identify the leastcost resource portfolios associated with various conditions. IRP RULE REQUIREMENTS In accordance with the IRP Rule, section , Contents of IRP for Electric Utilities, PNM s IRP contains the following sections: Part I Summary, Most Cost Effective Portfolio, and Action Plan Section 1: Executive Summary Section 2: An assessment of the most costeffective resource portfolio and alternative portfolios ( G) Section 3: A fouryear action plan that outlines the steps needed to implement the resources identified in the most costeffective resource portfolio ( I) Part II Process and Technical Analysis Section 4: A discussion of the integrated resource planning approach including compliance and reserve margin requirements ( C.10) Section 5: Status Report on 2008 IRP ( I) Section 6: A description of the public advisory process ( H) Section 7: A review of existing resources, rates and transmission ( C and F(3)) Section 8: Forecasting system load and Loads and Resources Table ( D and E) Section 9: An assessment of supply side fuels ( F(2)) Section 10: A review of potential future resource options ( F) Section 11: Scenario Analysis ( G) Section 12: Quantitative Analysis ( G) Section 13: Qualitative analysis ( G) 19

32 Integrated Resource Planning Approach PNM IRP ABOUT THE INTEGRATED RESOURCE PLANNING PROCESS The IRP broadly identifies future actions to ensure that PNM continues to meet the energy needs of its customers and existing and reasonably expected regulatory requirements. This is PNM s second IRP filing under the IRP Rule issued by the NMPRC on March 1, The IRP Rule requires PNM to complete an IRP every three years. For planning purposes, PNM used known and reasonably expected variables to develop most assumptions. These included assumptions about technology availability and price, current regulations, anticipated future regulations, and consumer usage patterns. This planning process allowed PNM to create a portfolio that has the ability to respond to future events to ensure the availability of adequate resources to meet demand and maintain service reliability; however, it will not capture unanticipated changes such as innovation that may make new technologies feasible within the longrange planning timeframe. PNM updates its plan every three years or sooner, if material changes in assumptions would lead to a different course of action. APPROACH PNM designed a multidimensional process for the IRP to determine the most costeffective resource portfolio, along with alternative portfolios for the twentyyear period from 2011 through The process included reviewing existing resources, forecasting future energy needs, examining future resource options, and designing scenarios to evaluate various portfolios to meet requirements. The PNM Integrated Resource Planning group worked with the IRP Working Group to evaluate cost, proposed environmental policy impacts, and reliability factors while determining the most costeffective resource portfolio. PUBLIC PARTICIPATION PNM invited the public to participate in the planning process as it progressed. Goals of the process included increased understanding of the resource options available and the inherent tradeoffs between the cost, environmental concerns, and reliability associated with choosing one resource over another. Public participation, along with meeting dates and discussion items are detailed in The Public Advisory Process section 6. Public participation in this IRP provided transparency to PNM s planning efforts. A diverse group of individuals and organizations actively participated in the planning process through indepth discussions, detailed questions, and diverse comments about resource planning, modeling activities, and review of this report. A significant contribution by members of the IRP Working Group included the adoption of alternative scenarios and assumptions (detailed in the Scenario Analysis section 11) proposed by participants and incorporated into the IRP process. DETERMINING THE MOST COSTEFFECTIVE RESOURCE PORTFOLIO PNM identified the most costeffective resource portfolio by considering a variety of factors, including regulatory requirements, environmental impact, and system reliability. PNM evaluated each of these factors for potential financial and nonfinancial risk. The fouryear Action Plan for the period from 2011 through 2015 in Section 3 outlines the nearterm steps to implement the most costeffective resource portfolio. 20

33 Integrated Resource Planning Approach PNM IRP ADDITIONAL RESOURCE PLANNING REQUIREMENTS In addition to the IRP Rule requirements, the IRP must comply with EE requirements, environmental regulations, renewable energy requirements, system reliability standards, and Commission orders, including orders approving stipulated agreements. The following paragraphs review each of the additional resource planning considerations. PNM s IRP complies with: IRP Rule requirements Energy efficiency requirements Environmental regulations Renewable energy requirements System reliability standards Stipulated agreement terms ENERGY EFFICIENCY REQUIREMENTS The EUEA and the EE Rule ( NMAC) require utilities to include costeffective EE and DR programs in their resource portfolios. The EUEA and the EE Rule ( NMAC) establish costeffectiveness as a mandatory criterion for all programs. The EUEA and the EE Rule require utilities to implement all costeffective and achievable EE programs and file an annual EE Program Report with the NMPRC. The EUEA requires utilities to realize energy savings of at least 5% by 2014 and 10% by 2020 based on 2005 retail sales, or energy sales to end users, subject to the costeffectiveness and achievability criteria. In addition, the EUEA requires the NMPRC to balance customer and shareholder interests by removing any disincentives or barriers to implementation, and by providing incentives to promote demandside resources. The Energy Efficiency Rule allows PNM to earn incentives on costeffective load management programs through an approved tariff rider. ENVIRONMENTAL REGULATIONS EUEA energy efficiency requirements are: 5% by % by 2020 NATIONAL AMBIENT AIR QUALITY STANDARDS (NAAQS) UNDER THE CLEAN AIR ACT The federal Clean Air Act (CAA) governs air quality in this country. The purpose of the act is to protect and enhance the quality of the Nation s air resources to promote the public health and welfare. The provisions of the act are implemented in federal regulations developed by the Environmental Protection Agency (EPA). These regulations are applied and enforced by individual states. The National Ambient Air Quality Standard (NAAQS) program, a centerpiece of the CAA, addresses the most common air pollutants in this country that are harmful to human health and the environment. The EPA sets ambient concentration thresholds for these pollutants at levels that protect human health with an adequate margin of safety, and reviews these standards every five years to determine if they need to be revised. The emissions of most concern are Nitrogen Oxides (NOx), Sulfur Dioxide (SO2), particulate matter (PM), and ozone. Each state develops sourcespecific emissions limits in regulations to implement the NAAQS program. To prevent significant 21

34 Integrated Resource Planning Approach PNM IRP deterioration in air quality, the CAA implemented the New Source Review (NSR) program. This program requires more stringent control technologies on new and modified sources that are included in air permits issued by the state. Finally, the CAA addresses specific pollution problems, such as emitting mercury from coalfired power plants. Currently, most electric generation comes from fossil fuels such as coal plants and natural gas plants. These plants are subject to regulation under the CAA. The cost of compliance with the CAA is a necessary factor that is considered in the IRP process. The CAA regulations are subject to change, which affects cost estimates for compliance. The trend in recent years has been towards more regulation of air emissions from fossil fuel sources. REGIONAL HAZE Regional haze is defined as visibility impairment that is caused by the emission of air pollutants from numerous sources located over a wide geographical area. In 1977, the CAA set a goal to remedy any existing visibility impairment, and prevent any future impairment from manmade pollution at 156 mandatory Class I Federal Areas (national parks and wilderness areas) across the United States. The 1990 amendments to the CAA required that the EPA address visibility impairment due to regional haze. In 1999, the EPA promulgated a regulation to address visibility in the Class I areas due to regional haze. The final Clean Air Visibility Rule was promulgated in July 2005 along with guidelines for Best Available Retrofit Technology (BART) determinations for appropriate pollution controls at BARTeligible facilities. The rule requires states to identify certain industrial facilities and power plants that impact visibility in the 156 Class I areas and then determine the type of emission controls that constitute BART for each specific facility. To enable a state to determine BART for a facility, the facility submits a BART analysis that includes a recommendation for BART. Both San Juan Generating Station (SJGS) and the Four Corners Power Plant are BARTeligible sources and will be required to add emission controls to address the Regional Haze regulation. The New Mexico EIB has determined that selective noncatalytic reduction (SNCR) constitutes BART for SJGS. EPA has provisionally determined that selective catalytic reduction (SCR) technology on all four units of SJGS, and all five units for Four Corners Power Plant, is required for BART. Four Corners Power Plant is presently considering options with respect to possible retirement of certain units. The final BART determination for SJGS is currently pending. The installation of additional emissions controls at SJCC and Four Corners Power Plant to comply with the BART requirements will result in additional costs. Section 11: Scenario Analysis details how various environmental outcomes were modeled in the IRP. OZONE STANDARD The EPA has established an ambient concentration limit (NAAQS) for groundlevel ozone. EPA plans to strengthen the 8hour ozone parts per million (ppm) standard by revising the current standard of ppm and setting the new standard in the range of to ppm. The EPA proposed these new values for the standard on January 6, 2010 and is scheduled to issue a final decision by July, The EPA proposes to designate nonattainment areas (i.e., those areas across the U.S. that exceed the new ozone standard level) by August It is uncertain if some counties within New Mexico may become nonattainment for ozone and how designated nonattainment areas will develop overall reduction plans. Due to the highly uncertain nature of ozone regulations, specific 22

35 Integrated Resource Planning Approach PNM IRP modeling was not done; however, IRP Working Group participants agreed that CO 2 costs added to fossil fueled generation were sufficiently high and served as a proxy for other unknown and uncertain regulations that may apply to these generation plants. HAZARDOUS AIR POLLUTANTS (INCLUDING MERCURY) On March 16, 2011, EPA submitted for publication in the Federal Register the proposed National Emission Standards for Hazardous Air Pollutants from Coal and Oilfired Electric Utility Steam Generating Units and Standards of Performance for FossilFuelFired Electric Utility, Industrial CommercialInstitutional, and Small IndustrialCommercialInstitutional Steam Generating Units, commonly referred to as the EGU MACT. The proposed regulations for existing coalfired units (e.g., SJGS boilers) establish emission standards for a list of hazardous air pollutants (HAP). Of those affecting PNM s power generation fleet are PM (surrogate for nonmercury (Hg) HAP metals), SO 2 (surrogate for hydrogen chloride) and mercury (minimum 91% control efficiency). The pollution control equipment currently used at the SJGS is anticipated to meet all of the proposed emissions standards. The EGU MACT is scheduled to be finalized under a court order on November 16, COAL ASH On May 4, 2010, EPA released its proposed rule on the regulation of coal combustion byproducts (CCBs) such as coal ash. The proposal includes two options for regulation of coal ash. These options include: 1) The regulation of CCBs as a hazardous waste under the Resource Conservation and Recovery Act (RCRA) 2) The regulation of CCBs as a nonhazardous solid waste under RCRA A final EPA rule is expected late 2012 to early The proposed CCB regulations by EPA could impact SJGS and the Four Corners Power Plant. Currently, CCBs are placed in the mine pits of the related coal mines for SJGS and Four Corners Power Plant. If CCBs are regulated as hazardous waste, mine placement may no longer be an option, and other disposal options would have to be considered. Under this scenario, the costs associated with the handling and disposal of CCBs will increase. The Office of Surface Mining (OSM) recently indicated that it intends to renew its effort to develop regulations under the Surface Mining Control and Reclamation Act (SMCRA) to address mine placement of coal ash. OSM s draft rulemaking schedule targets an April 2012 publication in the Federal Register. Additional requirements for placement of CCBs in mine pits could also increase the cost of CCB handling and disposal. The scope of future regulation of CCB disposal remains uncertain. Depending on how CCBs are regulated, the cost of regulatory compliance will vary widely. Section 11: Scenario Analysis details how various outcomes for coal ash were modeled in the IRP. CLIMATE CHANGE The scope, direction, and cost of emerging policy actions related to global climate change creates uncertainty for the electric utility industry and may substantially impact integrated resource 23

36 Integrated Resource Planning Approach PNM IRP planning. Members of the IRP Working Group differed significantly on expectations for climate change. This division of opinion included questions on the validity of the scientific evidence, likely political outcomes, and cost projections. As a result, the impact of climate change was the most heavily analyzed input variable in this IRP. Under the May 9, 1992 United Nations Framework Convention on Climate Change, the United States committed to stabilizing GHG concentrations at specified levels. Since that time, the U.S. Congress has considered various proposals to regulate GHG emissions, but none have been passed into law thus far. Also, the State of New Mexico and the federal EPA have initiated regulatory actions that will eventually restrict GHG emissions. While the ultimate adoption and/or form of policy are unknown, future emissions of GHG are likely to have significant costs, which must be considered in resource planning. In 2010, under Governor Bill Richardson s administration, the NM Environmental Improvement Board (EIB) approved two GHG restriction regulations, a cap and trade rule ( NMAC), and a cap rule ( NMAC or NM GHG Cap Rule). Required compliance with Rule 350 could take place as early as 2012, depending on whether a sufficient carbon trading market develops under the Western Climate Initiative members. The NM GHG Cap Rule is secondary in that it takes effect in 2013 only if Rule 350 cannot be implemented. Both rules are under appeal in the courts. Also, current Governor Susanna Martinez has indicated opposition to the rules. The Governor s Small BusinessFriendly Task Force Report has recommended rescission or revision of NMAC Despite the uncertainty around the New Mexico rules and possible federal legislation, IRP planning applies standardized carbon emission cost assumptions in most cases analyzed. More discussion of IRP CO 2 cost modeling is provided in Section 11. Current federal and regional carbon legislation proposals typically include similar elements. First, the proposals often include emission reduction under a program of emission allowances using a cap and trade mechanism. For each ton of CO 2, the emitting entity would be required to obtain an allowance. Under these proposals, the government would reduce the number of allowances available each year, thereby reducing CO 2 emissions. Allowances will be granted to existing sources, and allowances can be bought and sold. This market driven system (cap and trade) has the advantage of moving allowances to the highest value emission sources and rewarding reductions in emissions. A second component of proposed legislation suggests that entities currently emitting are granted some allowances at no cost. This would mitigate the immediate financial impact on emitting industries or, in the case of the utility industry, the impact on customers. Third, proposed legislation often includes a cost threshold that may ease the restrictions on CO 2 emissions, in the event the costs of compliance reach a level that would impose excessive adverse impacts cost on consumers or the economy. Section 11: Scenario Analysis details how various proposals for CO 2 costs were modeled in the IRP. RENEWABLE ENERGY REQUIREMENTS The New Mexico REA and RPS Rule ( NMAC) establish PNM s Renewable Portfolio Standard (RPS). Each year, PNM files an annual Renewable Energy Portfolio Report and a Renewable Energy Portfolio Procurement Plan to request NMPRC approval for resource additions that are necessary to maintain compliance with this standard. 24

37 Integrated Resource Planning Approach PNM IRP RPS RENEWABLE ENERGY REQUIREMENTS Subject to the RCT, the RPS Rule outlines renewable energy requirements that vary each year. These requirements are a function of PNM s retail energy forecast. The RPS requires a resource portfolio that includes renewables that meet the following thresholds: No less than 10% of retail energy needs for calendar years 2011 through 2014 No less than 15% of retail energy needs for calendar years 2015 through 2019 No less than 20% of retail energy needs for calendar year 2020 and subsequent years According to section A(5) of the REA, a renewable portfolio plan should be, reasonable as to its terms and conditions considering price, costs of interconnection and transmission, availability, dispatch ability, renewable energy certificate values and portfolio diversification requirements. The REA and Rule 572 also provide costbased exclusions for large nongovernmental customers. RPS RENEWABLE ENERGY DIVERSITY REQUIREMENTS The RPS Rule requires a fully diversified renewable energy portfolio which is defined as one that includes: Wind resources of no less than 20% of the RPS requirement Solar resources of no less than 20% Nonwind, nonsolar resources of no less than 10% DG resources of no less than 1.5% from 2011 through 2014, and no less than 3% thereafter REASONABLE COST THRESHOLD The RPS Rule states that a public utility shall not be required to add renewable energy to its electric energy supply portfolio or achieve a fully diversified portfolio at a cost above the RCT. Thus, the RCT relieves the utility of the obligation to add renewable resources if the customer rate impact of doing so exceeds: 2.0% in 2011, increasing yearly by 0.25% until % in 2015 and thereafter STIPULATED AGREEMENTS Two stipulated agreements entered into in connection with NMPRC cases, and approved by the Commission, affect PNM s 2011 IRP. 1. Utility Case 3137 Stipulation Transition Plan Filed Pursuant to the Electric Utility Industry Restructuring Act of 1999 and approved by the NMPRC on January 28, 2003 The Stipulation in Case 3137 includes several elements that impact resource planning. The stipulation identifies which loads and resources are to be included in jurisdictional resource planning. It also establishes a reserve margin and provides the amount of capacity from each resource that should be counted against the reserve requirement. 25

38 Integrated Resource Planning Approach PNM IRP The Stipulation in Case 3137 identifies jurisdictional load as New Mexico retail load and wholesale firm requirement customers contracted with prior to September 2, These wholesale customers are the City of Gallup and Navopache. A planning reserve margin is necessary to compensate for potential imprecision in the peak demand forecast, such as variations due to weather, and the possibility of a resource contingency (e.g., an outage or failure). The planning reserve margin is calculated as the amount of installed jurisdictional peak resource capacity in excess of projected jurisdictional demand as a percentage of total demand, as shown in Figure 41. FIGURE 41. PLANNING RESERVE MARGIN FORMULA The Stipulation in Case 3137 defines the resource capacity for renewable resources which is available on peak, because some resources have different ratings based on their intermittent characteristics. The IRP uses the net dependable summer capacity coincident with PNM s system peak load. This results in less than the full nameplate output from some resources and significant degrading of capacity from nondispatchable intermittent resources, such as wind and solar resources. 2. Utility Case No UT, the Resource Stipulation, approved by the NMPRC on May 26, 2009 The Resource Stipulation requires that beginning with the 2011 IRP, PNM will use a planning reserve margin of 13% of peak demand, but not less than 250 MW of planning reserve capacity. Additionally, the City of Aztec is added as a wholesale customer that PNM must plan for as part of its jurisdictional load. PNM calculates both firm and nonfirm reserve margins. The firm reserve margin calculation uses the peak load demand forecast, including estimated effect of existing EE measures, but excludes projected reductions from new EE programs. The resources included in the firm reserve margin calculation are those that are dispatchable. The nonfirm reserve margin calculation adds the projected effects of new demand side measures, such as EE, existing and projected residential solar photovoltaic (PV) systems, and other DG. Thus, intermittent resources are included in the nonfirm reserve margin calculation. SYSTEM RELIABILITY STANDARDS PNM regards system reliability as an overarching consideration for selecting the most costeffective resource portfolio. The following paragraphs review the system reliability standards required of PNM. As previously discussed, PNM s planning reserve margin target is set by the NMPRC at 13%. In addition, PNM s planning reserve must consider operating requirements, loss of the largest loadside resource, including transmission, and forecast uncertainty due to normal forecast fluctuations and extreme weather. The combination of these factors is an approximate minimum reserve of 250 MW. 26

39 Integrated Resource Planning Approach PNM IRP PNM follows WECC and NERC Criteria for: Control Performance Standards Disturbance Control Standards Transmission Planning Standards Power Supply Assessment WECC AND NERC CRITERIA As a member of Western Electricity Coordinating Council (WECC) and North American Electric Reliability Council (NERC), PNM complies with reliability criteria to ensure that its electric systems are safely and reliably operated. PNM must comply with NERC operating standards, which in part, might dictate the use of certain resources to meet the requirements. These include Control Performance Standards 1 (CPS), which measure a control area operator s ability to control system frequency and balance its load and generation at all times. They also include Disturbance Control Standards 2, which measure the control area s ability to respond to generator or load loss. PNM must also comply with NERC standards that relate to transmission planning and operations. These include Transmission Planning Standards 3 (TPL), which measure the sufficiency of the transmission system to meet present and future needs. TPL standards state that, The interconnected power system shall be operated at all times so that general system instability, uncontrolled separation, cascading outages or voltage collapse will not occur as a result of any single contingency or multiple contingencies of sufficiently high likelihood. POWER SUPPLY ASSESSMENT (PSA) NERC requires WECC to annually evaluate future resource adequacy of the western region based upon annual resource plans submitted by member utilities. The PSA is a regional and subregional determination of resource adequacy, rather than an individual utility evaluation of resource adequacy. The purpose, as stated in the Reliability Assessment Guide book 4, is to project whether enough physical resources exist, at any price, to meet load and possible reserves while considering the transmission transfer capabilities of major paths. PNM, balancing area coordinator (BAC) in New Mexico, participates in the PSA study process and collects historical and future load and resource information from load serving entities (LSEs) within New Mexico. This assessment is important because, if the PSA were to identify a resource adequacy issue in the region or subregion where PNM operates, PNM would be obligated to participate in finding a solution to the resource deficiency. 1 See BAL0010_1a.pdf 2 See BAL0021.pdf and BAL002WECC1.pdf 3 See TPL through TPL0040 standards 4 See Reliability Assessment Guidebook v1.2 27

40 Integrated Resource Planning Approach PNM IRP RESERVE SHARING AGREEMENTS In addition to meeting planning criteria, PNM also ensures that its resource portfolio meets operating conditions. From time to time, the operation PNM maximizes the cost benefits of PNM s system may warrant additional generation and reliability improvements that or the use of certain types of reserves to maintain result from coordinating with other adequate stability. utilities. PNM recognizes the economic and reliability benefits of participating in the Southwest Reserve Sharing Group (SRSG) for operating reserves. The operating reserve margin is measured in real time to maintain proper system frequency and balancing of loads to resources in the southwestern U.S. Southwestern U.S. utilities specify their load requirements and their resource availability on an hourly basis to SRSG. The SRSG administration examines the risk or the likelihood of a system disturbance to determine the collective reserves it needs to hold. SRSG then notifies each utility of the operational reserves they should hold, in addition to the resources each utility uses to serve its customers. Total SRSG operating reserves can be split between spinning reserves (coming from units that are operating at less than their full output) and nonspinning reserves (resources that are not operating but can be brought online within ten minutes). PNM s participation in SRSG is critical to minimizing the expense of PNM s reliability obligations. If PNM had to provide all of the necessary reserves itself, the requirement would equal its single largest operating unit, which is the utility s largest risk. PNM s SRSG allocation is partly determined by the size of the units that are included in PNM s operating portfolio. Currently, PNM s single largest potential risk is SJGS Unit 4 (240 megawatts) if it is operating or Afton (230 megawatts) if Afton is operating and SJGS Unit 4 is not. Looking forward, and for purposes of this IRP, PNM must determine how new resource additions might change the level of reserves required for SRSG purposes or otherwise result in additional costs to meet reliability standards. Generally, PNM s planning criterion is to limit the size of new generation to that of the current largest unit. OTHER SYSTEM RELIABILITY STANDARDS Although states have had the primary role in setting reserve margin requirements, federal agencies (Federal Energy Regulatory Commission (FERC) and NERC) have taken increased responsibility. Numerous states (including Maryland, New Jersey, Pennsylvania, Ohio, Indiana, Wyoming, Delaware, and the District of Columbia, in addition to portions of Michigan, Wisconsin, Illinois, Kentucky, Tennessee, and Virginia) have received approval from FERC to utilize one day in ten years resource planning criteria. Implementation of this criterion would result in planning for sufficient resources so that no more than 48 loss of load hours would be experienced in a 20 year planning period. This is a more stringent criterion than PNM s existing reserve planning criteria, but could be a consideration for future planning. 28

41 Integrated Resource Planning Approach PNM IRP The optimal resource portfolio must provide adequate energy generation to meet both peak demand and total energy needed. ANALYTICAL TECHNIQUES Based on the aforementioned rules and requirements, PNM s charge in the IRP is to determine the most costeffective resource portfolio. The most costeffective portfolio is the combination of generation resources and demandside programs that will produce the least cost to PNM customers, while providing them with an adequate and reliable supply of electricity over a wide range of potential circumstances. This least cost criterion is subject to a number of constraints that are factored into the analysis. The IRP Working Group employed a multidimensional analysis approach that incorporates scenario identification, and both stochastic and qualitative risk analyses. The selection of the most costeffective resource portfolio involved the use of each of the analytical techniques that are described in the following paragraphs. SCENARIO ANALYSIS The scenario analysis utilizes a technique called constrained optimization to identify a wide array of resource portfolios and evaluate portfolio impacts throughout the twentyyear planning period. Constrained optimization seeks to provide a solution (i.e. portfolio) where costs are minimized, while taking into account how much each limitation (i.e. constraint) is weighted. For this IRP, a portfolio represents a set of generation resources to meet the growing load. Each scenario represents a combination of various input factor assumptions or projections. These include varying the load forecast (i.e., low, mid and high) and production cost factors, such as the price of natural gas fuel (mid and high) for power plants, the projected cost of constructing new resources, and costs of compliance with potential future CO 2 regulations (i.e., $0, $8, $20 and $40/metric ton of CO 2 equivalent emissions). For example, one scenario may have a mid load forecast for peak demand, mid forecast for natural gas and a CO 2 cost of $20/metric ton. In contrast, another scenario might have a mid load forecast for peak demand, high forecast for natural gas and a CO 2 cost of $35/metric ton. A more complete listing of input factors is contained in the Scenario Analysis section. Each scenario produces a variety of portfolios which are then ranked to yield the least cost portfolio in terms of NPV for the mix of input assumptions. The least cost solution to the analysis modeling represents the optimal mix of building or acquiring new resources and the optimal dispatch of those resources over the 20year planning period. Note that dispatch refers to the operational decisions to run selected power plants at any given time, while the build decision relates to the type and size of new resource that should be acquired as customer demand grows. Collectively, the scenario analysis addresses the uncertainty regarding potential changes in important input variables, including levels of natural gas prices, economic growth, environmental costs, and regulatory restrictions. STOCHASTIC ANALYSIS Stochastic analysis identifies the financial cost risks of portfolios over a broad range of potential conditions for certain key variables. These include fluctuations in customer demand, variability of natural gas prices, future CO 2 costs, and system market prices for electricity. The stochastic analysis 29

42 Integrated Resource Planning Approach PNM IRP measures the robustness of specific portfolios over the range of possible conditions. Each of the least cost portfolios that were the result of the scenario optimization are tested over the same potential conditions to define variability in portfolio cost due to uncertainties. This analysis broadens the discrete modeling done in the scenario analysis to the full range of expected values of uncertain variables. The most advantageous portfolio is one that minimizes both cost and the variability due to uncertainty. Additional details are included in Section 12, Quantitative Analysis. QUALITATIVE ANALYSIS Qualitative risk analysis captures risks that are not readily quantifiable, yet should be considered in the development of the most costeffective resource portfolio. PNM has considered risks in the areas of operation, economic, financial, behavioral, technology and regulations, which are detailed in Section 2, The Most CostEffective Resource Portfolio. The optimal portfolio reduces risk and has known mitigation strategies. LifeCycle Costs The analysis aims to reflect all costs to PNM s customers associated with PNM s electricity supply. The time value of money is recognized by discounting future cash flow. In addition, some effects occur after the 20year planning period and adjustments are made to account for those. These adjustments include recognition of not fully depreciated asset values, levelized cost streams and others. Also, the analysis identifies costs of power production that NMPRC Rule G(1 and 2) requires the utility to discuss risk and uncertainty and the lifecycle cost of the portfolio resource. do not appear in PNM s direct costs. For example, there is currently no cost for GHG emissions from power plants. The analysis looks at a range of costs for those emissions as discussed in the section on climate change. Costs not affecting PNM s customers are generally excluded, for example, state and federal government subsidies for different generation types that do not lower the utilities cost for those technologies. A detailed discussion of lifecycle costs and externalities is presented in Appendix H. 30

43 Status Report on 2008 IRP PNM IRP The IRP Rule I(1) requires a status report on the specific actions contained in the previous action plan. 5. STATUS REPORT ON 2008 IRP strategically delayed previously planned additional resources. Since the 2008 IRP was filed with the NMPRC, PNM experienced the economic consequences of a nationwide recession. This recession caused many businesses to fail, increased unemployment, and forced many PNM customers to become acutely aware of their energy demand. As a result, PNM s forecasted load did not increase at projected rates, so PNM Natural gas prices also decreased over the planned period as a result of the recession and the development of shale gas supplies. 31

44 Status Report on 2008 IRP PNM IRP TABLE 51. STATUS OF 2008 IRP ACTION PLAN Implementation Strategy Promote DemandSide Resources Expand Renewable Distributed Generation Add More Renewable Resources Add Natural Gas Fired Resources Action Pursue maximum levels of energy efficiency. File for inclusion of a larger than 10kW customersited distributed PV program in the 2009 renewable procurement plan. Issue Renewable Energy from a Parbolic Trough Solar Thermal Resource RFP to expand solar resources and seek NMPRC approval. Issue Renewable Energy Resources RFP for all renewables to select the leastcost renewable resource option. Upon selection of renewable resource options, seek NMPRC approval through a supplemental filing in the 2009 renewable procurement and/or the 2010 renewable procurement plan. Pursue NMPRC approval for the addition of the existing Luna and Lordsburg natural gas facilities in PNM s rate base portfolio. Status NMPRC approved EE programs in Case No UT in May 2009 and Case No UT in June Current programs have successfully increased savings of annual energy and peak demand and are expected to grow thru Measurement and verification of DR programs is filed every year on April 1, in accordance with the EE Rule and EUEA. This was filed on July 1, The NMPRC approved this program at $.15/KWh. In 2010, the NMPRC established a new solar REC incentive program (SIP) for small and large PV facilities program participants that provides for tiered incentive pricing And replaces the small and large PV REC purchase programs. The RFP was issued. The project was not feasible. In 2010 the NMPRC authorized the installation of 22 MW of solar PV at five sites. Besides the authorized solar installations, none of the proposals met the RCT. In 2010 the NMPRC authorized the installation of 22 MW of solar PV at five sites. The CCN application was filed September 12, 2008 and was approved on May 28, 2009 (Case No UT). Transmission Considerations Monitor and Evaluate Conduct a sitespecific study to optimally select the specific site and size for the next natural gas addition, then pursue NMPRC approval of the best natural gas resource addition. Secure 60 megawatts firm transmission from Luna to Springerville. Restructure EPE transmission service agreement. Study the use of various storage technologies to determine long term viability for use on PNM s system to help offset the regulation requirements associated with intermittent resources such as wind and solar and to maximize utilization of existing base Load did not increase at the expected rate, so a natural gas addition was unnecessary during this time period. Transmission service was secured from EPE beginning on 1/1/2010. Still under evaluation. Currently studying a variety of storage technologies. Construction of a 500 kw solar project with battery storage was approved by the NMPRC in August 2010 and is currently underway. 32

45 Status Report on 2008 IRP PNM IRP Implementation Strategy Action load facilities. Continue to monitor opportunities to purchase the remaining Palo Verde Units 1 and 2 leases. Make appropriate regulatory filings as these become available at reasonable prices. Status Continuing to investigate this option. 33

46 Public Advisory Process PNM IRP PUBLIC ADVISORY (PA) PROCESS OVERVIEW PNM began preparing for the PA process in the spring of 2010 by placing newspaper advertisements and sending notifications in customer bills to create public awareness. On June 8, 2010, PNM began the process by notifying the NMPRC in accordance with the IRP Rule. Facilitated by a third party, the process was designed to provide transparency to PNM s resource planning by affording the opportunity for community meetings and inviting public participation. Through a series of meetings held at least once a month from September 2010 through June 2011, working group members representing the general public and various interest groups, along with PNM employees, actively engaged in the planning process by providing comments, sharing concerns, and proposing alternative scenarios, assumptions, and methodologies for consideration in this IRP. THIRDPARTY FACILITATION PNM contracted with New Mexico First to act as a process advisor and facilitator for the public meetings. New Mexico First is a nonprofit, nonpartisan public policy organization that has considerable experience in organizing and facilitating public forums and deliberations. COMMUNITY MEETING PARTICIPATION AND VALUES INPUT Per the IRP Rule, PNM used a bill insert and newspaper notice to invite customers to community meetings in eleven communities throughout the PNM service area from June 2010 through August PNM officers and employees from the PNM Integrated Resources Planning department traveled to Alamogordo, Albuquerque, Clayton, Deming, Farmington, Los Lunas, Las Vegas, Rio Rancho, Ruidoso, Santa Fe and Silver City to inform interested parties of the IRP process and encourage their participation in the future working group meetings. During the community meetings, attendees learned about PNM s 2008 resource plan and the requirement to update the plan every three years. PNM executives outlined the IRPPA process and encouraged attendees to be part of the working group. Utilizing the PNM website at irp_electric.htm participants were able to view related documents such as pertinent research reports, meeting presentation materials, and meeting minutes, and to provide comments. At each of the community meetings, participants learned about current and future generation resources and PNM s perspective on the tradeoffs between different resource selections. Participants were then invited to provide their opinions on a number of issues facing utilities when considering new resource selection. The issues were: Maintaining high reliable energy access to customers Minimizing customer rates for energy Using the least amount of water possible Minimizing greenhouse gases Growing New Mexico s energy economy through new jobs and manufacturing In some communities, the discussion was informal and individuals stated why they felt some issues deserved more consideration than others; in other communities, a more formal process of prioritizing issues was conducted. Table 61 reflects participation at the community meetings as well as the community values rankings where a 1 represented the top priority issue and a 5 was 34

47 Public Advisory Process PNM IRP the lowest priority. However, all groups recognized that the issues were interconnected. Although the participants presented diverse opinions on the issues, there were a number of themes that recurred throughout the discussions. These included: Reliability is important to maintain a healthy economy, i.e., attract businesses that will create jobs. Reliability is also important for basic needs, including access to water. Rates need to be kept low because New Mexico is a poor state. Rates need to be low especially for businesses because they will create jobs which will have a trickledown effect. Rate increases are acceptable if they serve to maintain or improve the reliability of the system. Water is vital for life, and New Mexicans should conserve it. Greenhouse gases and climate change was the most polarizing issue; attendees often felt that this issue was either extremely important or completely irrelevant. Creating jobs is not the responsibility of the utility. It is more important to have good service that attracts a wide variety of businesses that will create jobs. TABLE 61. COMMUNITY MEETING PARTICIPATION AND VALUES Participants Reliability Rates Water GHG Jobs Rio Rancho public Los Lunas public Albuquerque employee Albuquerque employee Albuquerque employee Albuquerque employee Albuquerque public Santa Fe employee Santa Fe public 42 Clayton public 13 Las Vegas employee 3 Las Vegas public Ruidoso employee Ruidoso public Alamogordo employee Alamogordo public Silver City employee 26 Silver City public 28 Deming employee 1 Deming public Farmington employee Farmington employee Farmington employee 7 Farmington employee Total public Total employee Total all Overall, both the public participants and the PNM employees expressed very comparable opinions surrounding these issues with reliability of the system and minimizing water use being ranked as the most important issues and greenhouse gases being the least important. 35

48 Public Advisory Process PNM IRP INCLUSION PNM contacted a variety of organizations in the public and private sector to ensure broad representation in the IRP process. The organizations included environmental and energy advocacy groups, public interest groups, industry and labor, and customer groups. PNM reached these organizations through personal contact and direct . Several subsequent s were sent in advance of meetings to encourage broadbased community engagement. In addition, PNM promoted meetings via Twitter and Facebook. PNM also developed a dedicated web site for posting meeting notices and schedules to continuously invite the public to participate in the IRP process. Date TABLE 62. TOPICS OF IRP WORKING GROUP MEETINGS Topics Overview of planning process, participant introductions, PRC expectations, regulatory requirements, utility bill factors and rate design, getting organized as a working group Energy efficiency and transmission issues Optional tour of JACO Environment, Inc. recycling plant, EE priorities, resource site issues, load forecasting, smart grid and electric vehicle issues Scenario building and modeling methodology, sensitivities for load forecasting, electric vehicle adoption and EE, emerging energy resource technologies, water issues Sensitivities for fuel costs, emissions/performance regulations and sensitivities, capital costs for new generating technologies (including siting, transmission, and loss credits) Question and answer session with PNM subject matter experts on topics reviewed todate (per IRP Working Group request), finalize modeling sensitivities, plant joint ownership implications, life cycle costs Status of shortterm compliance with EIRP , financial investment and timeframes, finalize scenario grid Optional tour of Reeves Generating Station and PNM Solar Array, risk analysis methodology, quantitative and qualitative measures, Quantitative and qualitative measures, reliability, scenario modeling review Scenario modeling, Stochastic risk, and Report review Modeling updates, Qualitative risk results, Report review Report review 36

49 Public Advisory Process PNM IRP WORKING GROUP MEETINGS The purpose of the working group meetings was to provide an open and transparent process to inform and educate members regarding resource planning, as well as collect member comments which could be incorporated into this IRP. The IRP Working Group meetings followed an agenda of topics proposed by PNM, as well as agenda items requested by IRP Working Group members. Meeting materials were posted on PNM s web site the week prior to the meetings. PNM presented and discussed all of the data and analytic techniques used in this IRP. PNM provided hardcopy handouts of related reports and analyses to all meeting participants. PNM encouraged an open discussion of the topics and related issues which was facilitated by New Mexico First. After the meetings participants were asked to complete a postsession evaluation. This provided an opportunity for suggestions to improve session planning, logistics, and content. Summaries of each meeting, including the IRP Working Group input, were posted on PNM s web site. Table 62 lists the IRP Working Group meetings, including dates, and topics discussed. TABLE 63. PNM STAKEHOLDERS PARTICIPATING IN THE IRP PUBLIC ADVISORY PROCESS Stakeholder Area Environmental Advocates Government Resource Developers Concerned Citizens Regulatory Participating Members Belin & Seligman, Coalition for Clean Affordable Energy (CCAE), Natural Resources Defense Council (NRDC), New Energy Economy, Sierra Club, Western Environmental Law Center, Western Resource Advocates State of New Mexico, NM Energy, Minerals and Natural Resources Department Carlisle Energy Services, Clean Switch, Galvin Electricity Initiative, GE, Glen Consulting, Kiewitt, KDR Engineering, REIA Red Mountain Energy Partners, David Allen, Jan Bray, Barbara Chatterjee, John Clema, Donna Crawford, James Crawford, Dave Gilmer, Dana Jones, Gabrielle Kotoski, Gabe Mayr, Martin Newman, Jerry Pekarek, Michelle Henrie, Scott Moye, Geri Rhodes, Alexa Schirtzinger, Kelly Sims, Pat Socci, David Thompson, Bud Wildin, PNM Employees NMPRC staff Other Advocacy Groups AARP, Citizens Alliance for Responsible Energy, Rio Rancho Schools, NM Design Center, Albuquerque Public Schools Media Observers Santa Fe Reporter, New Mexico News Service Indiana Utility Regulatory Commission, New Mexico State University (NMSU), Ventyx 37

50 Public Advisory Process PNM IRP WORKING GROUP COMPOSITION An average of 22 members of the public attended each working group meeting. An average of nine members of the public participated in the meetings through the webinar. Table 63 identifies the stakeholders who attended at least two meetings during the IRP process. PARTICIPANT IMPACT ON THE PLANNING PROCESS PNM worked with working group members and considered their concerns and positions. Their input included assumptions and sensitivities relating to the load forecast, EE, resource costs, fuel prices, CO 2 emissions, permanent load shifting including use of thermal energy storage, and planning constraints, and was incorporated into PNM s analyses, as shown in Table 64. TABLE IRP COLLABORATIVE OUTCOMES Topic System Load Demandside Management Supplyside Resources Scenario Development Stochastic Risk Qualitative Risk Outcomes Broader load forecast levels and the inclusion of changes for electric vehicles. Increased free rider EE, including building code changes. Demandside resources to include a level of EE programs higher than necessary to meet EUEA requirement and including expanded customersited renewable resources with thermal and electrical storage. Supplyside resource costs to include the following two modifiers: Performing sensitivity to higher costs, if a coal plant with carbon capture and sequestration was chosen. Lowering the costs of solar technologies in 2015 and beyond to reflect some industry projections based on maturing technology and increased deployment. Expanded scenarios to meet some stakeholder concerns: No regulatory or legislative change A water shortage situation due to drought. Addition of a $100 per metric ton CO2 cost (in 2017), including escalation. Incorporation of resource restrictions including exploring the retirement of coal units at Four Corners and San Juan. Modeled risk sensitivities to include: Expanded gas price curves. Use of PVNGS hub pricing for market sales and purchases. Use of tiered CO2 prices. Presentation of three portfolios to illustrate qualitative risks: EE with all natural gas peakers (scenarios 1, 2, 16) Renewable compliance, EE, and natural gas peakers (scenarios 6 and 16) Retire coal, high EE, some renewable, natural gas combined cycle for coal replacement, natural gas peakers (scenarios 14, 24) 38

51 Reviewing Existing System Resources PNM IRP REVIEWING EXISTING SYSTEM RESOURCES Reference IRP Rule, section F(3) for existing rates and tariff C (110) for existing generation resources and section C (11) for existing transmission resources. OVERVIEW This section describes PNM s existing owned and purchased generating resources, energy efficiency resources also describes the transmission system used to bring the resources to PNM customers. Resources and their transmission paths, where applicable, are presented in the order of: (1) existing EE resources, (2) renewable resources, and (3) supplyside resources. PNM delivers most resources to customers through the northern New Mexico (NNM) transmission system (WECC Path 48) or through the southern New Mexico (SNM) transmission system (WECC Path 47). ENERGY EFFICIENCY RESOURCES This section addresses the information requested in C(9) of the IRP Rule. subsection. PNM includes NMPRCapproved demandside programs in its existing portfolio. Currently, PNM includes three types of demandside resources: EE, DR, and customersited, renewable Distributed Generation (DG). PNM s customersited DG resources are discussed in the Existing Renewable Resources ENERGY EFFICIENCY PROGRAMS PNM offered the first EE programs to residential and commercial customers in October 2007, with the approval of NMPRC Case No UT. The NMPRC approved the existing EE programs included in this IRP in PNM designs EE and Demand Response programs to reduce overall energy consumption and peak demand. PNM files an EE program report on April 1 st of every year. The report measures and verifies program results from prior years. Case No UT in May The programs consist of a variety of incentives to encourage customers to install energyefficient options, which include: (1) instant rebates for the purchase of compact fluorescent light bulbs, (2) rebates for recycling older refrigerators, (3) homebuilder incentives for building ENERGY STAR homes, (4) rebates to small and large commercial customers for lighting, (5) heating, ventilating, air conditioning (HVAC) and other efficiency improvements tailored to the customers business, and (6) incentives that specifically target lowerincome customers. Programs designed by PNM must be costeffective, as measured by the total resource cost (TRC) ratio, which is the ratio of program benefits to program costs. 39

52 Reviewing Existing System Resources PNM IRP The ratio must be greater than one. Program benefits include the value of the lifetime avoided energy and capacity which include: Avoided cost of energy production, such as fuel costs Avoided or delayed cost of capacity additions Avoided cost of future environmental costs (CO 2) The costs include all program and participant related costs (i.e., program administration, marketing, rebates, and participant incremental costs). The approved EE programs run until modified or canceled by the NMPRC. PNM forecasts the demand and energy savings for these programs using the results from the annual independent third party measurement and verification process, and estimates of participation in current and future programs required to meet the EUEA savings requirements. Approved EE programs will increase savings of annual energy and peak demand from 2011 to After 2023, the growth in annual energy and peak demand savings is expected to decline through 2030, due to the market transforming and EE technologies maturing. In the forecast, PNM only counts savings from the EE programs through their estimated lifetime. The IRP assumes that as the lifetime of programs expires, they will be replaced with new programs so that demand savings and energy savings will continue throughout the plan period. A detailed discussion of energy efficiency goals is provided in Section 10, Reviewing Future Resource Options. LOAD MANAGEMENT Demand Response programs are voluntary, incentivebased peak shaving programs that reduce summer system peaks, but do not necessarily reduce overall energy use. Both programs are contracted through 2017, and the IRP assumes costeffective program continuation through Program results are detailed in the annual program reports to the NMPRC, published in April every year. The existing demandside resources also include two voluntary DR programs approved by the NMPRC in Case No UT. The Power Saver program is for residential and small commercial customers with less than 150 kilowatt (kw) load, and the Peak Saver program is for commercial customers with 150 kw of load or greater. PNM selected each of the DR program contractors through a competitive bid process. PNM designed the Power Saver program for customers with refrigerated air conditioning. PNM hired a thirdparty contractor, Comverge, Inc. to manage this program. The program is governed by a 10year professional services contract that was effective January 31, 2007 and expires September 30, Comverge installs a device on customers refrigerated air conditioners that is used to remotely control when the units cycle. During peak periods, PNM can reduce peak demand by remotely cycling the air conditioners, which reduces the collective electricity demand from these devices. The program occurs in the summer months of June through September and can be dispatched within ten minutes as a peakshaving resource for up to 100 hours each year. The IRP assumes the program s costeffective 40

53 Reviewing Existing System Resources PNM IRP continuation over the 20year study period; however, this will require substantiation in future EE proceedings. The 2010 cost per kw was $104, reflecting the cost of the contract with Comverge, Inc. as calculated at the customer s meter. The PNM Peak Saver program is for larger commercial and industrial customers with peak loads of 150 kw or greater per month. PNM contracted with EnerNOC to manage this program until This program targets nonessential electric loads that can be reduced during periods of peak system demand. EnerNOC installs demandcontrolling equipment that runs during the summer peak period of June through September, and can be dispatched with ten minutes as a peakshaving resource for up to 100 hours each year. The IRP also assumes this program extends through the 20year study horizon. The 2010 cost per kw was $98, reflecting the cost of the contract with EnerNOC as calculated at the customer s meter. The peak demand savings from the Power Saver program is determined by use of a statistical sampling method that derives a kw savings factor per installed unit. The Peak Saver program provides actual meter data to determine the demand savings available to PNM. Measurement and verification of the DR programs is filed every year on April 1, in accordance with the EE Rule and the EUEA. Table 41 shows the verified capacity reductions for TABLE 71. DEMAND RESPONSE PROGRAM COSTS 2010 MW Capacity $/kw* Program Start Date Programs 2010 Participants Available Hours PNM Power Saver (< 150kW) 32, $ PNM Peak Saver (>150 kw) $ Demand Response Totals 32, $ *The capacity and capacity costs are calculated at the customer meter and therefore include transmission losses. TABLE 72. ENERGY EFFICIENCY AND DEMAND RESPONSE PROGRAM RESULTS EE and DR Results Oct 2007Dec TRC Test Ratio Total annual savings at the customer meter 35.2GWh 39.9 GWh 58.8 GWh Peak demand reduction 7.5 MW 6.3 MW 9.9 MW DR program capacity 47 MW 53 MW 67 MW Total program expenses $8 million $12 million $16.6 million Average cost per MWh $13.20 $17.60 $

54 Reviewing Existing System Resources PNM IRP TABLE 73. ENERGY EFFICIENCY PROGRAM RESULTS THROUGH DECEMBER Program Participation Units Totals Residential Lighting Bulb 1,005, , ,445 2,940,894 Refrigerator Recycling Refrigerator 8,537 7,001 8,239 23,777 Energy Star Homes Home ,432 Low Income CFLs and Refrigerators** Bulbs & Refrigerators 2,158 10,462 12,620 Easy Savings** Kit 8,681 7,251 15,932 CFL Exchange Bulb 80,920 44,086 17, ,170 Energy Saver Kit* Kit Advanced Evaporative Cooling Cooler Commercial Lighting* Participant 27,799 59,699 87,498 Commercial Comprehensive** Participant Commercial Self Direct Participant Demand Response Participant 16,731 23,189 32,247 72,167 Program MWh Annual Savings Totals Residential Lighting 24,142 69% 15,663 39% 20,583 35% 60,388 Refrigerator Recycling 5,745 16% 4,614 12% 7,312 12% 17,671 Energy Star Homes 158 0% 839 2% 831 1% 1,827 Low Income CFLs and Refrigerators** 312 1% 1,245 2% 1,558 Easy Savings** 3,377 8% 2,390 4% 5,767 CFL Exchange 1,942 6% 877 2% 342 1% 3,161 Energy Saver Kit* 130 0% 130 Advanced Evaporative Cooling 17 0% 1 0% 0% 18 Commercial Lighting* 2,043 6% 6,594 17% 8,637 Commercial Comprehensive** 6,707 17% 26,104 44% 32,811 Commercial Self Direct 1,034 3% 243 1% 1,277 Demand Response 665 2% 0% 665 Totals 35,211 39,892 58, ,911 Program MWh Lifetime Savings Totals Residential Lighting 193,135 64% 125,302 36% 144,084 28% 462,521 Refrigerator Recycling 57,454 19% 46,137 13% 35,720 7% 139,310 Energy Star Homes 4,733 2% 25,164 7% 24,918 3% 54,815 Low Income CFLs and Refrigerators** 4,622 1% 17,279 3% 21,902 Easy Savings** 27,015 8% 18,052 3% 45,067 CFL Exchange 15,537 5% 7,018 2% 2,391 0% 24,946 Energy Saver Kit* 912 0% 912 Advanced Evaporative Cooling 269 0% 21 0% 0% 289 Commercial Lighting* 14,301 5% 46,158 13% 60,459 Commercial Comprehensive** 67,647 19% 286,541 55% 354,187 Commercial Self Direct 15,515 5% 2,430 1% 17,945 Demand Response 665 0% 0% 665 Totals 301, , ,984 1,183,018 42

55 Reviewing Existing System Resources PNM IRP TABLE 73 (CONTINUED). ENERGY EFFICIENCY PROGRAM RESULTS THROUGH DECEMBER Program kw Savings Totals Residential Lighting 5,533 10% 1,836 3% 2,783 4% 10,152 Refrigerator Recycling 939 2% 798 1% 1,179 1% 2,916 Energy Star Homes 93 0% 494 1% 596 1% 1,183 Low Income CFLs and Refrigerators** 39 0% 145 0% 184 Easy Savings** 295 0% 220 0% 515 CFL Exchange 445 1% 101 0% 39 0% 585 Energy Saver Kit* 22 0% 22 Advanced Evaporative Cooling 14 0% 1 0% 0% 18 Commercial Lighting* 322 1% 1,136 2% 1,458 Commercial Comprehensive** 1,478 2% 4,902 6% 6,380 Commercial Self Direct 129 0% 125 0% 254 Demand Response 47,365 86% 53,410 89% 67,032 88% 67,032 Totals 54,862 59,714 76,896 92,807 *Discontinued in 2009 **New programs starting July of 2009 ENERGY EFFICIENCY AND DEMAND RESPONSE RESULTS In accordance with the EE Rule and the EUEA, PNM filed the first annual PNM EE Program Report with the NMPRC on April 1, 2009, and filed subsequent reports on April 1, 2010 and April 1, The reports include detailed measurement and verification findings that quantify customer adoption rates and energy savings. The first annual report covered the period October 2007 to December 2008 and indicated that the programs were very costeffective and exceeded projected target savings. Participation rates also exceeded expectations, so program costs were slightly higher than anticipated. Table 72 summarizes the program results from 2008 through Table 73 lists the programs, the participation levels, and the annualized energy and demand savings reported to the NMPRC through December As of the date of this IRP, the programs have achieved 134 GWh savings, and PNM is on target to meet or exceed the 2014 cumulative goal of 411 GWh (5% of 2005 retail sales), and the 2020 cumulative goal of 822 GWh (10% of 2005 retail sales). Year to year results vary based on date of implementation, customer participation, verified savings and marketing efforts. Detailed analyses of each year s results are available in PNM s annual EE and measurement and verification reports at EXISTING RATES AND TARIFFS According to state statute, rate and rate riders refer to every rate, tariff, charge or other compensation for utility service rendered or to be rendered by a utility, as well as any rules, 43

56 Reviewing Existing System Resources PNM IRP regulations, and requirements related to the rate or rate rider. PNM incorporates LM and load shifting concepts into several rates and tariffs. These include the following: Inverted Block Residential Rate Design: Rates per unit of energy increase for residential customers as usage increases (i.e., Rate 1A). This is designed to discourage higher usage by increasing cost. Figure 71 shows an example of current increasing rates for usage. Seasonal Residential Rate Design: Summer rates are higher than winter rates for most customer classes. This rate encourages customers to avoid usage during the summer months when demand on the system is greatest and utility generation costs are highest. By discouraging usage during the peak season, seasonal rates help to delay the need for new resources. Figure 71 also illustrates this rate design. FIGURE 71. INCLINING BLOCK ENERGY RATES Time of Use (TOU) Rates: PNM offers time of use rates for residential, small power, general power, large power, irrigation service, and water and sewage pumping customer classes (Rates 1B, 2B, 3B, 3C 4B, 5B, 10B, 11B, 14B, 15B, 17B and 30B). These rates encourage customers to avoid usage during the time when the cost to serve is highest and allow for greater efficiencies in generation resource utilization. TOU rates are required for all larger customers (greater than 50 KW). The remaining customers can choose TOU rates to lower their cost by shifting usage. Incremental Interruptible Power Rate: Five general power and three large power customers have contracts for service under PNM s Rate Rider 8. In the event of a PNM system emergency, these customers can be called upon to interrupt their incremental 44

57 Reviewing Existing System Resources PNM IRP onpeak billed demand with thirty minutes notice during the onpeak period of 8:00 a.m. until 8:00 p.m., Monday through Friday. Interruptions can extend up to two hours into the daily offpeak period, but have no limit in the total hours of interruption per year. A customer may bypass an interruption request, and will forgo the monthly tariff discount afforded to them, but if the customer fails to interrupt more than two times during any calendar year, it will be permanently removed from the rider. Voluntary EE Program: Residential and business customers (PNM s Power Saver program) and large power customers (PNM s Peak Saver program) can volunteer to have portions of their load curtailed on tenminutes notice from June through September for up to 100 hours per year. This load shifting helps PNM manage peak summer loads, but cannot be fully counted for meeting spinning reserves. The standards which PNM must meet to support system reliability, discussed in Section 3, require a resource to be fully net metered to qualify to meet SRSG spinning reserves. Since it is impractical to net meter thousands of customers under the PNM Power Saver Program, that capacity cannot be counted for SRSG purposes. As a result, only capacity from PNM Peak Saver can be counted towards meeting SRSG nonspinning reserves. PNM designs rates, tariffs and DR and EE programs to offer customers economic incentives to either shift energy use to offpeak periods, thereby increasing the system load factor, or to reduce system demand and energy through demand side management. Improving system load factor results in improved utility asset use and lowers overall system costs. PNM promotes EE programs, EE programs, and energy use incentives through bill inserts, direct mail advertising, radio, television, and print advertising, and community education programs. The PNM website also provides information on these programs. The IRP implicitly considers the ongoing impact of rates on PNM s resource needs through the load forecast, which, being based on customer usage patterns, captures the effects of these rates on usage. Growth in participation in the Power Saver and Peak Saver programs was modeled in the same way as for the existing and projected EE resources. Growth in Rates 24, 31 and 32 is explained in the Existing Renewable Resource Section. PNM also has rates and tariffs that encourage renewable development: Voluntary Renewable Tariff: PNM designed the PNM Sky Blue program, in accordance with Rule 572, for customers who want to demonstrate an additional commitment to the environment, above and beyond the utility s RPS requirement, by purchasing energy from renewable resources. PNM North customers can purchase 100 kilowatt hour (kwh) blocks of electricity based on resources from New Mexico Wind Energy Center (NMWEC), provided the number of blocks does not exceed 90% of a customer s minimum monthly usage over the previous twelve months. Alternatively, customers can subscribe for 90% of their monthly electric consumption. PNM has requested NMPRC approval in Case No UT to transition the voluntary program from an all wind program to a blended renewable resource program using wind and solar resources, so that the program reflects more current renewable generation costs and a more diverse renewable portfolio. This request is pending before the Commission. 45

58 Reviewing Existing System Resources PNM IRP Cogeneration and Small Power Production Rate (Rate 12): This rate, based on PNM s energy costs in the corresponding month of the prior year, is offered to qualifying facilities that provide netexcess renewable generation to PNM. Small Photovoltaic Renewable Energy Certificate Procurement Rates (Rate 24, Rate 31, and Rate 32): These rates incentivize customers to install solar facilities on their premises and help PNM with RPS compliance. Rates 24 and 31 are closed to new participation. EXISTING RENEWABLE RESOURCES CUSTOMERSITED DISTRIBUTED GENERATION (RENEWABLE, DEMANDSIDE RESOURCE, PNM SERVICE TERRITORY) In 2006, the NMPRC approved a customersited, renewable DG program (i.e., small PV program) for small solar PV for systems up to 10 kw in size. Solar PV technology converts solar energy to electricity in a solar cell. The program allowed customers to netmeter and sell to PNM the environmental attribute (i.e. the REC) associated with the energy generated by customers PV systems. Contracts under the Small PV program last for a 12 year period from the inservice date of the facility. RECs purchased under contracts dated prior to January 1, 2010 have a 3:1 REC weighting; i.e. for each kwh generated, three kwh can be counted toward compliance with the RPS. RECs purchased under contracts dated on and after January I, 2010 have a 1:1 weighting. Customers receive a payment of $0.13 per kwh for the RECs acquired by PNM. In 2009, the NMPRC approved a customersited, renewable DG program for solar PV systems larger than 10 KW and up to 1 MW in size (i.e., large PV program). Similar to the small PV program, the large PV program allowed customers to netmeter and offered a REC purchase program for the environmental attribute of the energy generated by the customers PV systems and used by the customer. Contracts to purchase RECs under this program are for a 20 year period at $0.15/KWh. All RECs purchased under the large PV program have a 1:1 weighting. Effective August 31, 2010, the Final Order in Case No UT established a new Solar REC Incentive Program (SIP) and with certain exceptions closed the small and large PV programs to new participants. SIP is similar to the small and large PV programs but has one significant difference. The new program has declining price ratchets in each system size category and sets capacity limits for each category; and the total capacity that can be installed under the SIP is set at a maximum of MWDC. Table 75, taken from the Final Order, shows the solar REC incentive categories. Contract terms for the SIP are the same as in the prior programs. Table 74 shows growth in the DG REC purchase programs from 2006 through

59 Reviewing Existing System Resources PNM IRP TABLE 74. CUSTOMERSITED RENEWABLE DG PROGRAM GROWTH Year Number of Participants Cumulative KW DC Installed Annual Energy KWh Annual RECs KWh 2006 Small PV only , , Small PV only ,920 1,592, Small PV only ,175,143 3,525, Small and Large PV 340 2,124 4,298,722 7,132, All Programs 625 6,145 8,934,000 13,611,196* Customer growth in DG programs (see Table 74) has substantially increased both in the number of participants and size of systems that are being installed. This is due to the tax incentives provided by the American Recovery and Reinvestment Act and the current downward trend in the cost of photovoltaic cells, as well as the netmetering and REC payment incentives offered by PNM. To project the participation rate for SIP, PNM assumed that 90% of the program applicants would actually construct the proposed facility. This forecast, along with the amounts already placed in service by yearend 2010, is found in Table 75. By 2015, PNM expects that the NMPRC capacity limit will be reached. The capacity amounts listed in the table are reduced by 0.5% per year beginning in 2016, to account for degradation of PV panels. The forecast (MW ac installed), customer peak load reduction and annual energy production is shown in Table 76. Since the renewable DG installations are customer owned and not utility owned, they are the responsibility of the owner. For IRP purposes PNM has assumed that these installations will be maintained by the customer since they are incentivized to do so. Also for IRP purposes, PNM assumed that the DG installations will continue to operate to offset system load for the entire planning period, regardless of when particular contracts may expire. The combination of PNM s DG programs already exceeds the 1.5% renewable DG diversity compliance requirement in the RPS rule. PNM received 13,611,196 KWh of RECs in 2010 which fulfills about 2% of the RPS. TABLE 76. CONTRIBUTION TO SUMMERTIME PEAK Capacity (MW ac ) Installed At peak Annual MWh Energy 2 42,871 58,022 65,968 72,179 78,046 77,655 77,267 76,881 76,496 RECS 3 46,370 61,521 69,467 75,678 81,545 81,137 80,731 80,328 79, Capacity (MW ac ) Installed At peak Annual MWh Energy 2 75,733 75,355 74,978 74,603 74,230 73,859 73,489 73,122 72,756 RECS 3 75,733 75,355 74,978 74,603 74,230 73,859 73,489 73,122 72,756 1Values include degradation factor of 0.5% and have been adjusted to account for distribution losses. 2Annual Energy based upon 2,339 sunhours per year. 3Annual RECs include 3x REC multipliers for customers grandfathered under the Small PV program (prior to 2010). 47

60 Reviewing Existing System Resources PNM IRP Program Category TABLE 75. SOLAR REC INCENTIVE PROGRAM CATEGORIES AND REC RATES Step Size in MW DC Estimated Number of Systems* Cumulative MW DC Incentive REC Rates per kwh Estimated Annual kwh* Step Cost* Average Size Small PV 0 to 10 kw $ ,024,920 $ 122, $ ,024,920 $ 112, $ ,024,920 $ 102, $ ,024,920 $ 92, $ ,024,920 $ 81, $ ,024,920 $ 71, $ ,024,920 $ 61,495 > 10 kw to 100 kw $ ,024,920 $ 143, $ ,024,920 $ 133, $ ,024,920 $ 122, $ ,024,920 $ 112, $ ,024,920 $ 102, $ ,024,920 $ 92, $ ,024,920 $ 81, $ ,024,920 $ 71, $ ,024,920 $ 61,495 >100 to 250 kw $ ,275,456 $ 165, $ ,275,456 $ 153, $ ,275,456 $ 140, $ ,275,456 $ 127, $ ,275,456 $ 114, $ ,275,456 $ 102, $ ,275,456 $ 89, $ ,275,456 $ 76,527 >250 kw to 1 MW $ ,847,000 $ 341, $ ,847,000 $ 284, $ ,847,000 $ 227, $ ,847,000 $ 170,820 Large 1 MW $ ,832,800 $ 751, $ ,832,800 $ 614, $ ,416,400 $ 239, $ ,416,400 $ 170,820 48

61 Reviewing Existing System Resources PNM IRP EXISTING SUPPLYSIDE RESOURCES PNM s existing supplyside portfolio consists of resources that are either owned by PNM or purchased by PNM through a Power Purchase Agreement (PPA). This section provides an overview of all resources including transmission. EXISTING SUPPLYSIDE RESOURCES: Figure 72 shows the amount of existing owned and contracted supplyside resources by year for the plan period. A reduction occurs in 2018 and 2023 that reflects expired PVNGS leases. Additionally, several other resources have contracts that are due to expire during the 20year plan (i.e., Delta, NMWEC, and Valencia). Since these contracts expire late in the planning timeframe, PNM has assumed that these contracts will be extended so that they are available to meet summer peak load until the end of PNM will address these contract renewals in future IRPs closer to contract expiration dates. FIGURE 72. LONGTERM AVAILABLITY OF EXISTING AND CONTRACTED SUPPLYSIDE RESOURCES Existing PNM & Contracted SupplySide Resources MW Delta Valencia Reeves Lordsburg Afton CC Luna CC San Juan Four Corners Palo Verde 1&2 PNM Owned Solar NM WEC 0 49

62 Reviewing Existing System Resources PNM IRP Coal and nuclear resources are the leastcost of PNM s portfolio. EXISTING SUPPLYSIDE CAPACITY With the exception of the existing, intermittent renewable resources, the capacity listed in Table 77 under the label Total Capacity is expected to be fully available to meet system load and reserve margin requirements at the time of the summer peak for The capacity values for wind and solar depend on the amount of capacity they provide at peak. PNM s wind resources have been found to contribute only 5% of their installed capacity during summer peak. Solar resources contribute 55% of their installed capacity during peak. Figure 73 illustrates fuel mix as a percentage of the kilowatt hours generated. It is important to note that coal and nuclear resources are the least cost resources in PNM s portfolio. In total, 77% of the energy needs are met with these low cost resources. TABLE 77. EXISTING SYSTEM S TOTAL CAPACITY Resource Peak Contribution Total Capacity Energy Efficiency 0.74% 0.68% Demand Response 3.24% 2.99% Coal 43.66% 40.26% Nuclear 11.59% 10.68% Natural Gas 28.06% 25.87% Purchases (Gas Unit) 11.98% 11.04% Solar 0.30% 0.51% Wind 0.43% 7.97% Total, % 100.0% 100.0% Total Capacity, MW 2,509 2,313 FIGURE FUEL MIX SHOWN AS PERCENTAGE OF KILOWATT HOURS GENERATED Source: PNM Federal Energy Regulatory Commission (FERC) Form 1 50

63 Reviewing Existing System Resources PNM IRP EXISTING PNMOWNED RENEWABLE RESOURCES UTILITY OWNED SMALL PV SYSTEMS (RENEWABLE, SUPPLYSIDE RESOURCE, NNM SYSTEM) Installed prior to 2006, PNM operates a 25 kw solar installation located off of Interstate 25 in Algodones, New Mexico and a 5 kw rooftop fixed thinfilm flat plate PV installation at its Aztec office facilities located in Albuquerque, New Mexico. Both of these facilities are ratebased and serve to meet PNM s RPS obligation with a REC weighting of 3:1. Historical output of the facilities is shown in Table 78. PNM expects to maintain and operate these installations during the planning period. TABLE 78. HISTORICAL OUTPUT OF ALGODONES/AZTEC Facility Output (KWh) Algodones PV 9,162 75,376 37,849 34,915 29,012 Aztec PV 2,130 1,166 11,471 7,830 5,115 RECs Generated (kwh) Algodones PV 27, , , ,745 87,036 Aztec PV 6,391 33,498 34,413 23,490 15,345 UTILITY OWNED PV FACILITIES (RENEWABLE, SUPPLYSIDE RESOURCE, NNM & SNM SYSTEMS) The final order issued by the NMPRC in Case No UT on August 31, 2010 approved PNM s construction of 22 MW of fixed tilt, thinfilm solar PV panels located at five sites in PNM s service area: Albuquerque, Los Lunas, Las Vegas, Deming and Alamogordo. The Albuquerque site is located on the premises of Reeves Generating Station and achieved commercial operations on April 8, The Los Lunas solar PV was placed inservice June 1, PNM is currently developing the three remaining sites. Output of these facilities will be used to meet the RPS. Details of these facilities are provided in Table 79. Location Transmission Location TABLE 79. INSERVICE DATES OF PV FACILITIES Construction Start Date InService Installed Capacity (MW) Peak Contribution (MW) Expected First Full Year Production (MWh) Albuquerque NNM 2/15/2011 4/08/ ,680 Los Lunas NNM 4/15/2011 6/1/ ,699 Deming SNM 6/15/2011 8/8/ ,699 Las Vegas NNM 10/15/ /15/ ,699 Alamogordo SNM 8/15/ /15/ ,699 Total ,777 *An energy degradation factor of 0.5% per year is applied after the initial year of service. UTILITY OWNED PV/BATTERY DEMO PROJECT (RENEWABLE, SUPPLYSIDE RESOURCE, NNM SYSTEM) As part of the Department of Energy s smart grid demonstration program, PNM was selected as one of 16 nationwide locations to demonstrate the integration of renewable energy and 51

64 Reviewing Existing System Resources PNM IRP energy storage. The project features one of the largest combinations of battery storage and PV energy in the nation, and involves extensive research and development of smart grid concepts in cooperation with the University of New Mexico, Northern New Mexico College, East Penn Manufacturing and Sandia National Labs. Located in Albuquerque near Mesa del Sol, this 500 kw PV and 1MWh rated battery facility will have the ability to simultaneously smooth the intermittency of the PV output, while shifting output to peak periods. The shifting function will be accomplished with advanced lead acid batteries; ultra batteries will perform the smoothing function. The project will be highly instrumented, gathering one second interval data from over 200 points in the PV and battery systems. This data will be coupled with sophisticated computer models to refine controls and create a dispatchable renewable resource, where the capacity contribution will be raised from 55% to 100%. The plant construction started in late spring of 2011 and the facility is expected to be operational in August The initial energy production is expected to be 866 MWh/year, with an annual 0.5% degradation per year. Output of this project will serve to meet RPS solar diversity compliance. EXISTING PNMCONTRACTED RENEWABLE RESOURCES NEW MEXICO WIND ENERGY CENTER (RENEWABLE, SUPPLYSIDE RESOURCE, NNM SYSTEM) NMWEC is located on the eastern side of the state near House, New Mexico and interconnects to the PNM transmission system at the Taiban Mesa substation located on the BlackwaterBA 345 kilovolt (kv) line (BB Line). PNM purchases the renewable energy and the associated RECs from NextEra Energy, Inc. under a 25year PPA initiated in the fall of For purposes of this IRP, PNM assumed the contract would be renewed at its current cost for a period of two years to reach the end of the 20 year planning horizon. Historical data shows that wind energy from this installation contributes 5% of the installed capacity towards meeting the summer peak. Therefore, PNM credits NMWEC as having 10 MW of capacity available at peak. The amount of wind energy that NMWEC will provide is difficult to predict. A review of the historical data (see Table 710) shows that production can range from 500 GWh to 577 GWh per year. For purposes of this IRP PNM has forecasted 525 GWh of energy per year from the NMWEC, realizing that this annual amount could vary significantly. The NMWEC aids PNM in meeting its voluntary renewable tariff (SkyBlue) obligations and the RPS requirements. NMWEC fulfills PNM s wind diversity target. TABLE 710. NMWEC HISTORICAL PRODUCTION AND REC ALLOCATIONS Actual/Project Capacity SkyBlue Generation Factor Participation Wholesale Sales RPS Balance kwh % kwh kwh kwh ,758, ,710 3,500, ,248, ,587, ,204,879 63,100, ,282, ,068, ,752,287 65,800, ,515, ,429, ,035, ,900, ,493, ,560, ,697, ,090, ,772, ,507, ,497, ,576, ,433, ,288, ,855,368 59,950, ,483, ,241, ,722,091 82,157, ,362,166 52

65 Reviewing Existing System Resources PNM IRP EXISTING PNMOWNED SUPPLYSIDE RESOURCES REMOTE TO LOAD FOUR CORNERS POWER PLANT (SUPPLYSIDE, PNM JOINTOWNED RESOURCE, REMOTE LOCATION) The coalfired Four Corners Power Plant in Fruitland, New Mexico consists of five units that are operated by Arizona Public Service (APS). PNM owns 13% of unit 4 and 13% of unit 5, which supply 200 megawatts of base load capacity to PNM. Capacity in units 4 and 5 was acquired in 1969 and 1970, respectively. The fuel for Four Corners is supplied through a fuel agreement with the owners and BHP Navajo Coal Company (BNCC). BNCC holds a longterm coal mining lease with options for renewal from the Navajo Nation, and operates a surface mine adjacent to the Four Corners Power Plant. BNCC expects a sufficient fuel supply for the life of the units. APS, which oversees the administration of the coal contract, is currently negotiating with BNCC to extend the fuel supply past 2016, and has been granted an extension of the land lease from the Navajo Nation until Four Corners Power Plant is in the process of regional haze rulemaking through the EPA Region 9 Federal Implementation Plan (FIP). The first version of the draft FIP required SCR as BART to reduce nitrogen oxide emissions on Units 4 and 5 by A supplemental FIP put forth by the EPA proposed a BART alternative that would delay the implementation date for SCR installation on Units 4 and 5 to 2018, in exchange for APS shutting down Units 1 through 3. The FIP has not yet been finalized and is expected to be finalized after the filing of this IRP. Based upon these events, PNM assumes that the Four Corners Power Plant is an available resource and will serve to meet loads through the 2030 timeframe. Currently, PNM relies upon network transmission service rights to bring the energy from the plant into the northern New Mexico system to deliver to New Mexico loads. SAN JUAN GENERATING STATION (SUPPLYSIDE, PNMOWNED RESOURCE, REMOTE LOCATION) SJGS is a coalfired plant that consists of four units. PNM has an overall 46% ownership share, or 810 MW, of SJGS. The SJGS units were constructed as follows: Unit 1 in 1976, Unit 2 in 1973, Unit 3 in 1979 and Unit 4 in PNM is the majority owner of the plant as well as the plant operator. Table 711 shows the ownership by unit, and that PNM represents the largest ownership share by unit. SJGS is located in Waterflow, New Mexico near Farmington, in the four corners region of the state. PNM s ownership share of Unit 3 represents its largest single resource (263 MW). SJGS is PNM s primary source of baseload generation, and PNM relies upon network transmission service rights to bring SJGS energy into the northern New Mexico system to deliver to New Mexico loads. Recent upgrades in equipment have resulted in new capacity uprates, for Unit 1 and Unit 2 and capacity uprates at Unit 3 and Unit 4 are expected by yearend PNM has used the expected capacity uprates at all SJGS units for planning purposes. PNM purchases coal for SJGS from the adjacent underground coal mine owned by the San Juan Coal Company (SJCC), a subsidiary of BHP Billiton. PNM oversees the administration of the coal contract, and is currently negotiating with SJCC to extend the fuel supply past 2017, as well as investigating other fuel supply sources. The regional haze requirements for SJGS are currently being developed by NMEIB and the EPA. On June 2, 2011, the NMEIB approved a State Implementation Plan that includes a determination that BART for SJGS is SNCR technology on all four units. The EPA s decision on 53

66 Reviewing Existing System Resources PNM IRP BART is expected by August 5, Since the EPA s final decision will likely occur after the filing of this IRP, PNM modeled various scenarios to assess an array of outcomes. TABLE 711. SJGS OWNERSHIP BY UNIT Owner Unit 1 Unit 2 Unit 3 Unit 4 PNM 50% 50% 50% 38% Tucson Electric 50% 50% TriState 8% SCAPPA 42% Anaheim 10% City of Farmington 8% Los Alamos County 7% MSR 29% UAMPS 7% Total 100% 100% 100% 100% Size, MW (Total) 1, Size, MW (PNM Share) Size, MW (PNM Operating Share) PALO VERDE NUCLEAR GENERATING STATION (SUPPLYSIDE. PNM JOINTOWNED RESOURCE, REMOTE LOCATION) PVNGS is a nuclear power plant operated by APS that consists of three units located west of Phoenix in Wintersburg, Arizona. Units 1 and 2 were completed and placed in service in 1986 and Unit 3 was completed and placed in service in The original PVNGS operating licenses ran through 2025 to 2027; however, on April 21, 2011, the Nuclear Regulatory Commission approved an application to extend the operating licenses of all three units at the PVNGS for an additional 20 years. Unit 1 was extended to 2045 and Unit 2 through PNM has capacity rights to 134 MW from each of the three units (i.e., 10.2% of each unit). Only the capacity associated with Units 1 and 2, which totals 268 megawatts, is included in the jurisdictional resource portfolio. Unit 3 was excluded from the jurisdiction based on an NMPRC determination in Case In 1985 and 1986, PNM undertook sale/leaseback financing of its Unit 1 and Unit 2 holdings. In the intervening years, PNM has bought back 90 MW of that leasefinanced capacity. Currently, PNM owns 30 MW in Unit 1 and 60 MW in Unit 2; the remaining 104 MW in Unit 1 and 74 MW in Unit 2 continue to be leased by PNM from financial investors. The remaining leases for PVNGS Unit 1 and Unit 2 expire in , and PNM has options to extend the leases or purchase its interest in those units. For the purposes of this plan PNM has assumed that the leases will continue for the duration of the planning period at the current lease costs. PNM will consider any opportunities to buy back more of the leased capacity. A detailed listing of the PVNGS participants, as well as leased/owned amounts of capacity that PNM relies on to meet customer loads, is provided in Table

67 Reviewing Existing System Resources PNM IRP TABLE 712. OWNERSHIP BY UNIT OF PVNGS Palo Verde Nuclear Generating Unit 1 MWs Unit 2 Percent Station MWs Utility Owners 1 Arizona Public Service % 2 Salt River Project % 3 El Paso Electric % 4 Southern California Edison % 5 SCPPA (SoCal Public Power) % 6 LADWP (Los Angeles) % 7 PNM % 8 Total % PNM Capacity Rights 9 Leased Capacity % 10 Owned Capacity % 11 Total PNM % Since 2005, PVNGS has undertaken a number of projects that were designed to increase output capacity, improve operating efficiency and replace aging equipment. Recent major projects have included replacement and upgrades of steam generators, low pressure turbines, and generator rotors along with numerous process improvements. As a result, PNM s capacity rating for its share of PVNGS has increased from 387 MW to 402 MW. In 2010, PVNGS set a single year energy generation record for U.S. generating facilities at 31.2 million MWh. PNM relies on network transmission rights to deliver energy from PVNGS to serve retail loads in New Mexico. The plant obtains its fuel supply through longterm contracts. For planning purposes, the transmission rights to bring PVNGS to New Mexico, as well as the longterm fuel contracts, are expected to extend throughout the planning period. EXISTING PNMOWNED SUPPLYSIDE RESOURCES NEAR LOAD AFTON GENERATING STATION (SUPPLYSIDE, PNMOWNED RESOURCE, LOCATED WITHIN SNM SYSTEM) The Afton Generating Station (Afton) is a 230MW natural gas combined cycle generating plant located within PNM s concentrated load pocket in southern New Mexico. Afton was originally constructed as a simple cycle merchant facility and became operational in December In October 2006, the NMPRC issued a Certificate of Public Convenience and Necessity (CCN) to convert the simple cycle facility to a combinedcycle facility and to make it a jurisdictional resource. The Afton combined cycle plant consists of one gas turbine, a heat recovery steam generator (HRSG) and a steam turbine, in a 1x1x1 configuration (commonly referred to as a 1x1 ). The upgraded 1x1 combined cycle facility became operational in the fall of 2007 and has the flexibility to operate in simple cycle mode. Afton is able to deliver to SNM loads or can be delivered via contracted transmission rights to the northern New Mexico system to serve NNM loads if needed. Natural gas is transported and delivered to the Afton facility via the El 55

68 Reviewing Existing System Resources PNM IRP Paso Natural Gas Company southern main line. PNM assesses natural gas requirements for Afton on a monthly basis, taking into consideration the load, weather and other events, such as forced outages in the fleet, and then and makes purchases for the upcoming month. LUNA ENERGY FACILITY (SUPPLYSIDE, PNM JOINTOWNED RESOURCE, LOCATED WITHIN THE SNM SYSTEM) The Luna Energy Facility is a combined cycle natural gas plant constructed in 2006 near Deming, New Mexico. This facility is configured with two General Electric (GE) heavy frame 7FA gas turbines each connected to a HRSG; both HRSGs are attached to one steam turbine, or a 2x2x1 configuration, commonly called a 2x1. PNM owns onethird, or 185 MW, of Luna. Tucson Electric and FreeportMcMoRan also own onethird interests. In 2008, the NMPRC granted a CCN to PNM in Case UT which made PNM s shares of Luna a jurisdictional resource. Unlike Afton, Luna can only operate in combined cycle mode. Luna is able to deliver to SNM loads directly or, via contracted transmission rights, to PNM s northern load centers. PNM oversees the plant operation and maintenance on behalf of the owners through a long term service agreement with North American Energy Services (NAES). NAES operates and maintains the plant. Luna receives a natural gas supply via the El Paso Natural Gas southern main line in New Mexico. Each owner purchases its own fuel supply. PNM assesses natural gas requirements for Luna taking into consideration the load, weather and other events such as forced outages in the fleet. Natural gas is purchased on a monthly basis for the upcoming month. LORDSBURG GENERATING STATION (SUPPLYSIDE, PNMOWNED RESOURCE, LOCATED WITHIN THE SNM SYSTEM) Lordsburg Generating Station (Lordsburg) is an aeroderivative natural gasfired peaking facility located near Lordsburg, New Mexico. Lordsburg has two GE LM6000 units which can deliver a total of 80 MW of peaking capacity and 80 MWs of fast start capability needed for system load balancing and regulation. PNM obtained a CCN to make Lordsburg a jurisdictional facility in Case UT decided in Located in the concentrated southern NM load pocket, Energy from Lordsburg can be delivered directly to SNM loads, or can be delivered via contracted transmission rights to PNM s northern load centers. PNM has contracted with NAES to operate and maintain Lordsburg under a service agreement. Lordsburg receives a natural gas supply via the El Paso Natural Gas southern main line. Natural gas for Lordsburg is assessed on a monthly basis for fuel supply requirements, taking into consideration the load, weather and other events such as forced outages in the fleet. Purchases are then made for the upcoming month. LAS VEGAS (SUPPLYSIDE, PNM OWNED RESOURCE, NNM SYSTEM) PNM acquired the Las Vegas Generating Station in 1973 and operated it from 1973 until March, 2011 when it was taken out of service pursuant to an NMPRC order of abandonment in Case No UT. The facility was a simple cycle combustion turbine (CT) of 18 MW on peak located within the city of Las Vegas, New Mexico, north of Santa Fe that was operated intermittently to meet peaking needs and to facilitate line maintenance in the Santa Fe and Las Vegas areas. Activities have begun to enable the facility to be dismantled. This resource is no longer available to serve load. 56

69 Reviewing Existing System Resources PNM IRP REEVES GENERATING STATION (SUPPLYSIDE, PNM OWNED RESOURCE, NNM SYSTEM) The Reeves Generating Station (Reeves) is located southwest of the Paseo del Norte and Jefferson intersection in the city of Albuquerque. The 154 MW facility is a natural gas steam electric plant comprising three units. Unit 1 became operational in 1958 and has a 44 MW steam turbine generator (STG). Unit 2 became operational in 1958 and has a capacity of 44 MW, and Unit 3 became operational in 1962 and has a 66 MW capacity. During 2010 and 2011, PNM overhauled Unit 1 and 2 and installed new distributed controls systems to increase reliability and prolong the life of these units. PNM is addressing the aging of this facility through ongoing maintenance programs, and has factoredin required maintenance to reach the end of the planning period in Natural gas is transported and delivered to the Reeves facility under New Mexico Gas Company s natural gas transmission and distribution tariff rates. Fuel supply is assessed on a monthly basis and purchased for the upcoming month. PNM operates these units not only to meet generation requirements but also to relieve transmission constraints and provide system voltage support. EXISTING, PURCHASED SUPPLYSIDE RESOURCES, REMOTE AND NEAR LOAD DELTAPERSON GENERATING STATION (SUPPLYSIDE, PURCHASED POWER, NNM SYSTEM) The Delta Generator (DeltaPerson) is owned by Delta Power, LLC and is located on the south side of Albuquerque off of Interstate 25 at the site of the former Person Generating Station which is owned by PNM. This station consists of a GE 7F combustion turbine from which PNM purchases 132 MW of natural gasfired capacity (or 148 MW of fuel oilfired capacity) under a longterm PPA, which expires on June 30, Due to Person s location within the NNM load center, it is a critical PNM loadside resource for both generation requirements and to relieve transmission system constraints and provide voltage support. For this IRP, PNM has assumed that the PPA will be renewed for the duration of the twentyyear planning period at costeffective terms. The natural gas supply for Delta is delivered to the facility under New Mexico Gas Company s gas transportation and distribution tariffs and purchased [by PNM?] for the upcoming month. The DeltaPerson PPA was included as a jurisdictional resource in t Case No SOUTHWESTERN PUBLIC SERVICE COMPANY PPA (SUPPLYSIDE, PURCHASED POWER, NNM SYSTEM) Prior to its expiration on May 31, 2011, PNM purchased 100 megawatts of capacity and energy from SPS system resources under this PPA. The power was delivered to PNM via the Blackwater highvoltage direct current (DC) converter station that interconnects the PNM system with the SPS system. The capacity provided under the SPS contract was interruptible for up to 5% of the hours each month. SPS did not offer PNM the opportunity to extend the contract. 57

70 Reviewing Existing System Resources PNM IRP VALENCIA ENERGY FACILILTY PPA (SUPPLYSIDE, PURCHASED POWER, LOCATED WITHIN SNM SYSTEM) The Valencia Energy Facility is located south of the city of Belen and houses a heavyframe GE 7FA gas turbine that began commercial operations on May 30, 2008 and supplies PNM with approximately 145 megawatts of peaking power under a 20 year PPA with Southwest Generation, LLC that expires in For the purposes of this IRP, PNM has assumed that the contract term will be extended to 2030, the end of the planning period. Valencia receives its natural gas fuel supply through a fourmile long pipeline interconnection to Transwestern s interstate pipeline. It was approved as a jurisdictional resource in Case No UT. OPERATIONAL INFORMATION The IRP Rule requires a report describing the resources used by the utility to meet jurisdictional retail load at the time of filing. The following tables provide the details required by the Rule for all PNM owned and contracted resources. An overview of the location, ownership share, inservice date and the amount of capacity for each PNM contracted resource can be found in Table 713. Similar information for owned resources can also be found in Table 714. TABLE 713. PNM CONTRACTED RESOURCES SHOWN (IRP RULE C) PNM Purchases NM Wind Energy Center Load Side Contract Capacity (MW) Fuel Type NNM 204 Wind DeltaPerson NNM 132 Valencia Energy Facility NNM 145 SPS NNM 100 Natural Gas Natural Gas Not Specified Duty Cycle Intermittent (10 MW capacity) Peak Contribution (MW) 10 Peaking 132 Peaking 145 Base & Intermediate Total Comments Contract through July 2028 Contract through June 2020, 34 MW fast start capability Contract through May 2027 Contract terminated May 31,

71 Reviewing Existing System Resources PNM IRP TABLE 714. PNMOWNED SUPPLYSIDE RESOURCES (IRP RULE C) Generating Resource Palo Verde Unit 1 Palo Verde Unit 2 San Juan Unit 1 In Service Date Retirement Date Location Wintersburg, AZ Wintersburg, AZ 1976 After 2030 Waterflow, NM Unit Capacity (MW) PNM Capacity (MW) Ownership Share % Fuel Type Duty Cycle Comments 1, % Nuclear Base 30 MW owned 104MW leased 1, % Nuclear Base 60 MW owned 74 MW leased % Coal Base San Juan Unit 2 San Juan Unit 3 San Juan Unit 4 Four Corners Unit 4 Four Corners Unit After After After 2030 Waterflow, NM Waterflow, NM Waterflow, NM % Coal Base % Coal Base % Coal Base 1969 After 2030 Fruitland, NM % Coal Base 1970 After 2030 Fruitland, NM % Coal Base Afton CC 2007 After 2030 La Mesa, NM % Luna CC 2006 After 2030 Deming, NM % Lordsburg Unit 1 Lordsburg Unit 2 Reeves Unit After After After 2030 Lordsburg, NM Lordsburg, NM Albuquerque, NM % % % Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Intermediate Intermediate Peaking Peaking Peaking 221 MW PNM Operating Share 249 MW PNM Operating Share Approved rate base in 2008 Approved rate base in 2008; provides 40 MW faststart Approved rate base in 2008; provides 40 MW faststart 51 years old Reeves Unit After 2030 Albuquerque, NM % Natural Gas Peaking 52 years old Reeves Unit After 2030 Albuquerque, NM % Natural Gas Peaking 49 years old Las Vegas CT Las Vegas, NM % Gas/Oil Peaking Abandonment approved Algodones & Aztec Solar 2001, 2005 After 2030 Various % Solar Base Total 2,086 59

72 Reviewing Existing System Resources PNM IRP TABLE 715. O&M COSTS: OWNED AND CONTRACTED RESOURCES (IRP RULE C) Resource PNM Share (MW) Fuel Type or Source Heat Rate (Btu/kWh) Dispatch Ramp Rate (MW/min.) Cap. Factor Ranges (%) O&M* (k$/yr) 2010 Equivalent Availability (%) 2010 Forced Outage Rate (%) Distributed Generation Algodones & Aztec Solar PV 0.03 Solar N/A N/A 26.7% <$1 N/A N/A Renewable New Mexico Wind Energy Center (PPA) 204 Wind N/A N/A 30% N/A N/A N/A PV/Battery Demo 0.5 Solar N/A N/A 26.7% TBD N/A N/A Utility Owned PV 22 Solar N/A N/A 26.7% $528 N/A N/A Nuclear Palo Verde Units 1,2 268 Uranium 10,420 <1 70% 95% $40, % 1.0% Natural Gas Afton 230 Nat. Gas 7, % 65% $6, % 2.5% Luna 185 Nat. Gas % 65% $5, % 0.3% Lordsburg Units 1,2 80 Nat. Gas % 15% $1, % 5.4% Reeves Units 1, 2, Nat. Gas 10, % 15% $4, % 0.5% DeltaPerson (PPA) 132 Nat. Gas 12, % 15% Valencia (PPA) 145 Nat. Gas 10, % 15% Coal Contract Prices Contract Prices Unknown Unknown Unknown Unknown Four Corners Units 4,5 San Juan Units 1,2,3,4 200 Coal 9, % 85% $13, % 14.6% 810 Coal 10, % 85% $60, % 19.0% Other Las Vegas CT 18 Nat. Gas % 5% $59 >90% N/A SPS (PPA) 100 Unknown N/A N/A 40% 95% Contract Prices Unknown Unknown * Figure includes all fixed and variable O & M costs required to operate the plant. Solar distributed generation rates reflect the Aztec solar PV facility and the Algodones solar PV array. Capacity factors are representative only because dispatchable units are not constrained to stay within these limits. It may be possible for the units to economically dispatch outside these ranges, depending on modeled inputs. Dispatch ramp rate refers to the rate that a generator changes its output, expressed in MW per minute. 60

73 Reviewing Existing System Resources PNM IRP As per the IRP rule, the operational characteristics, cost details and expected operating ranges for each existing generation and contractual resource sorted by fuel type are provided in Table 715. This table details the expected operations and maintenance (O&M) costs for each resource, equivalent availability, forced outage rates, heat rates and dispatch ramp rates. With the exception of the O&M estimates for PNMowned resources, all the information contained in the table is based on yearend 2010 data. Numbers in Table 715 for O&M represent levelized expenses for a five year period. Environmental performance for each plant as well as water use is provided in Table 716. These data were used in the modeling phase of the IRP process for the entire planning period. EXISTING RESOURCE ENVIRONMENTAL IMPACT TABLE 716. ENVIRONMENTAL IMPACTS OF PNM OWNED AND CONTRACTED RESOURCES Resource Natural Gas CO NO x Particulate SO 2 CO 2 Mercury Water lbs/kwh lbs/kwh lbs/kwh lbs/kwh lbs/mwh lbs/kwh gals/mwh Afton n/a 123 Lordsburg ,125 n/a 194 Luna n/a 290 Reeves ,260 n/a 927 Delta ,289 n/a 28 Valencia ,579 n/a 31 Coal San Juan , Four Corners Nuclear , PVNGS n/a n/a n/a n/a n/a n/a 768 Other NMWEC n/a n/a n/a n/a n/a n/a 4 PV Solar n/a n/a n/a n/a n/a n/a 0 * data thru 9/30/10 WATER USE AT EXISTING PLANTS New Mexico s arid climate and periodic drought conditions raise questions about the extent of water use for various purposes, including for power generation. However, less than 2% of the water withdrawals in New Mexico are used in the generation of electricity and water cost 61

74 Reviewing Existing System Resources PNM IRP is a very small component of PNM s total generating costs. Even so, PNM is committed to conserving water resources. PNM s generation facilities vary in their water consumption. Table 717 illustrates the gallons consumed per MWh, also known as water intensity, by PNM s current generation fleet, along with some potential future sources of generation. Solar PV and wind do not consume water and simplecycle gas turbines use little water. Steamturbine plants (such as combinedcycle, coal and nuclear) use the most water primarily because of the need to cool (for reuse) the steam that turns the turbines. The newer gasturbines like Delta and Valencia are much less water intensive than the 1950s era Reeves steamturbine technology. It should also be noted that PVNGS uses reclaimed city water for cooling, so its fresh water intensity is about 20 gallons per MWh compared to its total water intensity of 768 gallons per MWh. TABLE 717. WATER INTENSITIES BY GENERATION TYPE (WET COOLED) 1,200 Water Intensities by Generation Type 1, Baseload/Steam Treated Wastewater Renewables gal/mwh Combined Cycle Gas Gas Turbines Fresh water 0 Afton is hybrid cooling Blue represents existing resources; Green represents potential future resources. WATER SECURITY AT EXISTING PLANTS Providing for a reliable, sustainable water supply is essential to the successful operation of PNM s generation fleet and is the focus of its Water Resources group. Using a variety of strategies, including water conservation, water rights acquisitions, shortage sharing 62

75 Reviewing Existing System Resources PNM IRP agreements, and modern technologies, PNM mitigates the risk that a lack of water could impact the availability of its generation fleet for power production. PNM has secured groundwater rights in connection with the plants at Reeves, Delta Person, Afton, Luna, and Lordsburg. Groundwater is much less susceptible to annual variations in water availability than is surface water. Reclaimed city waste water is used at Luna and PVNGS. Hybrid Cooling (combination of wet and dry) is utilized at Afton to reduce water consumption. These approaches serve to minimize the fresh water used at those plants. Severe drought in the Four Corners region, similar to the 2002 drought, could affect the availability of the SJGS and Four Corners plants because they use surface water for cooling. Consequently, PNM has undertaken to mitigate this potential by entering into agreements for sharing the impacts of water shortages with tribes and other water users in the San Juan Basin (shortage sharing agreements). Further, in case of a water shortage, PNM has agreements for supplemental water supplies with the Jicarilla Apache Nation and BHP Billiton for use at SJGS. In April 2010, APS signed a 40year agreement on behalf of the PVNGS participants with five cities to provide cooling water for power production at PVNGS. EXISTING TRANSMISSION REGULATORY BACKDROP Over the last 15 years, the U.S. electric transmission in has undergone remarkable changes. The largest change stems from the 1996 implementation of the FERC Order No This order requires that a jurisdictional transmission provider, such as PNM, provide open access to its transmission system to all eligible customers via an Open Access Transmission Tariff (OATT or Tariff). Eligible customers (e.g., TriState Generation and Transmission on behalf of its cooperative members, Los Alamos County, etc.) under the Tariff, can contract for Network Integration Transmission Service (NITS) to integrate their designated network resources and designated network loads on the PNM transmission system in a manner comparable to which PNM serves its own retail and wholesale customers. Tariff customers can also choose to contract for firm pointtopoint transmission service on a longterm basis with rollover rights that are essentially perpetual. The OATT obligates PNM to plan its transmission system to meet not only its own retail customer needs, but also its delivery obligations to NITS and longterm, firm pointtopoint transmission service customers. Order No. 890, issued in February 2007, clarified and strengthened these obligations and required regional coordination of transmission plans. The Energy Policy Act of 2005 (EPACT) legislated the implementation on a nationwide basis of mandatory transmission grid reliability rules for all owners, operators and users of the systems. Under the EPACT, FERC was given authority to develop, monitor and enforce all aspects of transmission grid reliability. FERC delegated to NERC the role of the national Electric Reliability Organization (ERO). The WECC has been delegated the role of a Regional Entity and will monitor and enforce the mandatory reliability standards in the West. Adherence to reliability standards on the western grid prior to passage and implementation 63

76 Reviewing Existing System Resources PNM IRP of the EPACT was accomplished through a voluntary contractual reliability management system. Failing to comply with the ERO standards subjects a utility to sanctions and civil penalties of up to $1 million per day, for each incident for the most substantive failures to follow FERC s grid reliability rules. TRANSMISSION SYSTEM DEVELOPMENT The New Mexico transmission system has undergone dramatic changes in its configuration and uses since its inception. The initial system consisted of 46 kv and 115 kv lines used to deliver locally generated energy to local loads. In the 1950s and 1960s, lines between the cities began to be built so local generators could provide backup support to each other, and an associated increase in reliability of service was obtained. PNM s first tie to the outside world was by way of a 230 kv line to Four Corners built in 1962, concurrent with APS construction of the original Four Corners Power Plant. The basic 345 kv transmission system that is in place today was developed in the late 1960s and early 1970s as the larger coalfired generating units at Four Corners Power Plant and SJGS were brought online. This shifted large base load generation from local to remote resources away from load centers, due partly to environmental, economic, water, and fuel availability considerations, while smaller and less efficient intermediate and peaking units were located within the load centers. The availability of remote resources with a low cost coal and nuclear fuel mix resulted in the dispatch of generating plants near the load centers being limited to peak hours of the summer, or when transmission system import limits would otherwise be exceeded. Economics drive the maximum use of energy brought in from the more efficient and larger remote generators. The last PNM backbone transmission line was completed in 1984 when PNM constructed the Eastern Interconnection Project, a 223mile 345 kv line from the Placitas area north of Albuquerque located at BA 345 kv Switching Station to Clovis, New Mexico interconnecting PNM with SPS through the Blackwater ACDCAC converter station. During the 1990s, PNM pursued the Ojo Line Extension (OLE) project to complete a third 345 kv path from the Four Corners area to the major load centers, to reinforce the 345 kv backbone transmission system, and increase import capability into the NNM system. Ultimately, permission to build the OLE project was denied and PNM focused its efforts on transmission reinforcements that maximized the use of the existing NNM system transmission lines. In the late 1990s, PNM purchased several transmission assets from TriState Generation and Transmission (TriState). Purchase of these assets allowed PNM to upgrade key portions of the system, further enhancing the import capability of the NNM System. PNM has made numerous modifications to the existing system in the past 15 years to maximize its use. However, PNM has reached the point where few, if any, opportunities remain to extract additional capability from the existing NNM System. Because of the configuration of the New Mexico system (i.e., the locations of the loads, generation and major transmission lines), a large portion of the power used to serve PNM and its transmission customers load flows across the NNM system, independent of where it is generated. All generation transmitted to PNM load in NorthCentral New Mexico from the Four Corners area and the western grid flows on the NNM system. Also, generation resources in southern New Mexico can be delivered from the Southern New Mexico (SNM) system to 64

77 Reviewing Existing System Resources PNM IRP customers in the NNM system. As customer usage on PNM s transmission system continues to increase, flows from the SNM system to the NNM System will continue unless new resources are located close to the PNM load centers in northern New Mexico. While the NNM system serves the majority of the overall PNM load, the SNM system is capable of serving PNM load in southern load centers from the Afton, Luna and Lordsburg generating plants. Resources from the NNM system can also be used to serve PNM southern loads via imports on existing transmission rights. The SNM system is also capable of exporting power into the NNM system. TRANSMISSION NETWORK CUSTOMERS In addition to PNM wholesale and retail customers, PNM is obligated to ensure delivery capability to all transmission customers (NITS, pointtopoint and preoatt contract customers) across PNM s system. Approximately 40% to 45% of the PNM system is used to provide transmission service for others compared to its own load needs. Network customers include: TriState, Los Alamos County (LAC), Navajo Tribal Utility Authority (NTUA), Western Area Power Administration (WAPA) for Kirtland Air Force Base, Navopache Electric Cooperative (NEC), and PNMWholesale Power Marketing (WPM) (for PNM retail, City of Gallup, City of Aztec) Pointtopoint customers include: El Paso Electric Company (EPE), High Lonesome Mesa, Aragonne Mesa, NextEra, WAPA, and PNMWPM Reference IRP Rule section C(11)(a), existing transmission capabilities: EXISTING TRANSMISSION CAPABILITIES Reliability of supply is a very important consideration for identifying the most costeffective resource portfolio. PNM s transmission system plays a key role in ensuring the reliable delivery of PNM s resources. A detailed discussion of the transmission and distribution systems is beyond the scope of this document. A more in depth report, including diagrams of the lines, stations and terminal facilities, can be obtained by downloading PNM s most recent FERC Form 715 filing from the FERC website at A listing of PNM owned transmission facilities at 115 kv and above is included in Appendix C. At a high level, the PNM system can be described by the block diagram in Figure 420, which shows the relative generation and load diversity of the PNM system. This diagram illustrates where load and resources (L&R) are located and where loads are served. It illustrates that the majority of the PNM load (88.9 %) is located in North/Central New Mexico. Similarly, more than 50% of PNM s resources are located at Four Corners or beyond that is transmitted, or wheeled, to North/Central New Mexico for delivery. Although physical connections exist between PNM and the Southwest Power Pool (SPP) to the east, no supply side resources are currently being imported from the SPP grid to serve PNM load for two reasons; 1) PNM s capacity on the transmission line connecting SPP at the Blackwater DC converter station to North/Central NM is fully committed by existing transmission customers and 2) import rights do exist from the SPP grid to the SNM system but there are currently nosupply side 65

78 Reviewing Existing System Resources PNM IRP resources available for contract. Adequate PNM serving capacity does exists to currently serve SNM loads. FIGURE 720. OVERVIEW OF EXISTING SYSTEM REPRESENTATION DURING PEAK LOAD North/Central NM: 21.6% of Generation 88.9% of Load WECC: 11.9% of Generation Four Corners: 43.9% of Generation 3.4 % of Load Southern NM: 22.6% of Generation 7.7% of Load SPP: 0.0% of Generation After many years of operating with other utilities within an interconnected system, PNM devised a plan to operate the transmission system in a safe and reliable way. PNM identified a path of transmission lines, tie points (points of connection between two or more utilities), or transformers and determined a safe operating limit for the system. At this path limit, the system can be operated in a safe and reliable manner and can handle the loss of a major element (e.g., line, transformer, and tie point) without affecting the quality of service delivered by the transmission system. In most cases, customers never know when an element is out of service because the system is operated in a manner that minimizes the effects on customers. In New Mexico, there are two paths that define the planning and operation of the transmission system. Path 48 controls the operation of the northern part of the state, and Path 47 controls the operation of the southern part of the state illustrated in Figure 721. Orange lines represent transmission lines in Path 48. Purple lines represent transmission lines in Path 47. Black and grey colored lines represent transmission that is external to that of Path 47 or Path 48 to other transmission systems. Assets within each path comprise a combination of PNM and nonpnm owned lines and/or stations. Any transaction that takes place on the PNM system with neighboring systems is bound by the operation of these paths. Resources that are required by PNM or other utilities to serve load within Path 47 or Path 48 usually help or enhance the operation of these paths by providing a local resource at the load center. When the load increases and Path 48 approaches its import limit, these additional resources can be dispatched to support the system from within a path. Siting, permitting, cost and construction timelines in new transmission line projects will continue to be a challenge. The use of loadside generation will continue to play a role in supporting the system and alleviating transmission constraints barring any future barriers to this type of operating practice. 66

79 Reviewing Existing System Resources PNM IRP FIGURE 721. WECC PATH 47 AND 48 Path 48 Walsenburg Shiprock Four Corners San Juan Taos Springer Clayton Ojo Gladstone Los Alamos Espanola Norton McKinley Bluewater Ambrosia BA Albuquerque Network Springerville Path 47 WECC SPP Blackwater Alamogordo Elephant Butte Holloman Greenlee Silver City Hidalgo Las Cruces WSMR Amrad Eddy Co. Luna Newman Diablo CFEJuarez El Paso El Paso Network Caliente 500 & 345 kv Lines 230 kv Lines 115kV Lines Switching/Substations Note: Path ratings used are for illustration purposes only. For complete path information, consult the WECC Path Ratings catalogue. 67

80 Reviewing Existing System Resources PNM IRP FIGURE 722. TRANSMISSION IMPORT LIMITS RELATIVE TO EXISTING NORTHERN NM GENERATION Legend: Future Transmision Commitments Future Load Commitments Load Serving Capablity: Total Transfer Capacity Plus Existing Load Side Generation Total Transfer Transfer Capablity ) W2200 (M

81 Reviewing Existing System Resources PNM IRP NORTHERN NEW MEXICO TRANSMISSION SYSTEM The NNM transmission system includes the WECC rated Path 48. This system delivers power to serve PNM s customer loads in NNM including the Albuquerque, Santa Fe and Las Vegas areas, as well as load areas in Valencia County south of the city of Albuquerque. As mentioned earlier, the NNM transmission system must accommodate 88.9% of PNM s total load, which affects its future ability to deliver necessary resources to meet load requirements. Figure 722 illustrates when new capacity is needed in the load center to support the transmission system. The annual bars represent the existing customer load compared against the current transfer capability (i.e., dark blue line), as well as the current total ability (i.e., import capability plus internal Path 48 generation) to serve loads within the WECC Path 48 constraint (i.e., green line). Projections of the transmission requirement for serving the combined PNM NNM load and transmission customer obligations illustrate a need to expand the existing transmission or generation system in This constraint problem could be solved a number of ways as previously discussed. Possible solutions include new resources inside the Path 48 boundary, a new transmission line and/or system reinforcements that increase import capabilities on Path 48, or through additional DSM options that decrease loads inside the Path 48 boundary. SOUTHERN NEW MEXICO TRANSMISSION SYSTEM PNM s SNM system delivers power to a combination of jurisdictional service territories which include Deming, Silver City, Lordsburg, Alamogordo, and Ruidoso. The SNM system also contains three natural gas plants in Afton, Luna, and Lordsburg that PNM integrates into its resource portfolio to effectively dispatch and serve load while minimizing overall utility costs. Figure 723 illustrates the relationship between PNM s SNM and NNM import/export rights on the transmission system. These power delivery rights exist over a combination of PNM, TriState and EPE assets. Arrows in Figure 723 indicate the direction of transmission rights utilized between stations across paths at various times to integrate SNM resources into the entire PNM system. FIGURE 723. SNM TRANSMISSION SYSTEM 69

82 Reviewing Existing System Resources PNM IRP Afton, Luna and Lordsburg generation resources provide a total 495 MW of capacity. Since they are located inside the Path 47 transmission boundary, these resources can adequately serve loads in SNM with the ability to deliver power to NNM via 345 MW of transmission rights when needed. Currently, there is ample generation resource to serve 160 MW of PNM load in the SNM system. In addition, PNM currently possesses rights to approximately 89 MW of transmission resources to deliver power from NNM to SNM into the Path 47 transmission boundary. Reference IRP Rule section (C)(11)(a), under construction UNDER CONSTRUCTION TRANSMISSION FACILITIES PNM s transmission construction plans are derived from its annual transmission planning process. The projects listed below are currently under construction or have been completed recently. These projects are intended to provide additional transmission capability or voltage support at existing stations with one newly constructed station built to support loads in the expanding Rio Rancho area. YahTaHey Additional Capacitors provides additional voltage support to reliably serve new load in the Gallup area (completed 2010) Mimbres Shunt Capacitor Addition provides reactive support to maintain acceptable voltage in the Deming Area (completed 2011) Alamogordo Third Source provides a third 115 kv transmission source into the Alamogordo station for additional transmission capability to maintain adequate service to existing and new loads (completed 2011) Rio Puerco Phase 1 provides additional transmission facilities to meet electrical service requirements of the fast growing Rio Rancho area (completed 2011) Belen Series Reactor mitigates overloads on TriState owned lines (projected to be completed in fall 2011) Alamogordo Dynamic Voltage Support provides adequate voltage and operational flexibility by increasing the transmission load serving capability (planned for 2012) Moriarty Capacitor provides additional voltage support for the central NM transmission system (planned for 2012) SW Albuquerque Support provides additional load serving capability for the Albuquerque Metro area (planned beyond 2012) Rio Puerco Phase 2 mitigates overloads for the loss of the BARio Puerco 345 kv line (planned for 2013) Replace Ojo 345/115 kv Transformer mitigate potential failure (planned for 2013) 70

83 Reviewing Existing System Resources PNM IRP YahTaHey Transformer mitigates overloads and improves YahTaHey voltage performance (planned for 2014) Ojo Voltage Support provides dynamic voltage support for Northeast area (planed beyond 2015) Taos Voltage Support provide dynamic voltage support for the Northeast Area (planned beyond 2015) Rio Puerco Progress 115 kv Line provides additional load serving capability to northern Rio Rancho area (planned beyond 2020) The major transmission lines owned by PNM were primarily developed to deliver remote resources from the Four Corners area of New Mexico to retail and wholesale customers near the load centers in northern and southern New Mexico (refer to section Existing PNM Owned SupplySide Resources Remote to Load). PNM s capacity in these facilities is fully committed to existing firm resources, and expansion of the transmission system would need to be factored into siting of additional remote supplyside resources. PNM has a single transmission line to the Albuquerque area from eastern New Mexico with a DC converter station allowing transfers between the PNM system and the eastern grid system. PNM s capacity on this eastern tie line is fully used by existing transmission customers. Similar issues would be expected for new resources sited in southern New Mexico that needed to be delivered to PNM loads in northern New Mexico system (see Figure 723 for existing SNM import/export rights). Deliverability of such resources would require expansion of the transmission system on the El Paso Electric. It may be possible to purchase additional capacity to the Four Corners area from Southern New Mexico, but the resources would then be subject to the same restrictions as additional Four Corners resources that would need to be imported into northern New Mexico. Resources sited near the loads are generally not viewed as restricted by transfer capability but can still require transmission improvements to address local network overload or voltage problems that can occur due to increased flows that result from the new resources. The required improvements tend to be specific to each interconnection location and should be reviewed on a case by case basis. TRANSMISSION RELIABILITY COMPLIANCE PNM plans and operates its transmission system to provide reliable service to its customers and all entities that use its system in accordance with NERC/WECC Operating and Planning Standards. Reliability comprises two measures: adequacy and security. Adequacy addresses the basic ability of the system to transmit power as it is needed. Security addresses the ability of the system to withstand a sudden disturbance or contingency while continuing to provide service. PNM serves as the NERC certified Balancing Authority (BA) for a large portion of the WECC area of New Mexico and must meet NERC reliability performance standards. Certified operators continuously monitor and use manual and automated means to maintain balance by adjusting imports/exports and maneuvering generation. As the local BA, PNM constantly communicates with neighboring BAs and the WECC Reliability Coordinator. 71

84 Reviewing Existing System Resources PNM IRP Intermittent renewable generation has impacts on PNM s ability to provide regulation and frequency response services within PNM s BA. These impacts will likely need to be addressed in the future IRP process. Details on the integration of variable energy resources (VER) can be located in Appendix C of this document. 72

85 Forecasting System Loads PNM IRP Reference IRP Rule section D, Current Load Forecast. 8. FORECASTING SYSTEM LOADS OVERVIEW PNM has shortterm and longterm needs for resources that will provide capacity and energy to PNM customers. PNM serves about 502,970 electricity customers statewide, as shown on the service territory following map. In the shortterm, PNM faces growing peak demand while in the longterm, PNM must serve future system loads, maintain system reserve margins and incorporate progressively higher levels of EE and renewable energy for compliance. This section reviews historical loads and discusses the methodology used to forecast low, middle, and high loads, depending on a range of potential conditions. FIGURE 81. PNM S ELECTRIC SERVICE TERRITORY MAP 73

86 Forecasting System Loads PNM IRP SYSTEM LOAD FORECAST For this IRP, PNM developed a load forecast based on the current load characteristics and projected economic data for the service territory. After discussion with the IRP Working Group, this forecast was labeled the mid load forecast sensitivity and corresponds to the basecase forecast as required in the IRP rule. In addition, PNM collaborated with the IRP Working Group to develop a low load forecast and a high load forecast sensitivity that incorporated various aspects of forecast uncertainty, such as accelerated economic growth, building code changes, and price elasticity. Each set of input assumptions is used to create a retail energy sales forecast. Estimated load factors by class are then applied to class energy sales forecasts to produce the overall peak demand forecast. The load forecast scenarios discussed in the following sections encompass both a peak demand forecast and the energy sales forecast on which that peak demand is based. METHODOLOGY PNM uses a statisticalbased time series modeling to prepare its load forecasts, and includes known customer growth and nearterm impacts of growing economic activity in PNM's service area This methodology reflects actual growth in customer loads over time. The forecast includes energy, customers, and peak demand and comprises three parts: a forecast of retail loads, a forecast of existing firm wholesale customers, and a forecast of distribution and transmission losses. Although the results of PNM s retail forecast are reported by FERC customer class, the forecast is actually prepared at the PNM rate class level and is further broken down by operating division. The FERC classes divide customers by type, while PNM rate classes correspond to the PNM rate schedules under which customers take service. For example, residential customers may take service under either of two PNM rate schedules. Similarly, commercial and industrial customers take service under one of several PNM rate schedules, which are usually based on the amount of energy the customer uses each month or the customer s peak demand. PNM s retail electric service territory comprises ten operating divisions corresponding to ten geographic areas: Albuquerque, Valencia County, Sandoval, East Mountain, Santa Fe, Las Vegas, Clayton, Deming, Southwestern New Mexico (Lordsburg, Silver City) and Eastern New Mexico (Alamogordo, Ruidoso). Energy usage varies based upon geography, customer mix, and climate. Recognition of these differences is important in preparing load forecasts. In 2010, residential sales were 37% of total retail sales, commercial sales were 44% and industrial sales were 16%. The remaining three FERC classes (other public authorities, street lighting, and interdepartmental, usually summarized as Other ) represented only about 3% of retail sales as shown in Figure

87 Forecasting System Loads PNM IRP FIGURE 82. TOTAL RETAIL SALES BY FERC CLASSES The residential energy sales forecast is based on forecasts of growth in number of customers combined with forecasts of percustomer usage. The forecast of energy sales equals the forecast of the number of customers multiplied by the forecast usage per customer. Separate forecasts are prepared for each of PNM s two residential rate schedules, and by PNM division based on statistical analyses of historical growth in numbers of customers and usage per customer, combined with exogenously forecasted (generally by external sources) macroeconomic variables. Since separate forecasts are prepared by operating division, differences in customer growth, as well as changes in usage among divisions are reflected in the 20year load forecast. The customer equation captures the growth in number of customers over time. Population forecasts from the Bureau of Business and Economic Research (BBER) at the University of New Mexico were used to determine growth rates for residential customers. This population forecast is prepared at the county level. PNM then matches its operating divisions with the appropriate county for population growth. Using county data allows PNM s forecast to capture changes in customer mix, as well as the rural to urban migration experienced within the state in recent decades, that would not be captured using a state level population forecast. PNM s service territory covers a range of different climates from cold winter conditions in Las Vegas to dry hot summers in Deming. These differences mean that usage often varies substantially between operating division, so it is important for PNM to forecast usage at the level of operating division as well. The usage equation captures seasonal differences within a year, responses to weather, and changes in usage patterns over time that result from lifestyle changes, price and other factors. The usepercustomer forecast assumes normal weather derived from a 10year average of heating and cooling degreedays, which for purposes of this forecast, covers the years 2000 to The FERC commercial class contains several PNM rate classes. The Small Power and General Power classes were forecast the same way as the two residential rate classes: in the aggregate, and by division, combining separate forecasts of numbers of customers and per customer usage. PNM uses unemployment estimates from BBER as an input in the commercial customer forecast equation to help capture economic conditions. Larger customers within the commercial class were forecast differently. Except for those in the Albuquerque division, Large Power customers (Rate 4B) were 75

88 Forecasting System Loads PNM IRP forecast on an individual basis. Routine contact with these customers provides updates on their growth expectations and identifies new large customers that are anticipated to begin taking service in the forecast period. Within the Albuquerque division, Large Power customers were forecast as a group because their large number of approximately 135, making it impractical to forecast them on an individual customer basis. The forecast for all Rate 15B customers, within and outside of Albuquerque, was prepared on an individual customer basis. PNM serves about 275 industrial customers, the largest 40 constituting the vast majority of energy sales to industrial customers. These largest 40 industrial customers receive service under five rates (i.e., Rate Schedules 4B, 5B, 14B, 17B, and 30B.). The forecasts for these customers were based on information provided by direct contact with the customers in the same manner as the forecasts for Large Power customers in the commercial class. PNM, through its quarterly update process, continually evaluates the forecasts for large customers. Forecasts for the remaining industrial customers, those served under either Small Power or General Power rate schedules, were prepared in the same way as the forecasts for their counterparts in the small commercial class, by aggregating all customers within a rate class. The Other Public Authorities class within the Other retail category (i.e., the largest component), is expected to continue to increase in energy sales due to large water pumping loads in Albuquerque and Santa Fe related to the San JuanChama Drinking Water Project. Albuquerque Bernalillo County Water Utility Authority anticipates that this project will ultimately provide up to 90% of the metropolitan area s future water. PNM prepared separate load forecasts for three firm wholesale customers, the City of Gallup, the City of Aztec and Navopache Electric Cooperative, using statistical analyses of historical growth in energy sales, which captured seasonal differences within a year, responses to weather, and changes in usage patterns over time. Estimates of energy and demand losses for the transmission system were prepared by PNM s Transmission Development and Contracts Department. Energy and demand loss estimates for the distribution system were based on studies prepared by PNM s Distribution Planning Department. HISTORICAL COMPARISON OF LOAD FORECAST IRP Rule D.3(b) requires a comparison of the annual forecast of coincident peak demand and energy sales to the actual coincident peak demand and energy sales for the previous four years. With the exception of 2009, PNM's forecasts prepared in 2005 through 2009 (for the 2006 to 2010 Long Range Plans) tended to underforecast system peak demands. A few factors have played an important role in increasing forecasting variances. The extreme weather faced in the summer of 2010 caused the understatement of peak load to be quite dramatic. PNM uses a tenyear weather normal versus a 30year normal for its weather normalization to better capture recent warming trends, but extreme weather conditions are often difficult to predict. Load factor is also important. PNM has seen a continuation of the deteriorating load factor reported in the 2008 IRP for both the total system and the retail portion of PNM s load. Actual and weather 76

89 Forecasting System Loads PNM IRP normalized system load factors are presented in Table 111.The retail load factor in 2010 was close to 60%, a significant decrease from averages of around 63% seen in the early 2000 s. Deterioration of load factor is difficult to predict for the forecast period. While recent history would infer continuing deterioration, PNM s demand response programs shave peak demand, while rate structure encourages load shifting from onpeak hours to offpeak hours. These programs and rate structure are designed to encourage increases in load factor, or mitigate decreasing load factors. The conflict between the recent history (decreasing load factors) and increasing program design (to encourage increases in load factor) creates some future uncertainty. For this reason, PNM uses recent history to predict load factor without overlaying a trend (either upward or downward). The same load factor is used in each of the forecast scenarios. The historical load forecasts compared to actual load are shown in Table 81. In this table, the columns represent forecast cycle and the rows represent the year forecasted. For example, column 2006 row 2009 represents 2009 s demand as forecasted in TABLE 81. PNM SYSTEM PEAK DEMAND AND ENERGY COMPARISON (WEATHERNORMALIZED) Peak Demand MW Actual Weather Normalized Actual ,703 1,786 1, ,771 1,853 1,866 1, ,807 1,909 1,909 1,838 1, ,852 1,954 1,951 1,870 1,866 1, ,892 1,990 1,993 1,899 1,896 1,973 1,938 Weather Energy Sales GWh Actual Normalized Actual ,164 9,198 9, ,632 9,789 9,495 9, ,916 10,076 9,902 9,450 9, ,132 10,300 10,186 9,762 9,237 9, ,352 10,524 10,387 9,921 9,351 9,456 9,373 LOW LOAD FORECAST The low load forecast represents a combination of a lingering recession followed by slower economic growth for the out years. The low load forecast was partially driven by the DoubleDip Recession scenario presented in the August 2010 quarterly FORUNM economic forecast by UNM s Bureau of Business and Economic Research. This analysis was presented with a 25% probability and predicts a second dip related to the recent recession in 2011, which is characterized by high unemployment, a prolonged recession in housing as access to credit is limited, and weak consumer durable purchases. The impact of this scenario to PNM s forecast is primarily in the commercial sector, where lingering high unemployment as the new norm will slow commercial customer growth. 77

90 Forecasting System Loads PNM IRP The low sensitivity also restricts growth in use per customer for both residential and commercial customers. This can be attributed to larger than expected efficiency gains and/or increased response to price increases. Finally, the industrial sector is altered by assuming decreases of 1.5% per year in industrial energy sales. This adjustment corresponds with one medium sized industrial customer leaving the system per year. MID LOAD FORECAST PNM developed a base forecast, or mid load forecast, using normalized weather and BBER s base scenario for projected economic conditions. The base scenario of the economic forecast predicts the recent recession coming to an end late in 2010, with a slow climb back to normal over the following years. As with the pessimistic economic scenario described in the low load forecast, the base also accounts for the new norm in unemployment being significantly higher than New Mexico unemployment rates in recent decades. PNM s base load forecast shows moderate residential and commercial customer increases, driven by population growth, as the New Mexico economy moves past the recent recession. However, it does not climb to some of the higher growth rates seen in the 1990 s for the service area. Use per customer flattens out due to price response and conservation. Lastly, there is continuing increase in energy sales in the Other Public Authorities class as a result of large water pumping loads in the Albuquerque and Santa Fe areas. Note that while some EE gains are inherent in the historical data, for the IRP process, incremental gains in EE programs have been treated as a separate component. Changes in use per customer, including these programs, are likely negative, depending upon the saturation sensitivity chosen for PNM s EE program. HIGH LOAD FORECAST The high load forecast represents strong, sustained economic and population growth in the service territory. The IRP Working Group focused on the importance of using a broad range of forecast sensitivities to obtain the most diverse output scenarios on resource mix. To do this, the group raised the high level forecast to include population growth rates similar to the high growth rates seen in the mid1990s. To correspond with the idea of migration to the service area, likely influenced by job growth and strong economic conditions, unemployment rates were also lowered. Consistent with increased job opportunities, this forecast also includes increases in industrial energy sales of 1.5% per year, approximately the size of one medium sized industrial customer per year joining PNM s service territory. This scenario also includes a slight uptick in use per customer (before the impact of EE programs) which corresponds to increased appliance saturation and penetration of refrigerated air conditioning that is popular in new housing units. Average 30year growth rates for the three load forecast sensitivities are summarized in Table Note that all forecast scenarios presented here predict slowed growth compared to the baseline presented in the 2008 IRP. This expectation is due, in large part, to the economic downturn in recent years, as well as an increasing public concern for energy conservation. The adoption of plans for increased efficiency gains, such as building code revisions, will accomplish changes above and beyond those directly related to PNM s EE programs. Using multiple load forecasts improves the planning process because it provides PNM and stakeholders with the ability to evaluate the impact of risks associated with the variables of the load forecast on the portfolio options. The peak demand forecast is especially important for resource 78

91 Forecasting System Loads PNM IRP planning because it dictates reserve margin. It is important to note that while PNM is a summerpeaking utility, the winter peak is generally 8085% of summer peak. This may influence timing decisions for resource additions because a resource may need to be available not only for the next year s summer peak, but also for the prior winter peak. Figure 83 provides a comparison of the peak demand and forecast sensitivities. TABLE 82. LOAD FORECAST GROWTH RATES WITHOUT ENERGY EFFICIENCY Low Mid High Residential Sector Residential Customers 1.0% 1.2% 1.6% Residential Use Per Customer 0.3% 0.3% 0.9% Residential Energy Sales 0.7% 1.5% 2.5% Commercial Sector Commercial Customers 0.7% 0.9% 1.0% Commercial Energy Sales 0.7% 1.2% 1.5% Industrial Sector Industrial Energy Sales 0.9% 0.1% 1.1% Retail Sector Retail Energy Sales 0.5% 1.2% 1.9% Peak Demand System Peak Demand 0.5% 1.1% 1.7% FIGURE 83. COMPARISON OF PNM FORECAST PEAK DEMAND FOR ELECTRICITY 3,500 3,273 3,000 2,751 (MW) 2,500 2,000 2,309 1,500 1,000 High Sensitivity Mid Sensitivity Low Sensitivity 79

92 Forecasting System Loads PNM IRP PLUGIN ELECTRIC VEHICLES (PEV) Electric vehicles are gaining increasing attention as the national and global economies look for solutions to reduce total carbon emissions, including those produced by traditional petroleumpowered vehicles. Depending upon the penetration levels of the electric vehicle, electric utilities worldwide could experience a large and rapid change in the demand and energy needs of enduse customers beyond what is included in PNM s base forecast. Because electric vehicles have the potential to significantly impact electric demand and energy usage, these potential impacts should be quantified as best as possible and considered when developing future utility infrastructure plans. Forecasts for the penetration of electric vehicles differ widely among industry players. The Obama Administration set a goal to achieve a million PEVs within five years following the creation of incentives which accelerated the awareness of PEVs. This, mirrored with availability of PEVs, creates a market that compels PNM to assess the possible energy needs if PEVs are widely adopted. To determine a forecast for the number of electric vehicles that PNM customers would own and operate, and thus the amount of additional demand and energy that PNM can expect from various combinations of assumptions, it is necessary to gather the population estimates for the service territories of PNM over the next 20 years. This information was gathered from the most recent U.S. Census performed in The 2010 U.S. Census registered the population of New Mexico at 1,980,225, and the current 2011 projected population for PNM service territory is 1,145,440. Table 83 lists the New Mexico counties that PNM serves and their calculated population projections through Population numbers were further adjusted to remove children under the age of 15, to reflect the potential ageappropriate market population for PEVs. TABLE 83. CALCULATED MARKET POPULATION BY COUNTY New Mexico Total 1,980,225 2,041,539 Bernalillo County 632, ,586 Grant County 29,854 30,940 Hidalgo County 4,971 5,152 Lincoln County 20,892 21,651 Luna County 27,137 28,124 Otero County 63,459 65,767 Sandoval County 118, ,791 San Miguel County 28,805 29,852 Santa Fe County 143, ,928 Union County 3,812 3,950 Valencia County 71,737 74,346 Total Project Population in PNM ST 1,145,440 1,187,087 A March 2010 study by KEMA, a leading authority in energy consulting, projected three separate adoption scenarios (slow, target, and fast). PNM assumed an aggressive PEV adoption rate to consider a bestcase scenario to capture energy demand and usage. PNM applied the penetration rates for the baseline of 1.9 cars per 1000 vehicle registrants in the PNM service territory, to 80

93 Forecasting System Loads PNM IRP generate an average estimate for PEVs. PNM then developed a range of potential market penetrations for the PEVs being considered using KEMA s market phases: (1) 3% for initial phase, (2) 6% for market and (3) 25% under market maturity. Assuming an average estimate of 6,000 kwh per year consumption rate for PEVs, the resulting energy consumption is shown in Table 84. The actual impact of PEVs may be lower than projected, given local sales figures compared to national sales figures to date; however, this forecast is developed to examine the effects if PEVs were extensively available and adopted in New Mexico. TABLE 84. ELECTRIC VEHICLES FORECAST Initial Market Entry Market Development & Growth Mature Market Deployment Adjusted PNM ST Population (000s) Penetration Rate (cars/1000 registrants) Growth Rate of Penetration Factor # of PEV kwh/yr consumed per vehicle (PEV) Total MWh/yr consumed by PEV Total MWh/day % 1,763 6,000 10, % 1,827 6,000 10, % 1,948 6,000 11, % 2,078 6,000 12, % 2,228 6,000 13, % 2,384 6,000 14, % 2,552 6,000 15, % 3,221 6,000 19, % 4,065 6,000 24, % 5,173 6,000 31, % 6,541 6,000 39, , % 8,271 6,000 49, , % 10,458 6,000 62, , % 13,223 6,000 79, , % 16,881 6, , , % 21,334 6, , , % 26,960 6, , , % 34,070 6, , , % 43,055 6, , , % 54,913 6, , The impact that electric vehicles would have on PNM s load is calculated using the vehicle energy use profiles. A reasonable initial approximation of vehicle charging is based on a joint study by Electric Power Research Institute (EPRI) and the National Resource Defense Council, which assumed the highest charging loads for electric vehicle transportation would occur during late night and early morning hours (see Table 115). Modest loads, the study presumes would occur for middaytime public or workplace charging. The lowest charging times of the day would occur during typical commuting times. PNM used this approach to estimate the load profile of PEVs. It is recognized that charging patterns can significantly vary depending upon actual consumer charging behaviors, which will be a direct result of the availability of public charging infrastructure 81

94 Forecasting System Loads PNM IRP development. Although this forecast is weighted towards offpeak usage, PNM assumed that timeofuse rates would likely be implemented to encourage offpeak charging of vehicles as not to exacerbate the strained transmission and generation situation of utilities during summer and winter peak times. TABLE 85. CHARGING PROFILE FOR PEVS Hour of Day Charging Fraction % % 3 9.0% 4 6.0% 5 4.0% 6 2.0% 7 1.0% 8 0.5% 9 0.5% % % % % % % % % % % % % % % % 100% PROJECTED LOADS WITH EXISTING RESOURCES Through the planning period, existing resources decline due primarily to the termination of supply contracts, while projected customer demand is expected to increase. PNM needs to add additional resources to meet customer needs and maintain reserve margin requirements. Figure 114 illustrates the currently projected customer demand and the existing jurisdictional resources to meet that demand. It shows that new resources are needed prior to 2017 peak to maintain the targeted reserve margin of 13% as mandated by the NMPRC. The figure is based on the L&R data shown in Table 86. The L&R table shows the existing resources, with no resources added, and the midload demand forecast documented in this plan, as required by IRP Rule

95 Forecasting System Loads PNM IRP TABLE 86. LOAD AND RESOURCES TABLE WITH MIDLOAD FORECAST AND EXISTING RESOURCES PUBLIC SERVICE COMPANY OF NEW MEXICO Total Load and Resource Projection (MW) for Summer Peak LRP BASE SCENARIO AOP Forecast Peak Demand 1,972 1,992 2,033 2,069 2,107 2,138 2,178 2,214 2,251 2,289 Projected Customer Sited PV (4) (6) (7) (9) (11) (12) (13) (13) (13) (13) Projected Energy Efficiency (17) (29) (41) (56) (68) (80) (88) (97) (107) (115) Net System Peak Demand Duty FirmDispatchable Resources Cycle Four Corners B coal Palo Verde Units 1 & 2 B nuclear Future Palo Verde Acquisitions B nuclear San Juan 1, 2, 3, 4 B coal Reeves 1, 2, 3 P natural gas Afton CC I natural gas Luna I natural gas Lordsburg P natural gas Valencia (Purchase) P natural gas DeltaPerson (Purchase) P natural gas Demand Response Programs (Contract) Future Demand Response (Contract) Total 2,279 2,284 2,290 2,296 2,296 2,296 2,296 2,296 2,296 2,296 Firm Reserve Margin (MW) Firm Reserve Margin (%) 15.6% 14.7% 12.6% 10.9% 9.0% 7.4% 5.4% 3.7% 2.0% 0.3% NonFirm, Intermittent Resources NM Wind Energy Center (Purchase) wind Future Renewable Additions Approved Total Reserve Margin including nonfirm (MW) Reserve Margin including nonfirm (%) 17.7% 17.8% 16.5% 15.6% 14.3% 13.3% 11.6% 10.2% 8.8% 7.3% The firm reserve margin is the difference between the forecast peak demand and the sum of the firmdispatchable resources. The nonfirm reserve margin is the difference between the net system peak demand and the sum of the firm and nonfirm resources. 83

96 Forecasting System Loads PNM IRP FIGURE 84. PROPOSED MIDLOAD FORECAST WITH EXISTING RESOURCES LRP Base Scenario: Mid Load Growth, No Generation Additions Peak Demand Reserve Margin Firm Resources NonFirm 3,000 2,500 2,000 MW 1,500 1, TABLE 87. PNM SYSTEM LOAD FACTOR COMPARISON SUMMARY Actual Weather Normalized Actual % 63.57% % 62.07% % 60.09% % 61.40% % 59.31% ENERGY EFFICIENCY ENERGY EFFICIENCY COMPLIANCE In 2010, PNM s approved EE programs have resulted in 134 GWh of energy savings. This exceeds the projection of 87 GWh from the 2008 IRP by 47 GWh or 54%. Current programs are forecasted to meet the 2014 minimum of 411 GWh, with new programs totaling 593 GWh needed to meet the 822 MWh minimum in The graph in Figure 115 shows the amounts of EE needed to meet EUEA goals, along with PNM s existing approved programs. Because EE thresholds are based on historical actual usage, the 84

97 Forecasting System Loads PNM IRP required amount of EE does not change with the load forecast. However, the potential for EE programs increases as load increases. FIGURE 85. PROJECTED ENERGY EFFICIENCY NEEDED TO MEET MINIMUM COMPLIANCE Accounting for EE programs in the load forecast is an emerging issue impacting PNM s forecasting group. This element is fairly new to the company, and as the program effects grow, they will become increasingly important during the forecasting process. For this IRP, PNM changed its methodology to include only incremental gains over 2009 (in energy efficiency) rather than program totals in the twenty year IRP load forecast. PNM expects that as these programs mature, the actual energy savings will become increasingly embedded into historical sales data and therefore, PNM only reports the incremental gains for this IRP report. This methodology may change as PNM gains more information and experience with the programs to better predict how the energy and peak savings will play a role in load forecasting in the future. PNM is actively exploring all methodologies by industry standards and other utilities to determine the best approach and as a result, may change how energy efficiency is treated in the load forecast after this filing. RENEWABLE ENERGY COMPLIANCE The RPS Rule NMAC sets forth the requirements for renewable energy resources. The following table compares the projected mix of renewable energy sources to the RPS requirements under the midload forecast, along with approved EE programs. 85

98 Forecasting System Loads PNM IRP PNM needs additional renewable energy resources beginning in By yearend 2027, PNM must add resources that will provide a minimum total of 2,400 GWh/year of renewable energy to meet the RPS energy requirements. The Rule specifies the following: Renewables must be diversified to ensure no less than 20% of the renewable portfolio is met using wind energy, 20% solar, and 10% other renewable technologies No less than 1.5% of the renewable portfolio must be met through renewable DG from , and 3% thereafter To meet RPS requirements in 2012 and beyond, PNM issued a Request for Proposal (RFP) on April 8, 2011 for renewable energy and RECs, as defined in Rule 572, up to 360,000 MWh per year. The proposals may provide energy and RECs for energy delivered to PNM, or for qualifying RECs. Proposals will be evaluated based upon a host of criteria which includes price, qualifications, size, location and engineering plan. Finalists will be further evaluated on credit quality, price and nonprice factors, and the greatest value to PNM and its customers. The deadline for proposal submittal was on June, and final results of the RFP will not be known prior to the filing of this IRP. Initial cataloguing of bids recorded over 340 bids from 80 different bidders. Proposals submitted represented a range of renewable resources, including biomass, geothermal, wind, solar and hydro. Final results of the RFP process will be filed with the NMPRC in PNM s 2012 Renewable Energy Procurement Plan. 86

99 Supply Side Fuels Assessment PNM IRP Biomass fuel must be available for the life of the plant, must be sustainably harvested, and must be located in proximity to the biomass facility. Biomass could fuel up to four 25 MW facilities. 9. SUPPLY SIDE FUELS ASSESSMENT PNM considers the availability of fuel when selecting potential future resource additions. While New Mexico is fortunate to have access to diverse fuel resources, fuel availability may restrict the development of some technologies. This section provides an overview of the relative availability of fuel resources and how they impact future resource options for the IRP. In addition, forecasts for those fuel sources considered viable are discussed. BIOGAS According to information supplied by the Dairy Producers of New Mexico and Ag2Energy, New Mexico ranks third in the U.S. in ability to harvest biogas from dairy farms. When organic matter from dairy cows decomposes anaerobically, biogas is produced. Biogas, similar in nature to natural gas because both are primarily methane, can be collected and purified to meet DOT pipeline standards and be a cost effective renewable fuel alternative that can be injected into natural gas pipelines. Biogas could potentially offset the need for fossil fuels in existing natural gasfired generation facilities. Although other agriculture waste products can be converted to biogas, dairy waste is the largest biogas resource in New Mexico. Conversion of the dairy waste could offset natural gas and generate between megawatts of electricity. BIOMASS In 2005, PNM issued the PNM Biomass Assessment: Status Report (the Biomass Study ) that documented a detailed biomass assessment for New Mexico. The Biomass Study considered sites for constructing a biomass facility between 2535 megawatts. Key elements to biomass fuel supply are: the fuel supply must be available for the life of the plant (30 years and beyond), sustainable harvesting principles must be followed, and the plant must be sited in proximity to the fuel source. In Case UT, biomass developers discussed the feasibility of five to seven projects within the state, however, due to lack of biomass facilities that have been developed in the state of NM, PNM eliminated biomass facilities as a potential resource. Accessible geothermal fuel is most abundant in the SW region of NM. Geothermal could fuel up to three 7.5 MW facilities. GEOTHERMAL Although geothermal resources exist within New Mexico, the feasibility of developing this source for electricity production is not fully known. In Daniel Fleischmann s September 2006 report, Geothermal Resource Development Needs in New Mexico (the Geothermal Study ) the most likely development of a geothermal resource would be between 510 megawatts. Besides the Valles Caldera National 87

100 Supply Side Fuels Assessment PNM IRP Reserve location (which has contentious development potential), the next best geothermal resource potential in New Mexico is in the southwestern area of the State. Until more extensive exploration is done and a site is developed, PNM considered geothermal could aid in meeting RPS scenarios that consider diversity compliance. Wind potential is the greatest in the eastern region of NM. Although the wind resource is unlimited, transmission system issues must be overcome to maximize wind energy in NM. SOLAR New Mexico s abundant supply of solar irradiance makes this a potentially attractive energy resource for PNM. This, combined with unprecedented subsidies, modular nature, and current oversupply of PV panels on the market, are helping to improve solar technologies attractiveness. Although all regions of New Mexico can produce solar energy, the New Mexico Renewable Resource Map (see Figure 9 1) shows that the regions with the highest annual Normal Direct Irradiance (NDI) are located in the southwest corner of the state. Transmission Solar radiation potential is the greatest in the SW region of NM, but the value of solar generation is the highest in the north. Solar energy could fuel a variety of solar facilities such as centralized solar, solar hybrid and largescale solar PV. resources are limited, and the ability to move the energy to loads in NNM would require extensive transmission upgrades or wheeling charges to be added. The addition of wheeling charges could cause this resource to increase in costs in comparison to other resources thereby negating any benefits solar receives from federal and state incentives. The most preferable sites would be near to NNM load, which would reduce incurred losses associated with transmitting energy to load. WIND Wind is another abundant resource in New Mexico. Wind generation is most economical in areas with the higher wind power density, primarily in the eastern region of New Mexico. Wind, like solar, benefits from the federal and state subsidies that make this least cost renewable resource even more attractive from a cost standpoint. Although no limits are placed on the development of wind facilities based on resource availability, PNM restricts the number of facilities due to lack of available resources (load following generators such as gas turbines) needed to maintain a balanced system due to the intermittency of this resource. 88

101 Supply Side Fuels Assessment PNM IRP FIGURE 91. MAP OF NEW MEXICO RENEWABLE ENERGY RESOURCE POTENTIAL 89

102 Supply Side Fuels Assessment PNM IRP SUPPLYSIDE FUELS ASSESSMENT URANIUM Nuclear fuel is obtained through longterm supply contracts that move uranium through a global supply chain. Creating the fuel rods for a nuclear power plant is a complicated process. There are four components to the nuclear fuel cycle: concentrates, conversion, enrichment and fabrication. Concentrates are produced through mining and milling uranium ore to produce uranium oxide. Uranium mining and milling operations are located worldwide, with significant supplies of concentrates coming from Canada, Australia and Kazakhstan. The price for concentrates spiked in 2007, which resulted in increased interest in reestablishing uranium mining in New Mexico. Figure 92 shows uranium deposits within New Mexico. In the conversion stage, the uranium is converted to a gaseous form. Enrichment refers to increasing the concentration of U235 in the gas. Finally, the gaseous uranium is fabricated into pellets, which are then inserted into the rods that fuel the nuclear reactor. There are very few facilities that provide conversion, enrichment and fabrication services, and those that supply PVNGS are located within the United States. Internationally, the demand for uranium is projected to rise as China, India and Russia are expected to build more than 70 reactors in the next 20 years. World demand is anticipated to exceed supply by about 10% in the next 10 years, and as a result, spot prices were on the rise until the tsunami and subsequent Fukushima Daiichi nuclear power plant incident occurred in Japan. Transactions on the spot market have decreased, as both buyers and sellers are reevaluating the market outlook in light of the crisis. It is anticipated that uranium prices will remain steady until the Fukushima Daiichi plant is fully stabilized. However, prices in the long term are expected to continue to rise as this incident is not expected to change the prospective positions of market players. Rather, it is reasoned that the Daiichi nuclear power plant incident in Japan won t change the renaissance of nuclear power, but will impact the adoption of new reactor technology that does not require cooling in the same manner. Closer to home, if the worldwide demand for uranium increases, it will impact domestic prices for new or existing nuclear power plants. As prices rise, it could spur interest in reestablishing uranium mining in New Mexico and elsewhere, which could increase the supply. The increased supply would send a signal to either stabilize prices or cause prices to fall. If a utility received necessary approvals and chose to construct a nuclear power plant, the development of the nuclear facility would not be limited by fuel supply. The fuel component of generation cost from a nuclear power plant comprises less than 10% of the overall costs. Past studies have shown that PNM can sustain twice the current fuel price before a fuel switchover occurs since nuclear generation must overcome high fixed costs (capital and O&M expenses) to be competitive with other types of baseload generation facilities. For these reasons, a high price forecast for nuclear fuel is not recommended nor was it forecasted. To simulate a proxy forecast for future nuclear fuel for new power plants as well our existing PVNGS, an estimate using the five year forecast for PVNGS was used. Beyond the five year period, fuel prices were escalated using a 2.5% per year growth fuel rate determined internally. These price projections are shown in Table

103 Supply Side Fuels Assessment PNM IRP FIGURE 92. MAP OF NEW MEXICO COAL AND URANIUM DEPOSITS 91

104 Supply Side Fuels Assessment PNM IRP COAL Of all the fossil fuels, coal is the most abundant. The United States is estimated to possess sufficient coal reserves to meet current coal consumption for electric generation for hundreds of years. Typically, coal is supplied for electric generation using one of two methods: the electric generation plant is located at the source of the coal (called a mine mouth plant), or the plant receives coal transported from one of the lcoal producing regions in the United States. The SJGS and the Four Corners Power Plant are mine mouth plants. The San Juan Mine supplies the coal used at SJGS, and the Navajo Mine supplies the coal used at Four Corners Power Plant. Both coal suppliers have provided a reliable supply of coal since SJGS and Four Corners Power Plant were built. Longterm coal supply agreements supply these plants, and in both locations, the coal reserve is expected to last well beyond the life of the coal supply agreements and the 2030 planning horizon used in this IRP. Historically, the price of coal has been stable, particularly when compared to other fossil fuels such as natural gas and oil. Generally, coal costs represent less than 29% of the overall cost to operate a new coalfired power plant. Consequently, the fuel price risks associated with coal plants are smaller than for other fossilfueled generation facilities. During this projected planning horizon, the coal contracts for the SJGS and Four Corners Power Plant expire. The Four Corners coal contract is due for renewal in 2016, and SJGS in The initial price projection from the coal mining company to APS, who operates the facility, has shown that coal prices could increase beginning in Beyond 2016, the prices have been escalated at 3.0% per year. Since negotiations with the coal mining company have not been finalized and are currently being negotiated, PNM included the most current coal price projections for this plant. PNM expects the negotiations to be completed after the filing of this IRP. For SJGS, negotiations to extend the coal supply contract after the 2018 expiration date will commence after the filing of the IRP. For this IRP, PNM assumes a contract extension through the end of the planning period at current costs. The IRP also considers new coal source generation alternatives. Rather than be captive to a mine mouth plant such as FCGS and SJGS, new coal supply is assumed to be acquired via rail. By locating next to rail, opportunities exist such that market purchases could be made to bring down the overall costs to benefit all customers. To simulate a proxy forecast for future coal prices (generic coal) for a new alternative, PNM assumed that any new coal would be sourced from the Powder River Basin (PRB). Because the PRB is vast, an estimate using Wyoming coal at high grade heating value of 8,683 Btu/lb at its current market price was used. Prices were escalated at 2.5% per year to obtain a 20 year pricing forecast. PNM included transport of the coal by rail to New Mexico to a centralized point. Price forecasts for coal are found in Table 91. NATURAL GAS The cost of natural gas as a percentage of total operating costs for a natural gas facility is generally greater than the percentage of fuel costs compared to total costs for coal or nuclear facilities. Unlike coal and nuclear, demand for natural gas due to electric generation should be expected to increase during the planning horizon for this IRP because, other than energy efficiency and renewable resources, natural gas is the only traditional fuel resource that can be brought online in the near term to supply growing electricity demand. 92

105 Supply Side Fuels Assessment PNM IRP New Mexico is home to two of the largest natural gas supply basins in North America: the San Juan Basin and the Permian Basin. As a result, the region has a robust natural gas infrastructure in place that already supplies natural gas to PNM s existing plants. The infrastructure presents several opportunities to site new plants adjacent to reliable sources of pipeline supply. Because supplies and infrastructure are already in place, the greatest consideration regarding new natural gas generation is the impact of volatile and rising natural gas prices. The emergence of shale gas as a viable fuel supply has changed the natural gas industry significantly. Natural gas produced from hydrocarbon rich shale rock formations, known as shale gas, is one of the most rapidly expanding areas in domestic gas exploration and production today. Though not a new source, advanced drilling methods and improvements in the costeffectiveness in drilling has lead shale gas to become a noteworthy event in recent years. In January 2011, the Energy Information Association reported the first increase in proved natural gas reserves since 1971, estimating that the U.S. has more than 862 trillion cubic feet (Tcf) of shale gas reserves, surpassing the 284 Tcf of proved wet gas reserves. This new estimate is projected to provide enough natural gas to supply the U.S. for the next 90 years. As a result, the prices for natural gas on market are depressed due to the speculation on abundant supplies from the shale deposits. Natural gas is traded in a very well developed market which includes pipeline delivery prices, gas prices, and financial derivatives trading. Gas has a very liquid futures market, in which buyers and sellers can contract for sales at future dates. The IRP gas forecasts were developed using a blend of New York Mercantile Exchange Price Index quotes for natural gas futures contracts for delivery at Henry Hub. Henry Hub represents the pricing point (located in Louisiana) for natural gas futures that are traded on NYMEX. Since the futures represent the best approximation for fuel pricing in the short term, the base case projections for natural gas are predicated upon these market prices which extend out to PNM used the average settlements over a three month period to create a monthly profile to reflect natural gas prices over a typical year. Since gas price forwards typically look ahead for 5 years, the price was escalated at 2.5% per annum thereafter to obtain a twenty year price forecast (see Table 91). Typical sites in NM for new generation units would most likely located near the San Juan Basin or El Paso Basin rather than Henry Hub, so a differential, referred to as swaps, for those basins should be considered. Similar to natural gas prices, settlements for swaps were collected over three months, averaged, and applied to the average price for Henry Hub, depending upon the plant location. For new options and plant located inside of Path 48, PNM assumed plants would operate using San Juan Basin natural gas. Existing plants located in the SNM Path 47 would operate using El Paso Basin gas. By 2014, GHG legislation (most likely a cap and trade program for carbon dioxide emissions) is assumed to be implemented. Since gasfired generation technologies emit roughly half of the carbon associated with coal generation, the demand for natural gas is anticipated to increase due primarily to two factors: repowering or fuel switching of utilities of existing fleet, and new generation additions to meet any future load growth. The potential for large increases in demand by the electric industry for gas, as a result of this switch from coal to gas, creates the possibility of rising gas prices. Also, since natural gas cost significantly impacts modeling results and can be volatile, it is especially important to capture a price forecast that represents the high end. Alternatively, the emergence of shale gas supplies may result in gas prices remaining at moderate levels. As a result, the IRP analyzed a wide range of gas prices. 93

106 Supply Side Fuels Assessment PNM IRP Historically, in New Mexico during the peaks of natural gas pricing, prices have been between $2/MMBtu and $12/MMBtu. To simulate a high forecast for natural gas pricing, the profile for the base natural gas case was used and a $2/MMBtu premium was added until This premium represents one standard deviation of historical natural gas fuel prices over the past 6 years. The escalation after 2016 was increased (from the 2.5% in the base gas forecast) to 3.5% per annum to capture a wider range for prices and account for increased demand on gas reserves in the longer term. The twenty year price forecast is found on Table 91. Base TABLE 91. DETAILED FUEL COST ASSUMPTIONS High Natural Gas Natural Gas SJ Coal FC Coal Generic Coal PV Fuel/ Generic Nuclear $/MMBtu $/MMBtu $/MMBtu $/MMBtu $/MMBtu $/MMBtu 2011 $ 4.08 $ 6.08 $ 2.38 $ 1.70 $ 1.90 $ $ 4.64 $ 6.64 $ 2.39 $ 1.75 $ 1.96 $ $ 4.97 $ 6.97 $ 2.53 $ 1.80 $ 2.02 $ $ 5.17 $ 7.17 $ 2.67 $ 1.87 $ 2.08 $ $ 5.35 $ 7.35 $ 2.82 $ 1.91 $ 2.14 $ $ 5.53 $ 7.53 $ 2.89 $ 2.02 $ 2.20 $ $ 5.73 $ 7.80 $ 2.98 $ 2.34 $ 2.27 $ $ 5.93 $ 8.07 $ 3.06 $ 2.39 $ 2.34 $ $ 6.14 $ 8.35 $ 3.16 $ 2.44 $ 2.41 $ $ 6.35 $ 8.65 $ 3.25 $ 2.50 $ 2.48 $ $ 6.57 $ 8.95 $ 3.35 $ 2.55 $ 2.55 $ $ 6.80 $ 9.26 $ 3.45 $ 2.61 $ 2.63 $ $ 7.04 $ 9.59 $ 3.55 $ 2.67 $ 2.71 $ $ 7.29 $ 9.92 $ 3.66 $ 2.73 $ 2.79 $ $ 7.54 $ $ 3.77 $ 2.79 $ 2.87 $ $ 7.81 $ $ 3.88 $ 2.85 $ 2.96 $ $ 8.08 $ $ 3.99 $ 2.91 $ 3.05 $ $ 8.36 $ $ 4.11 $ 2.97 $ 3.14 $ $ 8.66 $ $ 4.24 $ 3.04 $ 3.23 $ $ 8.96 $ $ 4.36 $ 3.11 $ 3.33 $ 1.10 Wind and solar resources are zerocost fuels and are omitted from this table. 94

107 Reviewing Future Resource Options PNM IRP REVIEWING FUTURE RESOURCE OPTIONS Reference IRP Rule section F, Identification of Resource Options OVERVIEW This section reviews the potential resource options that could be feasible alternatives to determine the most costeffective resource portfolio. These options are presented in the following order: demandside resources, supplyside resources (renewable, conventional, emerging technologies), DG. Each resource option includes a description of the actual resource, the modeling assumptions used to evaluate the resource, and any other attributes (such as transmission, siting or availability) that apply to a particular resource option. DEMAND SIDE RESOURCE OPTIONS This section discusses the future demandside resource options: energy efficiency forecasts, DR programs, and demand reductions through rate design. While renewable DG programs are considered demandside resources, the IRP presents the customerowned renewable DG program within the discussion of renewable resource options in Reviewing Existing System Resources section (Section 7). ENERGY EFFICIENCY PNM modeled three deployment levels of energy efficiency through the planning period. The three deployment levels are labeled as the low, middle and high levels of energy efficiency. The three levels are based on: 1. Current programs and new programs filed in Case No UT being approved by the NMPRC 2. Identifying and implementing new programs required to meet the EUEA savings requirements of 5% of 2005 Retail Sales by 2014 (411 GWh) and 10% of 2005 Retail Sales by 2020 (822 GWh) 3. Assumptions regarding market transformation and the maturation of energy efficient technologies 4. Assumptions regarding the regulatory environment in future years The scenarios presented below are based on the gross energy savings PNM is able to claim to meet the EUEA savings targets. PNM can claim 12 months of savings for every measure taken during a calendar year. The load impact due to energy efficiency is less than the annualized savings amounts that is reported, as the load impact for each measure only affects the months in which the measure was implemented. For example, a compact fluorescent bulb purchased in December through the Residential Lighting Program can be counted for twelve months of savings towards meeting the EUEA goals, but only one month of actual load savings for that year. The forecasts in this IRP represent an improvement over the forecasts in the 2008 IRP. In 2008, the energy efficiency programs were just beginning. In 2010, PNM had historical data, and newly developed 8,760 hourly load shapes to help determine energy savings and coincident peak demands. The forecasts represent PNM s best estimates of the impacts of energy efficiency over 95

108 Reviewing Future Resource Options PNM IRP time. Actual savings are subject to independent evaluation by a thirdparty measurement and verification contractor appointed by the NMPRC. The actual savings results could be different than forecasted, and PNM will use the measurement and verification results to continue to refine its forecasting methods. PNM will review the results of a statewide energy efficiency study being conducted by Global Energy Partners, LLC. The study objective is to identify potential cost effective energy efficiency and LM measures that maximize achievable energy savings. The scope of this study includes market research, saturation of EE measures, and identification of barriers to engaging in energy efficiency and DR programs. PNM will use the study results to refine design and implementation strategies for future energy efficiency and DR programs. LOW LEVEL ENERGY EFFICIENCY The low level represents the energy and demand savings based on the following assumptions: 2011: Like Middle Level Energy Efficiency, current and new programs filed 9/15/2010 in Case No UT will be approved by NMPRC : Slower growth in programs reflects potential risks such as: Lower participation in programs than forecasted Inability to identify cost effective programs Spending increases for new programs not approved by the NMPRC Changed regulatory or legislative priorities : A gradual decrease to 2010 levels will occur due to costeffective technology saturation and market transformation. Although the Low Level of Energy Efficiency does not meet the savings requirements of the EUEA in 2020 as illustrated in Figure 101; it does represent a valid scenario that should be evaluated during the planning cycle. The Low Level Energy Efficiency scenario is intended to capture the potential impact on the planned deployment of energy efficiency programs due to the various risks listed above. It is PNM s intention to propose and implement programs that will provide energy sufficient to meet or exceed the EUEA target; however, PNM has identified risks that could impact PNM s ability to achieve these goals and the Low Level Energy Efficiency scenario is intended to capture the impacts of those risks. 96

109 Reviewing Future Resource Options PNM IRP FIGURE 101. LOW LEVEL CURRENT AND NEW PROGRAMS VS. EUEA SAVINGS REQUIREMENTS , Gigawatt Hours Current Programs Future Programs Total Programs 2014 Savings Goal 2020 Savings Goal MIDDLE LEVEL ENERGY EFFICIENCY The middle level represents the energy and demand savings based on the following assumptions : Current and new programs filed 9/15/2010 in Case No UT will be approved by the NMPRC : New programs and savings targets will be developed based on achieving 2020 EUEA goal. New programs are assumed to have an effective useful life of 9 years and receive NMPRC approval : Gradual decrease in new annual savings to 2010 levels will occur due to costeffective technology saturation and market transformation. PNM believes that efficiency savings will continue to exist; however, the efficiency is reflected in the load forecast instead of through utility energy efficiency programs, generally due to enhanced codes and standards and transformed markets. Figure 101 illustrates middle level current and new energy savings programs compared to EUEA savings requirements. The blue bars represent the cumulative savings of current programs that begin decreasing in 2015 as the lifetime of the measures start to expire. As the current programs drop off, new programs represented by the green bars are forecasted to allow PNM to reach the 2020 EUEA savings goal. The red line represents the cumulative savings of the current and future programs combined. 97

110 Reviewing Future Resource Options PNM IRP FIGURE 102. MIDDLE LEVEL CURRENT AND NEW PROGRAMS VS. EUEA SAVINGS REQUIREMENTS ,000 Gigawatt Hours Current Programs Future Programs Total Programs 2014 Savings Goal 2020 Savings Goal HIGH LEVEL OF ENERGY EFFICIENCY The high level represents the energy and demand savings based on the following assumptions : Current and new programs filed 9/15/2010 in Case No UT will be approved by NMPRC : A gradual decrease to 2015 levels will occur due to costeffective technology saturation and market transformation. This is less of a decline than the middle case and was considered based on feedback from the IRP Working Group. Figure 103 illustrates that high level current and new program savings compared to EUEA savings requirements. As in the two previous graphs, the blue bars represent the cumulative savings of current programs and the green bars represent savings from new programs. The red line represents the cumulative savings of the current and future programs combined and shows that under the high scenario PNM will achieve the 2020 EUEA savings goal. 98

111 Reviewing Future Resource Options PNM IRP FIGURE 103. HIGH LEVEL CURRENT AND NEW PROGRAMS VS. EUEA SAVINGS REQUIREMENTS , Gigawatt Hours Current Programs Future Programs Total Programs 2014 Savings Goal 2020 Savings Goal PNM believes that the Middle Level of energy efficiency is the most realistic and achievable case. This case represents aggressive deployment of Energy Efficiency programs. PNM is committed to meeting the 2020 EUEA goal, but believes finding enough new costeffective programs to meet the goal will be a challenge. The budgets required to develop these programs by 2020 will require large increases every year, up to about $50 million in 2020, which represents over a 300% increase from the 2010 level of $16.6 million. All three of the energy efficiency scenarios included in the 2010 IRP include increasing levels of forecasted energy savings from new energy efficiency programs that must be approved by the NMPRC. Achievement of PNM s energy efficiency goals is dependent on the continued support and approval of the NMPRC. Figure 104 illustrates the actual and projected annual costs associated with the various levels of energy efficiency program deployment. The costs for years 2008 through 2010 are based on actual costs of PNM programs. The costs for 2011 through 2030 are projections determined by scaling the current costs to the projected future savings amounts. 99

112 Reviewing Future Resource Options PNM IRP $55.0 FIGURE 104. AGGRESSIVE DEPLOYMENT OF ENERGY EFFICIENCY PROGRAMS $50.0 $45.0 $40.0 $35.0 $ Millions $30.0 $25.0 $20.0 $15.0 $10.0 $5.0 $ High Case Low Case MidCase Demand Response Programs Approved demandside programs include DR programs for residential, commercial, and industrial customers. The existing resource section discusses the estimated impact of these programs. PNM believes that these are aggressive programs that may not be capable of expanding beyond their estimated impacts. For this reason, PNM is not initially modeling new DR programs as a future resource option; however, PNM did look at the portfolio impact if additional DR is available. PNM will continue to seek more DR opportunities should the existing programs exceed projections (see DR program results in Section 7) and customer growth continues. In addition, PNM will also consider other customer programs that result in shifting customer demand to offpeak periods. For example, offering incentives to customers to install thermal energy storage systems could permanently move cooling loads to offpeak times. New programs such as thermal energy storage would be subject to analysis of cost effectiveness and the potential customer market for the technology. REDUCTION IN SYSTEM DEMAND AND ENERGY Existing demandside programs include a reduction in overall system demand and energy, and a reduction in the system distribution losses. When calculating the planning reserve margin, PNM 100

113 Reviewing Future Resource Options PNM IRP considers demandside resource capacity and associated losses as a decrement to the system load as shown in Table 101. TABLE 101. DISTRIBUTION AND SUBSTATION LOSSES BY DEMAND AND ENERGY Loss Type Demand Energy Distribution Losses 5.36% 3.53% Substation Losses 0.69% 0.59% To account for losses, the demandside resources are increased in both total annual energy, and in contribution to peak capacity by the most recently calculated threeyear system average for distribution and substation losses. Table 102 shows the reduction in peak demand (in megawatts) and energy use (in gigawatt hours) by year for energy efficiency and DR programs, prior to loss adjustments. TABLE 102. LOAD REDUCTION IN PEAK DEMAND AND ENERGY USE FOR EE AND DR PROGRAMS IRP Scenario Units Low Case EE GWh Low Case EE MW Low Case DR MW Low Case Budget $M $ 23 $ 22 $ 20 $ 20 $ 22 $ 24 $ 27 $ 31 $ 32 $ 32 Mid Case EE GWh Mid Case EE MW Mid Case DR MW Mid Case Budget $M $ 23 $ 25 $ 27 $ 27 $ 27 $ 37 $ 36 $ 38 $ 40 $ 51 High Case EE GWh High Case EE MW High Case DR MW High Case Budget $M $ 23 $ 25 $ 27 $ 27 $ 27 $ 37 $ 36 $ 38 $ 40 $ 51 IRP Scenario Units Low Case EE GWh Low Case EE MW Low Case DR MW Low Case Budget $M $ 29 $ 27 $ 26 $ 25 $ 24 $ 22 $ 23 $ 23 $ 23 $ 24 Mid Case EE GWh Mid Case EE MW Mid Case DR MW Mid Case Budget $M $ 41 $ 37 $ 34 $ 30 $ 26 $ 22 $ 23 $ 23 $ 23 $ 24 High Case EE GWh High Case EE MW High Case DR MW High Case Budget $M $ 47 $ 45 $ 42 $ 41 $ 39 $ 38 $ 36 $ 34 $ 35 $

114 Reviewing Future Resource Options PNM IRP DEMAND REDUCTIONS THROUGH RATE DESIGN PNM s set of existing rates and tariffs incorporate LM and load shifting concepts. PNM assumes these will continue throughout the IRP planning period and incorporates them in the load forecast. Since PNM already offers a comprehensive set of rates, changes for IRP modeling at this time are not necessary; however, PNM will continue to monitor whether pricing can be used to optimize future resource use and selection. Some factors that may warrant changes include: CO2 costs, changes to typical use pattern, electric vehicles, and smart metering. PNM will continue its distributed renewable generation programs at prices or pricing mechanism authorized by the NMPRC. The expansion of the energy efficiency programs will have an impact on Rider 16 Energy Efficiency, since program costs will likely increase as well as corresponding cost recovery. Supply Side Resources To develop the list of potential supply side resource options, PNM and the IRP Working Group considered all feasible resources over the course of several Working Group meetings. Starting from a base of all possible resources, PNM and the IRP Working Group eliminated technologies that were not feasible in New Mexico (such as modular nuclear power plants) due to their early development stage. The list of each potential resource options, its feasibility to be implemented during the planning horizon, and fuel assessment are presented in this section. DISTRIBUTED GENERATION AND ENERGY STORAGE TECHNOLOGIES During the IRP process, the IRP Working Group discussed DG and energy storage solutions that could ease transmission congestion. Specifically, utility scale energy storage (batteries, compressed air), DG technologies (batteries, fuel cells and microturbines) and DG technologies coupled with storage were discussed. These are discussed below. MICROTURBINES AND FUEL CELLS For some applications, microturbines can be an appropriate option for DG, however, technical issues remain that prevent this technology from achieving high penetration. Compared to large combined cycle plants with efficiency near 50%, efficiency for microturbines is between 2328%. Noise is an issue for urban sites, and installations often require noise abating enclosures. NO x emissions range from 9 to 25 ppmv, depending upon the manufacturer and the model. In some applications, such as landfill gas or specific combined heat and power sites, microturbines have proven economically beneficial. Capital costs are projected to decrease if market demand for DG increases. Fuel cells offer reliability and flexibility in addition to low or no emissions. Phosphoric acid fuel cells (PAFC) are commercially available, but cost inhibits wide spread use. Solid oxide fuel cells (SOFC) are commercially available but their high operating temperatures can make them slow to start and drive up maintenance costs. The initial capital costs can also be prohibitive, so to date, many installations have been subsidized by tax credits. While there are diverse applications that could benefit from fuel cell energy, dramatic cost reductions would be required for this technology to achieve higher penetration rates. 102

115 Reviewing Future Resource Options PNM IRP ENERGY STORAGE Many drivers are pushing development and adoption of energy storage in the electricity grid. One driver is the intermittency of renewable generation resources that are increasingly being placed on the grid due to dictates of RPS. Other drivers included the need to defer capital expansion plans associated with accommodating load growth on transmission and distribution systems. Additionally, the development of storage technologies and the lower cost promise associated with increased production from ancillary markets is allowing for increased focus on utility based storage. PEV and hybrid vehicle production is greatly expanding the number of battery types and manufacturers. Energy storage devices can generally be classified into power and energy categories. Power related storage devices address quick charge and discharge needs charging and discharging within seconds to minutes, while energy related storage devices address charge and discharge over the course of hours. A myriad of technologies are emerging that address either of these categories on a small and large scale, with a few technologies addressing the storage needs that fall in between. Specific applications for storage are varied, ranging from shifting wind and solar energy time of use to periods when the utility system experiences peak usage, to use of storage to defer capital costs of transmission and distribution as well as generation expansion. The wide variety of emerging storage types also present a wide variety of relative costs, with some types already working in viable applications, while others are expected to be viable after costs are lowered. Lithium Ion batteries are a key example of a battery technology that is predicted to decrease in cost from its relatively high current position due to adoption by the auto industry. The following table classifies the various storage technologies currently being utilized, demonstrated or envisioned and the associated applications of these technologies, as well as their relative cost and size. The most commercially available energy storage technologies are pumped hydro and batteries. Since New Mexico is currently under drought conditions and rainfall is relatively scarce, the ability to maintain reservoirs levels to make pumped hydro a viable option is questionable. Compressed air is also a viable technology; however, to make this a feasible solution requires an established wholesale market price for regulation services and large capital requirements. Both of these technologies did not make PNM s list of feasible options for this IRP. 103

116 Reviewing Future Resource Options PNM IRP TABLE 105. STORAGE TECHNOLOGIES AND ASSOCIATED COSTS. Storage Type Power/Energy Application Specific Applications Relative Cost Relative Size Pumped Hydro Energy (hours/days) Shifting/smoothing Wind/Solar (current) Compressed Air Energy (hours) Shifting Wind (proposed) Flow Batteries (Vanadium Redox, Zinc Bromine) Metal Air Batteries Energy Sodium Sulfur Batteries Lithium Ion Batteries Energy (some Power ability) Energy (some Power ability) Power (minutes) Lead Acid Batteries Power (some energy ability) Flywheels Power (seconds minutes) Nickel Cadmium Batteries Ultra Capacitors Power Power (sub seconds to seconds) Smoothing/Shifting Wind/Solar (demonstration phase) Deferring system expansion (proposal) Shifting Wind/ Solar (proposed) Smoothing Wind/Solar (demonstration phase) Deferring system expansion (current) Smoothing Solar (demonstration phase) Shifting and Smoothing Solar (demonstration phase) Deferring system expansion (proposal) Regulation on ISO (current) System deferral (proposed) Smoothing/ regulation (proposed) Thermal Energy Energy Cooling shift to off peak (current) Low Low High (until proven forecasted to be low) High (until proven forecasted to be low) High Medium High (potential for cost erosion from associated Auto build) Low Medium Medium High Very Large Large Medium Medium Medium Large Small Medium Small Medium Medium Large Small Medium Small Medium Batteries remain expensive but could provide value by firming up intermittent resources and deferring T&D expansions. PNM incorporated batteries as a possible resource solution using two Low Small 104

117 Reviewing Future Resource Options PNM IRP options. PNM incorporated lead acid battery storage sized to fit with the 40 MW PV facility option discussed in section 7 using today s battery costs. Lead acid was chosen for its low cost. Additionally, PNM included an option for modeling storage using PNM s existing utility owned PV systems that are currently installed coupled with a battery to dispatch the energy. For planning purposes, battery storage would effectively raise the reserve margin contribution to peaking generation needs of the solar PV facilities from 55% to 100%. Current pricing of battery storage is relatively expensive, as confirmed by EPRI studies that indicate the need for large price reductions for sufficient cost/benefit ratios to be achieved. 5 Recognizing that battery storage is a mature technology that lacks integration schemes and the adoption rate that could reduce the manufacturing costs, PNM applied a 2020 market projection for the installed cost of batteries, which assumes full manufacturing capacity has been achieved. Table 105 provides these estimates. PNM considers all other storage solutions more expensive and in an early commercial phase and therefore, not viable for this IRP. It should be noted that members of the Working Group disagreed with PNM s assessment of the status of the technology especially related to flywheels. To acknowledge their concerns, resource planning will examine the results of the current PNM/DOE PV Demo Storage project and incorporate any benefits from adding storage into the modeling during the next planning cycle. Additionally, PNM agrees to monitor the developments in the storage industry to determine how storage could provide additional solutions to the portfolios that are at present, not apparent. Renewable Resource Options New Mexico has abundant potential to generate electricity using renewable fuel sources. PNM developed a list of possible renewable generation resource additions that could be available within New Mexico. The options modeled in this IRP are: parabolic trough (solar), largescale solar PV, wind resources, and customersited renewable DG (small PV). SOLAR Solar facilities convert solar energy to electricity by concentrating the incoming available sunlight and converting to electrical energy (PV), or converting to heat and then to electrical energy (solar thermal). Locations around New Mexico are ideal for maximizing the potential of these types of facilities. While many technologies exist for converting solar energy to electricity, PNM only utilized technologies that have been implemented and are commercially available on a large scale. For this reason, PNM only modeled two options as viable resources: parabolic trough and PV. Over the longterm, PNM expects the costs for solar technologies to decline to reflect anticipated gains in efficiencies and economies of scale, as this technology matures or full manufacturing capacity is realized. Based on a consensus with the Working Group, two capital cost expectations were modeled for all solar configurations. PNM developed a projection for 2011 based on current construction costs with 22 MW utilityowned solar PV (discussed in Section 7), and a future price reflecting a decline in solar equipment costs (which represent 50% of the overall costs) of 10% per year until EPRI: Electricity Energy Storage Technology Options, A White Paper Primer on Applications, Costs and Benefits, TR , December 2010 (publicly available). 105

118 Reviewing Future Resource Options PNM IRP It was noted over the course of the year long IRP process that the PV industry is rapidly changing, as revealed by the steadily declining price of PV panels. To allow enough time to model options and analyze the results, it was important to conclude final cost assumptions. In April 2011, PNM issued a RFP solicitation for renewable resource that is expected to provide solutions to meet PNM s RPS in Bid solicitations from that process were due to PNM in mid June. Final analysis of those bids is expected to occur after the filing of this IRP and therefore, cannot be included in this plan. However, PNM will revisit the cost assumptions made in this IRP filing with any new information we receive from those responses. Should the results of the RFP represent a material change to the plan, PNM will take appropriate steps. PARABOLIC TROUGH WITH NO THERMAL STORAGE In 2008, PNM, along with several other western utilities, studied the feasibility of a concentrating solar power project in New Mexico. This study, performed by various entities and directed by EPRI, produced a report indicating that nearterm, parabolic trough technology is the most commercial and economic. Solar energy is focused on a receiver tube containing a heat transfer fluid using parabolic (or trough shaped) mirrors in a series. The shape of these reflectors concentrates the sunlight to heat the transfer fluid which is used to produce steam via a heat exchanger. Steam then flows through a steam turbine to drive an electric generator to produce electricity. For this IRP, PNM modeled a 50megawatt resource, which is likely smaller than a plant would be built for the future. To achieve economies of scale, the IRP assumes that PNM would participate in shared ownership of a central solar facility which would be larger than 50 MW. PNM assumes this facility could be located within the NNM System (inside of WECC Path 48) and therefore would not require any transmission service rights or added wheeling costs to deliver to the load. Solar facilities are credited to contribute 55% of the installed capacity to meet the summertime peak. Therefore, when PNM is experiencing it peak, it is expected that solar facilities of this type and magnitude will be online to yield at least 27.5 MW of capacity to meet the load. The steam side of a trough plant requires large amounts of water to condense the steam to a workable fluid. For most future technologies that require water for cooling, PNM adds the cost to reduce water use in construction cost buildout. However, as the ambient temperature climbs, the ability to effectively cool the working fluid is reduced along with the associated output (capacity), generation (energy) and heat rate (efficiency). This increases the cost of generation. Because solar facilities have high capital costs, any additional costs would make them economically unfeasible. As a result, no water saving technology was used on any of the trough options. Therefore, all trough options include wet cooling as the means to transfer heat from the steam. PARABOLIC TROUGH WITH THREEHOUR THERMAL STORAGE The operational characteristics of the parabolic trough solar generation facility can be improved by adding thermal storage. Thermal energy storage diverts the heated transfer fluid to an insulated storage tank where it can be accessed during periods when solar radiation is low. Adding thermal storage to a parabolic trough system allows the solar plant to be dispatchable and to achieve higher capacity factors. Since thermal storage remains an evolving technology, this alternative is only considered available after Solar storage is modeled as an incremental addition to the centralized solar resource. This allows excess generation to be stored offpeak (for up to three hours) and then redispatched during times of peak usage. Solar facilities with storage are considered to contribute 100% of the installed capacity to meet the summertime peak. PNM assumes this facility could be located within the NNM System (inside of WECC Path 48) and 106

119 Reviewing Future Resource Options PNM IRP therefore would not require any transmission service rights or added wheeling costs to deliver to the load. SOLAR PV PNM modeled a 40megawatt nonconcentrating PV solar facility with singleaxis tracking capabilities. Single axis tracking results in higher energy capture by allowing the PV array to track the sun to maximize energy output at any particular time and date. Since New Mexico has abundant solar, it was assumed that a PV facility would be constructed on the load side inside of WECC Path 48 at one of many possible locations, so additional transmission costs associated with this facility in the resource optimization modeling are limited to interconnection station integration cost. Furthermore, PNM increased the output of these facilities to capture the avoided losses on the transmission system. Solar PV systems are expected to contribute 55% of the installed capacity to meet the reserve margin. WIND New Mexico offers abundant wind resources. PNM modeled new wind additions in 100megawatt increments as a resource selection. For RPS compliance, PNM modeled sizes ranging from 50 MW to 200 MW in increments of 50 MW. Transmission cost was added to this resource to reflect the need for interconnection station cost, as well as integration and transmission system upgrades in eastern New Mexico, because most of the viable wind sites in New Mexico are located in the eastern portion of the state where existing transmission capacity is very limited. There is a limit on the number of wind generation plants that can be constructed to serve PNM load, due to the number of natural gas facilities that would be required to provide system regulation for intermittent variable resources. PNM is conducting a study to estimate wind integration costs for various levels of wind generation, taking into account geographical diversity. PNM is also exploring ways to increase system flexibility to allow for integration of higher levels of variable wind resources. Nearterm initiatives include participation in the ACE Diversity Interchange (ADI) project and addition of flexible gas generation, such as gas turbines that can load follow without economic penalties. Future deployment of storage technologies could also allow for integration of higher levels of variable wind generation for New Mexico consumers should the technologies become more economic. 107

120 Reviewing Future Resource Options PNM IRP NATURAL GAS GENERIC COMBUSTION TURBINE NATURAL GAS PEAKING PLANT PNM modeled three different capacity sizes of peaking options using simplecycle gas turbine technology: 40, 85 and 177 megawatts. These units are based on typical New Mexico siting conditions and therefore include a derating of their capacity based upon a 4,500 feet elevation. The three generic sizes represent typical manufactured sizes. Of the three generic manufactured sizes, two (40 MW and 80 MW) offer a fast start capability and the larger unit is expected to be able to achieve fast start capability although it has yet to be demonstrated. That is, the ability to be ready, fully loaded and online in ten minutes, which helps PNM maintain system voltage and regulation, if needed, and helps satisfy spinning reserve requirements. Because natural gas is a relatively cleanburning fuel, and plants that use natural gas require relatively little acreage, PNM assumed this option could be located within the NNM System (loadside of WECC Path 48). For modeling purposes, the IRP assumes that loadside resources do not require any transmission upgrades; therefore, only transmission interconnection costs are associated with these facilities in the resource optimization modeling. Natural gasfired turbine facilities use minimal amounts of water; therefore, it is impractical to use water reducing technology. GENERIC COMBINEDCYCLE NATURAL GAS FACILITY Intermediate duty cycle resource options can be a pivotal part of fleet operations as they bridge the gap between operating a more costly peaking plant or backing down a baseload plant. To capture facilities that could provide intermediate duty cycle operations, PNM modeled a generic natural gasfired combinedcycle plant. A combinedcycle plant has greater fuel efficiency than a combustion turbine plant, but has higher capital expense due to the addition of a steam cycle and can be turned down without significant efficiency loss. At typical New Mexico site conditions, combined cycle facilities can range in size from approximately 180 to 600 megawatts. PNM chose a 252 megawatt 1x1 system based on its high efficiency rating (which meets PNM s reliability criteria), and its size (which fits PNM s system needs). PNM assumes that this facility could be located within the NNM system (load side of WECC Path 48), so additional transmission costs associated with this facility are limited to station integration. Unlike gas turbines, the steam side (i.e. Rankine cycle) requires large amounts of water to condense the steam. To reduce any impacts due to water shortage or high commodity costs, PNM expects that these types of applications would employ a watersaving technology for cooling, such as that installed in the Afton Generating Station (hybrid cooling), or an air cooled condenser (dry cooling). The lowwater use alternatives entail higher equipment costs. These costs are included in the installed capital costs for the construction, and the appropriate penalties have been included in the performance characteristics. 108

121 Reviewing Future Resource Options PNM IRP NUCLEAR The IRP limits the modeling of nuclear resource options to 200 megawatts increments, with costs prorated accordingly. Recent federal incentives and anticipated CO2 restricting legislation have caused the federal government and the utility industry to again explore the development of nuclear generation. Because several utilities have begun the process of licensing new plants, and the U.S. government has authorized loan guarantees, PNM considers nuclear energy a viable resource option. PNM does not need the large capacity associated with constructing new nuclear facilities. When modeling a new nuclear resource, PNM assumes participation with multiple facility owners in the construction of a new unit remote from the load center. The costs of the modeled nuclear plant include transmission costs for station integration. The IRP limits the modeling of nuclear resource options to 200 megawatts increments, with costs adjusted incrementally from a large scale buildout. Since no new nuclear facilities have been constructed domestically in the past 25 years, PNM assumes 2018 is the earliest date that a new nuclear resource could be constructed. This date could change depending upon the scrutiny following the Japan nuclear incident. Nuclear generation requires the most significant water use in the utility industry, due to the high operating temperatures. Similar to combined cycle facilities, these types of applications would employ a hybrid or dry cooling technology. These costs are included in the installed capital costs for construction, and the appropriate penalties have been included in the performance characteristics. COAL Coal options include a supercritical pulverized coal (PC) technology which represents the most efficient pulverized coal technology today. Since the IRP provides future cost assumptions during the entire planning horizon, equipment for SCR for NO x control and carbon capture and sequestration (CCS) (including costs to transport, store and monitor CO 2 emissions), as well as hybrid or dry cooling technology are included in the cost estimate. To achieve economies of scale, PNM would likely participate with other entities in construction of a base load coal plant. Any new coal facility will likely be remote from the load center, so the costs of all coal options are increased to include transmission costs for system integration. It is expected that baseload facilities would require transmission system upgrades to bring the energy to load. Should future additions show the need for baseload facilities, PNM will reassess transmission costs and include them in the modeling phase. During the IRP Working Group meetings, concerns were raised that the construction costs for new coal generation presented by PNM were low. Members provided other reports detailing their expectations of the costs. To reach consensus regarding the costs to build new coal resources, the capital cost estimate was increased from $5,115/kW to $5,735/kW. The higher number 109

122 Reviewing Future Resource Options PNM IRP represented the midpoint between both cost estimates. For modeling scenarios, the higher coal facility capital cost was used as a proxy for new coal alternatives. The IRP limits the modeling of coal resource options to 200 megawatt increments, with costs prorated accordingly. PNM assumes that 2018 is the earliest date that a new coal resource could be constructed. EMERGING TECHNOLOGIES Emerging technologies discussed during the IRP process included: CCS, modular nuclear power, smart grid, and electric vehicles. PNM presented these technologies to the Working Group as possible resources in the future. With the exception of CCS and electric vehicles, this list represents future technologies that PNM reviewed, but does not have adequate information to model at this time. For emerging technologies not modeled, PNM presented an overview of technology paths, mapping trajectories of all the technologies discussed, in terms of ease and extent of accommodation over the years. A general overview for each technology is presented in the following paragraphs. ELECTRIC VEHICLES Although the United States has had hybrid vehicles for some time now, a new variety of electric vehicles will be coming to market in late 2010 through These vehicles will have electric battery packs that not only charge by regenerative braking systems, like previous hybrid electric vehicles, but also plug in as a means to recharge the battery. Because these vehicles will plug in as a means of charging the batteries, it is important for the utility to understand how much electricity will be required to charge the batteries (electrical load), and the possible adoption rate of these vehicles, so that PNM can properly assess the effects of the vehicles on the utility infrastructure. At the time of this writing, there have been three major announcements of new models of electric vehicles or plug in hybrid electric vehicles. To charge these vehicles, there are three levels of charging: Level 1 charging (done at 120V), Level 2 charging (done at 240V), and Level 3 charging (this is a direct current fast charge). The Level 3 charging remains in development. Table 104 summarizes current projections. Given the charging requirements of these vehicles, it is important to understand where these vehicles will be charged. An EPRI consumer survey completed in 2010 indicated that, when given a choice of two locations, consumers overwhelmingly expected to charge vehicles at home (96%), with a secondary charging location being their place of work (49%). Public charging infrastructure will also be a factor in how much and where electricity is used for vehicle charging. The challenge with electric and plug in hybrid electric vehicles is to predict a possible adoption penetration rate. Most completed studies varied widely in their estimates of vehicle adoption. A study by KEMA in March 2010, took an approach similar to a 2008 Pacific Northwest National Laboratory report and a 2006 Oak Ridge National Laboratory report in projecting three separate adoption scenarios (slow, target, and fast). Based upon Toyota Prius sales from 2000 to 2007, New Mexico had a range of vehicles adopted per 1,000 vehicle registrants. Given these widely varying scenarios, one possible indicator of adoption rates is the adoption of what is seen today as traditional nonplug in hybrid vehicles. New Mexico is in the top 20 states in the nation in per capita adoption of hybrid vehicles. Using a possible adoption rate of 1.5 vehicles per 1000 customers 110

123 Reviewing Future Resource Options PNM IRP annually (which is approximately the rate of traditional hybrid vehicles), would equate to approximately 550 vehicles in PNM s service territory. This adoption rate would indicate approximately 4 MW of added load to the PNM system. Again, adoption rates can be extremely variable, and depend on many factors. Factors such as the cost of gasoline, cost of vehicles, and government incentives can change adoption rates. TABLE 104. ELECTRIC CAR LOAD PROJECTIONS Charge Type Voltage and Current Time to Charge (assume 0100%) Load Load comparison Level 1 120V 16 A max Between 8 16 hours kw A hair dryer. Level 2 240V 80 A max Between 3 8 hours kw A 3.5 ton air conditioner for a 2500 sq. ft. home. The 19.2 kw is a large battery system in the Tesla Roadster, which compares to 6 to sq. ft homes. Level 3 DC Fast Charge 480 V, 1000A About 20 to 30 minutes 50 to 250 kw Similar to a 3 phase commercial application, like a fast food restaurant. After estimating the load of this charging infrastructure, and the adoption rates, it is also important to estimate when these vehicles will be charged. Giving the opportunity to charge during off peak hours may help limit the need of the utility to upgrade infrastructure and add generating resources. If vehicles are charged during off peak times (i.e. not further contributing to system peak by charging at peak times), it is estimated that in the next three to five years, the additional charging load will not increase the need to add generating resources or transmission capacity to meet charging needs. Finally, there has been speculation in the industry of the capability of vehicle to grid support. This refers to the ability to use the plugged in vehicles as storage resources to do things such as shave peak locally, or smooth variability in renewable generation resources such as solar PV and wind. Although technically possible, it is not projected that this will be practical over approximately the next ten years. Today s batteries are early in technical development and come at a relatively high cost. Therefore, most vehicle manufacturers and consumers will not choose to use vehicle batteries until they are more technically capable, or more importantly, more economic to do so. PNM believes that even though electric vehicles are an emerging technology, it could impact the load forecast during the planning horizon. Unlike other technologies which act to shave the peak, PEVs do not operate as a resource to meet growing load. Rather, the forecast of electric vehicle utilization behaves as a load and will be added to the projected load forecast to determine the impact on the build decision. For more details on the PEV forecast, see Section

124 Reviewing Future Resource Options PNM IRP SMART GRID Although many people immediately think of smart meters when they think of smart grid, the truth is that there is smart grid technology throughout the utility grid today, including generation, transmission, distribution, and within the customer domain. The Department of Energy has defined the smart grid using seven principle characteristics: 1. Enable active participation by customers 2. Accommodate all generation and storage devices 3. Enable new products, services, and markets 4. Provide Power quality for the digital economy 5. Optimize assets and operate efficiently 6. Anticipate and respond to system disturbances and react to them (self heals) 7. Operate resiliently against natural disaster and attack There are opportunities to add sensors and automation throughout the generation, transmission, and distribution system to realize many of the DOE s seven principle characteristics. Sensors on the transmission and distribution system can help accommodate new generation resources such as renewable energies and storage devices, which is important for power quality, and will contribute directly to self healing and resilient operation against attack and natural disaster. However, the smart grid has the potential to involve more enduse customers than ever before. As described by the DOE s definition of smart grid, it could allow active participation by customers and enable new products, services, and markets that were not possible in the past, while safely and efficiently integrating their DG resources. Although not the be all, end all of smart grid, this particular aspect will be facilitated by smart meters. Both the utility and customer will potentially see benefits related to the deployment of smart meters. Benefits such as improved outage notification time, early detection of loss of service, automated meter reading, remote connect and disconnect would be possible. The ability to have active participation by customers in energy usage could allow from the most simple case of some consumers to track actual energy usage, to more interactive features, such as special pricing programs like prepay, time of use rates, electric vehicle only rates, or even in the most complex case, real time pricing. Residential smart meters currently available typically allow a utility to collect data incrementally via remote, secure, wireless communications. A resident can access usage information via a secure web site. Early deployments of smart meters in the United States have shown energy savings based on customers actively managing to this feedback, or within particular new rate structures. Early studies have shown 5% to 20% energy savings based on different rate structures. However, because these smart meters are in the early stages of deployment, it is not conclusive if these energy savings are sustainable, or are simply a product of participation in a pilot program, where behaviors can be easily sustained over the short period of study. This is important from a resource planning perspective because if utilities choose to invest in smart meter technologies rather than traditional peaking resources, the utilities must be confident that they can call on the smart meter technologies and be assured of the same response that they would normally get from a peaking plant in terms of load reduction. It is also important to note that customers will have different preferences. Some will be eager to manage their energy usage to either save money or contribute 112

125 Reviewing Future Resource Options PNM IRP environmentally. However, some customers will not choose to manage their energy usage, given the modest cost savings. PNM believes that smart grid meters would not be implemented in the short term for its service territory. PNM continues to evaluate smart grid meters and will reassess any future developments. CARBON CAPTURE AND SEQUESTRATION (CCS) The basis of CCS technologies involves capturing carbon dioxide from the flue gas of the combustion process at a coalfired generation plant. The basic approaches involve either chemical absorption or cryogenic cooling. Both of these technologies have been manifested in the chemical processing industry on a much smaller scale. The biggest challenge today is scaling up these technologies and generating the extra amount of energy required to run them in a coal plant environment. Chemical absorption uses catalysts that react with the flue gas and allow the carbon dioxide to be captured from the flue gas stream, and then isolated through an additional process. Cryogenic cooling involves taking the flue gas to a temperature low enough for the carbon dioxide to be separated from the other constituents in the flue gas. Both processes are very energy intensive and need to be tuned to the type of coal being combusted. Higher ash coal, such as that consumed at SJGS, is problematic in that it is unique in its high ash content, and this high content tends to be difficult to tune to these processes. DOE sponsors a few pilot projects that are targeting smaller scale demonstrations of carbon capture, and other large utilities are now assessing the potential to implement CCS on a large scale. These are being monitored for effectiveness and energy consumption. Additionally, there are demonstration projects testing the viability of sequestration in certain types of geologic structures throughout the nation. In concert, these demonstrations point to significant additional capital and O & M costs that would be required to implement CCS. PNM believes that there is a reasonable probability CCS could be viable in the next 10 years. Demonstration projects have been successful, have accelerated development, and it is credible to predict that CCS would be commercially available on a large scale within the planning time period. As a result, PNM has included the cost of building environmental equipment capable of capturing CO 2 by as much as an 80% removal rate for any coal alternative. Since CCS remains in its infancy, PNM s projected costs are based in part on EPRI data and are speculative based on scaling up small demonstration projects. NEW NUCLEAR With the advantage of no emissions, nuclear options have received renewed attention. Efforts focus on standardization of designs and acceptance of these designs by associated regulatory bodies. Nevertheless, costs for nuclear generation have remained high, as demand for construction and plant component manufacturing in the U.S. remains low. Regulatory and siting issues continue to be difficult hurdles, especially with recent events in Japan. Water consumption required by nuclear plants also remains a key issue as the high consumption is linked to declining availability of water resources, especially in the western U.S. Waste disposal is also an issue that needs to be solved to enable wider dissemination. Other developments in the nuclear power generation field are centered on mini or modular nuclear ( mininukes ) which essentially take naval (submarine and carrier) or similar type nuclear 113

126 Reviewing Future Resource Options PNM IRP generation designs and place them in landbased modular units. While the naval base generators are proven technology, the permitting and regulatory path for land based application that is non Defense Department based remains unclear. Because mini nukes are in still in their infancy and cost data is extremely hard to find, PNM did not include them as a possible resource alternative for this IRP. However, this technology interests PNM, and PNM will monitor its progression and may include it as a possible addition in the future. WATER FOR FUTURE PLANTS Depending on the type of generation needs in the future, water can play a critical role in the feasibility, cost and site selection for those generation facilities. Solar PV and wind consume no water, and simplecycle gas turbines use minimal water. Steamturbine plants (such as combinedcycle gas, coal and nuclear) use the most water primarily because of the need to cool the working fluid (steam) that turns the turbines. If the future resource mix calls for generation that requires significant amounts of cooling, the planning process will include an evaluation of the availability and cost of the following cooling resources (in approximate ascending order of initial cost and operating cost impacts): 1. Raw groundwater 2. Raw surface water 3. Private or municipal potable water 4. Reclaimed municipal wastewater 5. Impaired water (such as brackish, produced water from oil and gas exploration, industrial wastewater, etc.) 6. Hybrid cooling (air cooling with water cooling) 7. Air cooling In the context of developing future generation, water availability and cost can be key factors, but having these alternative cooling resources means that water rarely has the potential to shape the location or cost of a facility like other factors such as transmission availability, fuel supply, elevation, and land availability. For this reason, cost estimates for new technologies, except where noted, include cost base on level 6 or 7. COST AND PERFORMANCE SUMMARY FOR NEW RESOURCE OPTIONS Working through the list of all technologies, PNM provided cost estimates for new technologies based on EPRI data modified to fit typical siting conditions in New Mexico. The IRP Working Group was invited to comment on the cost estimates, and PNM received three different reports containing cost estimates for generic technologies. As a result of reviewing the three reports, capital costs for nuclear and coal were revised to reflect the midpoint between the Working Group estimates and PNM. All other estimates were found to be in range of both the Working Group and PNM s expectations. The following figure provides a highlevel comparison of the capital costs of each resource option discussed in this section. The capital cost for nuclear and coal shown in the graph reflect the midpoint. For a specific breakdown of actual costs by resource, refer to Figure

127 Reviewing Future Resource Options PNM IRP FIGURE 105. CAPITAL COSTS PER KILOWATT (IN 2011 DOLLARS) OF RESOURCE OPTIONS FUTURE RESOURCE COST SUMMARY TABLES Table 106 summarizes the operational characteristics, projected size, installation costs, O&M expenses and availability assumptions used to model new resource options in this IRP process. This table includes the corresponding environmental impact. Additionally, Table 106 includes an estimate for the inservice date for resource alternatives taking into account the time required to receive an air permit, file a CCN, receive an approval and construct a facility. 115

128 Reviewing Future Resource Options PNM IRP TABLE 106. COST, RELIABILITY AND ENVIRONMENTAL PERFORMANCE FOR NEW RESOURCE OPTIONS Aeroderivative Gas Turbine Gas Turbine Combined Cycle Coal w/carbon Solar Trough (no Solar Trough Plant Turbine (small) (large) Natural Gas capture Nuclear storage) (storage) Size (MW) Fuel Type Natural Gas Natural Gas Natural Gas Natural Gas Coal Nuclear Solar Solar Proj Forced Outage Rate (%) 3% 3% 3% 5% 9% 3% n/a n/a Proj Heat Rate (MMBtu/MWh) n/a n/a Proj Availability Factor (%) 97% 97% 97% 89% 81% 81% n/a n/a Proj Fixed O&M (000$/yr) $640 $1,275 $1,593 $6,048 $16,000 $18,200 $3,550 $3,919 Proj Variable O&M ($/MWh) $5.00 $4.00 $10.00 $2.50 $3.00 $5.70 $3.00 $3.00 Proj Capital Cost 2011 ($/kw) $1,680 $1,595 $916 $1,540 $5,115 $5,950 n/a n/a Proj Capital Cost 2015 ($/kw) $5,735 $4,440 $5,060 Earliest InService Date Retirement Date After 2030 After 2030 After 2030 After 2030 After 2030 After 2030 After 2030 After 2030 Emissions Data CO (lbs/kwh) n/a n/a n/a NOx (lbs/kwh) n/a n/a n/a Particulate (lbs/kwh) n/a n/a n/a SO2 (lbs/kwh) n/a n/a n/a CO2 (lbs/mwh) 1,147 1,030 1, n/a n/a n/a Mercury (lbs/kwh) n/a n/a n/a n/a n/a n/a n/a n/a Ash ($/ton) n/a n/a n/a n/a $5 n/a n/a n/a capital costs do not include all site costs 116

129 Reviewing Future Resource Options PNM IRP Plant TABLE 106 (CONTINUED). COST, RELIABILITY AND ENVIRONMENTAL PERFORMANCE Solar Photovoltaic Wind Small PV w/battery (DG) Microturbines (DG) Fuel Cells (DG) San Juan #1 Repower Size (MW) Fuel Type Solar Wind Solar/Battery Natural Gas Natural Gas Natural Gas Proj Forced Outage Rate (%) n/a n/a 5% Proj Heat Rate (MMBtu/MWh) n/a n/a n/a 12,700 6, Proj Availability Factor (%) n/a n/a n/a 90% Proj Fixed O&M (000$/yr) $600 $850 $25 $100 $280 $5,514 Proj Variable O&M ($/MWh) n/a $7.00 n/a $3.50 Proj Capital Cost 2011 ($/kw) $4,500 $2,564 $7,400 $1,400 $8,000 $844 Proj Capital Cost 2015 ($/kw) $3,860 Earliest InService Date Retirement Date After 2030 After 2030 After 2030 After 2030 After 2030 After 2030 Emissions Data CO (lbs/kwh) n/a n/a n/a TBD TBD TBD NOx (lbs/kwh) n/a n/a n/a TBD TBD TBD Particulate (lbs/kwh) n/a n/a n/a TBD TBD TBD SO2 (lbs/kwh) n/a n/a n/a TBD TBD TBD CO2 (lbs/mwh) n/a n/a n/a TBD TBD 796 Mercury (lbs/kwh) n/a n/a n/a n/a n/a n/a Ash ($/ton) n/a n/a n/a n/a n/a n/a capital costs do not include all site costs TABLE 107. GENERAL MAINTENANCE SCHEDULES ASSUMPTIONS New Unit Maintenance Schedule Assumptions Maintenance Frequency Unit Type Type Duration (weeks/year) Years from COD Yearly Gas Turbine Tuneup 1 N/A 10 years Combustion Inspection 1 5, 15, years Hot Gas Path 2 10, 20 Once Major Inspection 4 27 Yearly Tuneup 1 N/A 10 years Combustion Inspection 1 5, 15, 25 CC (1x1) 10 years Hot Gas Path 2 10, 20 Once Major Inspection 4 27 Yearly Tuneup 1 N/A 5 years Aeroderivative Combustion Inspection 1 15, years Hot Gas Path 4 10, 20, Months Pulverized Coal Regular Maintenance 3 N/A N/A Fixed Energy Renewables Regular Maintenance 0 N/A Along with the capital, O&M and performance data, the financial assumptions used to model each resource is important. Table 108 details the list of financial assumptions, incentives and various modeling assumptions that PNM used to model each potential resource option listed in the table above. 117

130 Reviewing Future Resource Options PNM IRP TABLE 108. FINANCIAL ASSUMPTIONS, INCENTIVES AND DEPRECIATION FIGURES Detail Duration Cost of Capital (Aftertax) 8.77% Inflation 2.5% per year Escalation on O&M 3.0% per year Escalation on Fuel (natural gas) 3.5% per year after 2016 Escalation on Fuel (coal/nuclear) 3.0% per year after 2016 NPV basis 30 Years Property Tax Rate 2.00% Insurance Rate 0.50% Federal Incentives Solar (ITC) 30% plus bonus depreciation Wind (PTC) $22/MWh 10 years, escalated at inflation State Incentives Solar(AEC) 10% Solar(PTC) Varies 10 years, caps at 200 GWh Wind(PTC) $10/MWh 10 years, caps at 400 GWh Property Tax Rate for Small PV 0% Residential systems only Depreciation for New Resource Options Book Life Book Method Tax Method Nuclear 40 yrs Straight Line 15 Yrs MACRS Coal 40 yrs Straight Line 20 Yrs MACRS Combined Cycle 30 yrs Straight Line 20 Yrs MACRS Combustion Turbine 30 yrs Straight Line 15 Yrs MACRS Solar 30 yrs Straight Line 100% 1st year Wind/Geothermal 30 yrs Straight Line 20 Yrs MACRS Other Modeling Assumptions Amount Source/Reference/Notes Capacity Factors Capacity factor for Wind alternative 36% Based on results from RFPs issued Capacity factor for PV alternative 26.7% Based on NREL data Capacity factor for Solar trough alternative 26% Based on EPRI Study for NM CSP Contribution to Peak Wind 5% Based on NREL data Solar Technologies 55% Based on historical performance 118

131 Reviewing Future Resource Options PNM IRP TRANSMISSION FACILITIES FOR NEW RESOURCES All new potential resources should include costs that reflect transmission improvements required to connect the resources to PNM s load, and transmission service costs required to deliver the power are not included. Since the major assumption for this IRP is that any new resources would be sited within the NNM load pocket; the need for transmission improvements would be limited to station integration costs and require little, if any, newly built transmission facilities. For resources such as coal or nuclear that would most likely be in remote locations, transmission improvements would most likely be required and need to be included in the cost to add resources to the system. For this IRP, PNM assumed that new transmission would not be built to new resources in remote locations. TRANSMISSION PLANNING: TRANSMISSION DELIVERY AND INTERCONNECTION SERVICES Planning and operating transmission systems has become more complex in recent years. Ever changing FERC policy, competition in the wholesale generation market, lack of new transmission development due to uncertainty over cost recovery, and opposition to siting of new facilities are just some of the issues facing transmission planners today. It is not possible to produce a complete transmission system expansion plan without a discussion of the regulatory and market forces that influence the planning process. FERC policy has undergone several very significant changes over the past decade. Currently, significant changes are taking place in the area of generator interconnection procedures. Each of these policy changes has added to the complexity of the transmission business and impacted the types of transmission services that PNM provides to itself and others, the processes PNM uses to study its system, and the allocation of expansion costs amongst project beneficiaries. FERC distinguishes interconnection service from transmission delivery service. Terms and conditions of each type of service are defined in the PNM Tariff. Interconnection service does not provide the ability to deliver energy across the system. Each type of service can be requested and purchased separately from the other, or they can be purchased at the same time, at the option of the Tariff customer. GENERATION INTERCONNECTION SERVICE PNM has experienced a surge in merchant generation interconnection requests over the last several years. PNM currently has 44 active Large Generator Interconnection Applications totaling 14,918 MW in a balancing authority area with a historic peak load of approximately 2,600 MW. The rise in interconnection requests is largely due to the increasing interest in renewable energy development for both wind and solar facilities to harvest and transform into electricity. The largest groups of generation interconnection requests are located in eastern New Mexico where wind dominates the requests. Other areas within the PNM service area are popular but not to the scale of the eastern side of the state. The eastern New Mexico area receives the most generation interconnection requests, yet has the least amount of existing transmission to manage all the requests. These generation resources equally compete for capacity on the transmission system whether they serve load in or outside of New Mexico. PNM uses a procedure established by FERC to identify the 119

132 Reviewing Future Resource Options PNM IRP necessary network upgrades and cost allocation. Generation interconnection service does not imply or reserve transmission service. PNM filed a request for acceptance of certain changes to its OATT with FERC on May 5, These changes will bring significant improvements to PNM s Large Generator Interconnection Procedures (LGIP) that will increase the efficiency of the interconnection process, decrease future queue backlogs, and promote the interconnection of viable generation projects that are ready to proceed. TRANSMISSION DELIVERY SERVICE PNM is obligated to ensure delivery capability to all eligible transmission customers (NITS and pointtopoint) within its system. As mentioned in section 7, PNM provides a relatively large portion of transmission service to others as compared to its own use. PNM is obligated to plan its transmission system to meet not only its own native load customer needs, but also the network load needs of the network transmission customers. PNM takes the lead in working with all of its network transmission service customers to incorporate their load growth and network resource plans into PNM s overall transmission growth requirements. By having virtually all New Mexico load under similar transmission service agreements, PNM is better able to coordinate the usage and planning of that system going forward. Transmission Service, commonly referred to as wheeling, refers to power that is moved on the transmission grid from a Point of Receipt (POR) to a Point of Delivery (POD), or from a resource to a load. It is important to note that transmission service is a separate and distinct service from generation interconnection service. Depending on the location of the transmission grid, the two service queues can have very different requests in terms of size of requested MW. The transmission queue is managed through PNM s OASIS (Open Access SameTime Information System) located on the web at When transmission service is requested, it can be immediately granted if there is available transmission capacity; otherwise, it goes into study mode to evaluate the capability of the system to accommodate the requested service. 120

133 Scenario Analysis PNM IRP SCENARIO ANALYSIS OVERVIEW The scenario modeling process determines the comparative cost, risk, reliability, and emission characteristics of resource portfolios given a set of future conditions. This section provides a description of the process PNM used to develop resource portfolios and analyze the type of resources selected for the given scenarios, identifies any resource addition trends, and includes recommendations of portfolios for further analysis. The information drawn from this analysis fed into the risk analysis and yielded the most cost effective portfolio. SCENARIO DEVELOPMENT PNM, with the help of the IRP Working Group members, developed a list of 26 scenarios to be modeled. The goal of the scenario analysis was to define a set of system conditions which over time could simulate future events. System conditions, such as changing customer demand levels, natural gas prices and CO 2 costs, are all possible future events which could impact the selection of resources and total system costs for customers over the next 20 years. Over the past year, PNM and the IRP Working Group defined the set of inputs for scenario development. The final set of scenarios is shown in Table 111. A scenario is a set of several conditions or input variables that are combined to obtain a unique result. The combination of conditions or variables comprising the scenario is known as a sensitivity. Sensitivity pertains to conditions such as a load forecast, natural gas price forecast, or CO 2 cost forecast. For example, scenario 1 in this IRP consists of the midload forecast, midnatural gas price forecast and an $8 per metric ton CO 2 cost. For this IRP, the twentysix scenarios were based on a wide range of factors to determine the impact of: Varying load forecast conditions Varying natural gas forecast Differing levels of future CO 2 costs Environmental upgrades for existing coal facilities Forced retirement of coal from PNM s existing portfolio High capital cost for new coal facilities Incorporating new regulations on coal fly ash (via cost adder) Simulating drought conditions Simulating New Mexico environmental regulations (Rule NMAC) A high adoption rate for PEVs Following scenario creation, PNM used the Strategist Software tool to create an economic mix of future resources and system costs based on the input variables of each scenario. The most economical future mix of resources, known as a least cost portfolio, was identified for each scenario and is discussed in detail in the Results of Scenario Analysis section. 121

134 Scenario Analysis PNM IRP TABLE IRP SCENARIOS Scenario Number Load Forecast Low Load X X Mid Load X X X X X X X X X X X X X X X X X X X High Load X X X X Mid Load with Electric Vehicle X Carbon Cost $8/metric ton CO2 Cost (2010) X $20/metric ton CO 2 Cost (2010) X $40/metric ton CO2 Cost (2010) X $35/metric ton CO2 Cost with Allowances X X X X X X X X X X X X X X X X X X X X $100/metric ton CO 2 (2018) X Fuel Mid Natural Gas Forecast X X X X X X X X X X X X X X X X X X X X High Natural Gas Forecast X X X X X X Capital Cost High PC w/carbon Capture X X X X Environmental SCR for SJGS X X SCR for SJGS/FCGS X X X X X X X SNCR for SJGS/FCGS X $20/ton Fly Ash Cost X $100/ton Fly Ash Cost X X X X Water Curtailment X NM GHG Cap Rule X Other Retire 200 MW of Coal Generating Resource X X Retire 340 MW of Coal Generating Resource X X 122

135 Scenario Analysis PNM IRP Section 8 discusses the details of load forecast and electric vehicle sensitivities and Section 9 addresses the details of the natural gas forecast sensitivities. The following paragraphs summarize the remaining sensitivities. CO2 SENSITIVITY The final order in Case UT, established standardized emission CO 2 costs to be used by electric utilities in IRP filings beginning in The order further provided that these standardized costs are presumed to be reasonable but did not preclude the use of any other cost assumption or alternative approach for dealing with CO 2 emissions in the IRP process. Due to the uncertainty currently surrounding GHG emission legislation, the IRP analysis assumed a variety of specific CO 2 costs for all scenarios. Most scenarios created for this IRP accounted for some amount of CO 2 cost and are consistent with NMAC and Federal Senate Bill 20 (Graham, 2010). The CO 2 costs used for the various scenarios are summarized as follows: Standardized CO 2 emission costs: Beginning in 2010, a cost per metric ton of CO 2 emitted by each portfolio of $8, $20, and $40 (in 2010 dollars with an escalation of 2.5% per year thereafter) was added to the dispatch cost of all existing and new resources that emit CO 2. These costs stem from the order in Case No UT. No allowances were credited back to the portfolio. Cap and Trade CO2 costs: Beginning in 2012, a cost of $35 per metric ton of CO2 (with an escalation of 2.5% per year thereafter) was added to the dispatch cost of all existing and new resources that emit CO2. This cost reflects the maximum CO2 cost (safety valve provision) that could be imposed under various federal GHG proposed legislation. The scenarios which include this $35 CO2 cost also incorporate a cap and trade mechanism whereby PNM is granted emission allowances based on PNM s existing generation portfolio. The annual amount of granted allowances declines according to federal proposals. For this plan, the credit for allowance emissions begins in 2012 and is based upon PNM s CO2 emissions in Extreme CO 2 costs: Beginning in 2012, a cost of $85.91 per metric ton of CO 2 (with an escalation of 2.5% per year thereafter) was added to the dispatch cost of all existing and new resources that emit CO 2. This cost reaches $100 in 2018, which the IRP Working Group chose to reflect the maximum carbon cost at a time when CCS would be available. No CO 2 cost: As a direct result of the IRP Working Group debates concerning CO 2 emission costs, the IRP Working Group requested an additional case where CO 2 costs were not considered in the optimization. ENVIRONMENTAL UPGRADES The EPA regional haze regulatory rulemaking process will determine best available retrofit technology (BART) for the SJGS and the Four Corners Power Plant. Since the EPA has not issued a final decision on BART, PNM tested the range of likely outcomes using two types of environmental upgrades that could reduce NOx emissions for improved visibility: SCR and SNCR technology. PNM commissioned a third party engineering, procurement, and construction firm (EPC) which estimated that PNM s share of the cost to install SCR technology at the SJGS would be $

136 Scenario Analysis PNM IRP million. This is the amount PNM modeled in the IRP even though subsequent estimates reduced this amount to be $408 million. Similarly, APS obtained an estimate to install SCR at the Four Corners Power Plant; PNM s estimated share is $66 million. The estimated l cost to PNM for installation of SNCR technology at SJGS is approximately $35 million for all four units. For this IRP, these initial estimated SCR and SNCR costs were added to the appropriate scenarios as an addition to the fixed costs over a three to four year timeframe to model the capital expense associated with the upgrades. Since these costs were added as fixed costs, they do not affect dispatch of existing or newly added units for each of the associated scenarios. The environmental equipment under these scenarios is projected to be online by the end of RETIREMENT OF COAL FACILITIES The impact of potential carbon costs and anticipated GHG legislation compel all utilities to take a second look at coal generation. Since the majority of PNM s existing portfolio is coal based, PNM examined the outcome of retiring existing coal generation. The amount of coal generation that was assumed to be retired from the portfolio varied: 200 MW and 340 MW, representing 20% and 34% of PNM s existing coal generation. PNM assumed that Four Corners Power Plant units #4 and #5 (200 MW total) would be retired by January 1, 2017 which coincides with the expiration of the coal supply contract. Similarly, PNM tested the assumption of eliminating a larger amount of coal generation at SJGS by retiring units #1 and #2 (340 MW total) by January 1, The 2022 date corresponds with the end of the jointowner operating agreements. The impacts of coal plant retirements were modeled under the mid and highload forecasts to understand future build decisions. It is important to note that for these scenarios, PNM modeled a forced retirement rather than allowing conditions to economically choose when to retire coal from the portfolio. In these scenarios, the plants were no longer available to meet the peak on their respective retirement dates, and O&M expenses associated with those units would not be counted after the retirement date in the calculation of the overall system costs; however, fixed costs were assumed recovered as a stranded asset. Additional decommissioning costs would apply to retirements but are not known and were not projected. HIGH COAL CAPITAL COSTS As the construction cost for most new power plants continues to rise, it is important to recognize the likelihood that actual costs may be higher than estimated, affecting the results of the analysis. This is true for generation technologies that are capital intensive, such as coal and nuclear facilities. During the course of creating the scenarios, several members of the Working Group raised concerns that the construction costs for new coal generation that PNM intended to use in scenario modeling were lower than they had expected. To address these concerns, PNM increased the estimated capital cost from $5,115/kW to $5,735/kW in 2010 dollars. All scenarios that included a high coal capital cost sensitivity used this higher cost. COAL FLY ASH REGULATION As discussed in detail in Section 4 of this IRP, the EPA released a proposed rule on the regulation of coal ash on May 4, The final ruling, expected in late 2012, may identify coal ash as a 124

137 Scenario Analysis PNM IRP hazardous waste. For purposes of this study, the IRP Working Group suggested that modeling coal ash as a hazardous material would have a cost impact for the handling and disposal of the fly ash. Therefore, two coal fly ash cost adders were created: a $20 per metric ton cost and a $100 per metric ton cost. These cost adders were used in scenarios that included coal fly ash regulation. DROUGHT CONDITIONS Water availability is an important concern in modeling future generation. The IRP Working Group suggested modeling a sensitivity based on a drought condition that would reducethe amount of generation from existing resources. To do so, PNM assumed three years of consecutive drought conditions from 2015 through 2017 in the Four Corners region. This timeframe was chosen because it is the period when PNM is expecting to need a new thermal resource, as reflected in the load and resources projections in Table 86 Load and Resources, and to capture any impacts drought could have on future resource selections. To model drought sensitivity, annual energy produced from all units at SJGS and the Four Corners Power Plant was curtailed by 10% for years 2015 through The 10% energy reduction did not affect the unit capacity contributions toward meeting the reserve margin of the system. Instead, the reduction was modeled to directly affect the energy availability of the units throughout the year. This assumption is with the existing operating practices at SJGS and Four Corners Power Plant. Both plants have onsite holding ponds for water pumped from the nearby San Juan and Animas rivers. Water stored in the ponds mitigates the effect of drought conditions by allowing the units to be operated at full or near full capacity if required to meet peak conditions, even when other water supplies are curtailed. NEW MEXICO GREENHOUSE GAS CAP RULE NMAC One scenario included the New Mexico GHG cap rule. In December 2010, the NM Environmental Improvement Board (EIB) approved an air quality regulation ( NMAC)(NM GHG Cap Rule) for a greenhouse gas reduction program that will become effective on January 1, 2013 or six months after the NM cap and trade regulation ( NMAC) ceases to be in effect, whichever is later. Rule 100 sunsets if a federal or regional greenhouse gas reduction program is in place, or ten years after its effective date. Rule 100 is currently under appeal to the courts. Under the NM GHG Cap Rule, all sources of CO 2 emissions within NMED s jurisdiction (greater than 25k metric tons per year) must reduce emissions according to a calculated annual maximum. The annual maximum, typically referred to as a cap, is undetermined and could be based on the emission portfolio profile from 2008, 2009 or PNM established a baseline proxy emissions level, which is equivalent to the consolidated emissions level for all affected PNM facilities (whether owned or contracted for under a longterm PPA) in calendar year Each year following the effective date of Rule 100, the cap declines by 3% of the baseline amount. For purposes of this cap, PNM excluded the Four Corners Power Plant because the plant is located on Native American land and is considered to be outside the jurisdiction of the NMED. Although facilities located within Bernalillo County are also not within NMED s jurisdiction, Bernalillo County typically follows the state regulations and therefore PNM s modeling included Reeves and DeltaPerson generating facilities for emissions reductions. 125

138 Scenario Analysis PNM IRP Under the NM GHG Cap Rule, there will be a standard carbon intensity equivalent limit of 0.5 metric ton per MWh in the first year of operation for any future generation resource. The carbon intensity rate for new generation declines by metric tons per MWh each year thereafter. The capability of the new generation units to meet the restricted carbon intensity standard is limited. Currently, only natural gas combined cycle plants rated for sea level conditions and renewable resources meet the new standard. Generation utilizing any type of gas turbine technology rated for typical NM site conditions would be excluded, since the output of the facility is reduced due to lower air density at higher elevations. This significantly limits the types of thermal resources that can be built within the NMED s jurisdiction. In light of this restriction, PNM assumed that all new fossil fueled resource alternatives would be constructed outside of NM, and would require the use of transmission facilities (i.e. wheeling).. To model this scenario, PNM assumed a transmission service wheeling rate cost of $1.97/kWmonth for full capacity of any new gas or coal facilities that were to be built to meet PNM s resource needs. This wheeling rate is a proxy for future transmission service and is based upon the APS Tariff Schedule 1 and Schedule 7 transmission service as of March However, the availability of transmission service over the already constrained Path 48 is questionable and the assumed wheeling cost could be greatly understated. Scenario Analysis Modeling The Strategist modeling tool is widely used in the electric industry to develop resource plans. This comprehensive resource planning tool allows the user to evaluate combinations of various types of resource options and compile up to 5,000 unique resource portfolios for a given study period. For a given set of sensitivity assumptions, it ranks the resulting resource portfolios according to NPV of total system cost. Strategist is capable of modeling a wide range of resource alternatives such as energy efficiency and demand side alternatives, storage technologies, renewable and thermal generating units, various types of power purchase and sales agreements, and an electric market. This modeling tool solves for the lowest cost combination of resources and dispatch mix based on cost assumptions for fuel, resource construction costs, plant efficiency, plant emission costs, and other data to meet a given load forecast and a given planning reserve margin. Strategist first uses the load forecast, or customer demand forecast to initialize the requirements that future resources will need to meet. Load modifying inputs, such as energy efficiency programs, and expected energy production from existing solar, wind and power transactions, are then used to reduce the peak demand and total energy required for a given scenario. Then, based on the various constraints and inputs, the model selects all combinations of available new resources to fulfill the demand and energy needs based on a binomial tree. Each combination of new resources, as previously discussed, is known as a portfolio. All resulting portfolios provide adequate energy generation to meet both peak demand and total energy required. After all portfolios are created, they are economically ranked, and a least cost portfolio results for the given scenario. For the scenario analysis, Strategist optimized resource additions within a prescribed planning reserve margin bandwidth of approximately 13% to 26%. The lower end of the reserve margin target is important, to ensure that all of the generated resource portfolios meet minimum system reliability requirements. In contrast, the upper limit of the reserve margin bandwidth was set high enough to allow the addition of larger capacity resources without compromising the 126

139 Scenario Analysis PNM IRP integrity of the 5,000 unique portfolio combination limit and biasing the results towards smaller units. A broader reserve margin bandwidth allows for large low cost resource alternatives to be selected. Since the Strategist model run times are directly related to the number of possible resource combinations, it was necessary to balance resource feasibility with expected portfolio results. To that end, PNM developed the following planning assumptions to constrain the model and reduce the amount of modeling time. Limited the number of all resource build options to one resource addition per year. Only one coal and one nuclear power facility could be chosen during the planning period. Only one of three energy efficiency forecasts (Low, Mid, or High) could be chosen starting in the first year of the study period. New DG resources were limited by conducting a bestinclass resource analysis. To accomplish this, all new DG resources were scaled up in size and cost and modeled as the only resources available in the modeling tool to meet future load growth, and were compared to obtain a most economic load serving resource. The resources competing with one another were the small PV w/battery technology, microturbine technology and fuel cell technology. As a result, Strategist chose the microturbine as the most economic DG technology. Therefore, the microturbine was set as the proxy for a DG resource, along with the other pool of resources that could meet reserve margin requirements for all scenarios in this analysis. Offsystem sales were not modeled as part of the scenario analysis. Some resources provide benefits such as more operational flexibility and greater system reliability that cannot be directly modeled. Strategist cannot currently optimize a resource portfolio based on New Mexico mandated renewable requirements that are not least cost. For this IRP, the required renewable resources to meet quantity, diversity and cost constraints are added into the model, based on annual energy requirements and costs. Additional information about Strategist is provided in Appendix E: Strategist Model Description. Results of Scenario Analysis PNM has compiled detailed reports identifying the results of the least cost portfolio for each of the 26 scenarios, and presented them in Tables 112 and 113 grouped by load forecast. A detailed table of the scenario results, which includes summaries of the leastcost portfolio resource build decisions and energy production mix, can be found in Appendix G. In Tables 112 and 113, the results for each portfolio include the following: The NPV in 2010 dollars of total system costs, including capital costs (billions of dollars) for new resource additions only, fuel, and O&M expenses for both existing PNM resources and any new resource additions The total plan period CO 2 emissions for both existing PNM resources and any new resource additions (millions of metric tons) The total plan period water usage for both existing PNM resources and any new resource additions (millions of gallons) The total plan period loss of load hours. This is intended to quantify the relative reliability of a portfolio (hours). 127

140 Scenario Analysis PNM IRP TABLE 112: MID LOAD SCENARIO ANALYSIS SUMMARY Load Forecast Low Load Mid Load X X X X X X X X X X X X X X X X X X X High Load Mid Load with Electric Vehicle Carbon Cost $8/metric ton CO2 Cost (2010) X $20/metric ton CO2 Cost (2010) X $40/metric ton CO2 Cost (2010) X $35/metric ton CO2 Cost with Allowances (2012) X X X X X X X X X X X X X $100/metric ton CO2 (2018) X Fuel Mid Natural Gas Forecast X X X X X X X X X X X X X X X High Natural Gas Forecast X X X X Capital Cost High PC w/carbon Capture X X X X Environmental SCR for SJGS X SCR for SJGS/FCGS X X X X X X SNCR for SJGS/FCGS X $20/ton Fly Ash Cost X $100/ton Fly Ash Cost X X X Water Curtailment X NM GHG Cap Rule X Other Retire 200 MW of Coal Generating Resource X Retire 340 MW of Coal Generating Resource X NPV of Least Cost Plan (billions) $6.781 $7.863 $9.439 $6.786 $6.263 $7.232 $6.786 $7.169 $7.616 $8.245 $7.281 $7.673 $6.982 $7.133 $8.245 $6.023 $6.814 $6.789 $6.485 CO2 Emitted (millions of metric tons) Water usage (millions of gallons) 98,886 93,057 77,361 82,890 63,316 92,110 82,890 82,835 91,998 85,257 81,582 72,404 74,057 73,789 85,257 99,976 82,890 82,226 78,523 Loss of Load Hours (hours)

141 Scenario Analysis PNM IRP TABLE 113. LOW LOAD, HIGH LOAD & MIDLOAD W/ ELECTIC VEHICLE SCENARIO ANALYSIS SUMMARY Scenario Number Load Forecast Low Load X X Mid Load High Load X X X X Mid Load with Electric Vehicle X Carbon Cost $8/metric ton CO2 Cost (2010) $20/metric ton CO2 Cost (2010) $40/metric ton CO2 Cost (2010) $35/metric ton CO2 Cost with Allowances (2012) X X X X X X X $100/metric ton CO 2 (2018) Fuel Mid Natural Gas Forecast X X X X X High Natural Gas Forecast X X Capital Cost High PC w/carbon Capture Environmental SCR for SJGS X SCR for SJGS/FCGS X SNCR for SJGS/FCGS $20/ton Fly Ash Cost $100/ton Fly Ash Cost X Water Curtailment NM GHG Cap Rule Other Retire 200 MW of Coal Generating Resource X Retire 340 MW of Coal Generating Resource X NPV of Least Cost Plan (billions) $6.234 $6.719 $7.765 $7.944 $8.123 $8.335 $6.823 CO2 Emitted (millions of metric tons) Water usage (millions of gallons) 85,026 68,571 82,726 75,396 75,886 96,677 83,292 Loss of Load Hours (hours) RESPONSE TO LOAD SENSITIVITIES The load forecasts modeled in this scenario analysis drive the timing and type of new resource additions. The scenario analysis was composed of 19 scenarios integrating the mid load forecast, two scenarios integrating the low load forecast, four scenarios integrating the high load forecast and one scenario with a mid load forecast and electric vehicle impacts. The results are described in the following paragraphs and shown on Figure 111. MID LOAD FORECAST The mid load forecast was used for the majority of scenarios in this analysis. In all mid load scenarios, the first new resource needed to meet planning reserve margin requirements was added in All of the mid load forecast scenarios, except scenario 19 (NM GHG Cap Rule), required eight to ten new resources in the 20year study period to serve the load. Scenario 19 resulted in larger and fewer resource additions that accommodated redispatch of higher CO2 intensity resources with those of lower intensities. The resource mix in the mid forecast scenarios was typically composed of gas turbines, wind, and solar PV. Even under extreme environmental and/or fuel costs such as scenarios 5, 6, 9, 10, 12, & 15, the least cost portfolio did not meet the RPS standard even though more renewable resources were included. High natural gas prices resulted in immediate development of new wind resources to offset increased fuel costs; however, these new wind resources did not include the likely cost of system regulation that would also be incurred. 129

142 Scenario Analysis PNM IRP LOW LOAD FORECAST Very few new resources were required in the low load forecast scenarios. Both scenarios (20 and 21) required only six new resources in the study period. Renewable resources are added, but are not enough for RPS compliance. Similar to the mid load scenarios, the resource mixes in these scenarios were typically gas turbines, wind, and solar PV with higher gas prices resulting in more renewable development. HIGH LOAD FORECAST High load forecast scenarios (22, 23, 24 and 25) resulted in the need for many new resources in the 20year study period. Besides the gas turbines and renewable additions included in the mid load forecast portfolios, the portfolios derived from the high load forecast included intermediate /baseload combined cycle natural gas additions. Eleven to thirteen new resources were required in the study period, beginning in 2013, which is a two year acceleration of the first resource addition compared in the mid load forecast scenarios. For all high load scenarios, an 80 MW solar PV addition in 2013 is followed by a gas turbine. The solar build decision is not based on least cost, but rather because of the longer lead times needed to construct other resources. Given that the baseload resources such as SJGS, Four Corners Power Plant and PVNGS operate close to their maximum levels, the high load scenarios resulted in higher total system costs (when compared to the mid load scenarios) since more new resources were required to meet the higher customer demands. Unlike the mid load and low load scenarios, more combined cycle type additions were required in the study period due to high yearoveryear load growth in both demand and energy. Therefore, with higher customer demands the type of new resource needed changed from peaking resources (gas turbines) that provide mainly summer capacity to intermediate/baseload combined cycle generation which provides more economical energy, as well as meeting capacity needs. TABLE 114 LOW, MID, HIGH AND MID WITH ELECTRIC VEHICLE LOAD FORECAST COMPARISON Scenario (21) Inputs Scenario (4) Inputs Scenario (22) Inputs Scenario (26) Inputs Load Gas CO2 Other Load Gas CO2 Other Load Gas CO2 Other Load Gas CO2 Other SCR at SJGS & FCGS Low Mid $35 $100 Fly Ash Mid Mid $35 High Mid $35 Mid with Electric Vehicles Scenario (21) Outputs Scenario (4) Outputs Scenario (22) Outputs Scenario (26) Outputs NPV Least Cost Plan (Billions of Dollars) CO2 Emitted (Millions of Metric Tons) Water (Millions of Gallons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO2 Emitted (Millions of Metric Tons) Water (Millions of Gallons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO2 Emitted (Millions of Metric Tons) Water (Millions of Gallons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) Mid $35 CO2 Emitted (Millions of Metric Tons) Water (Millions of Gallons) $ , $ , $ , $ , Scenario (21) Least Cost Portfolio Scenario (4) Least Cost Portfolio Scenario (22) Least Cost Portfolio Scenario (26) Least Cost Portfolio Year Resource Additions Year Resource Additions Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency High 2011 Energy Efficiency High 2011 Energy Efficiency High Solar PV (80 MW) Gas Turbine (177 MW) Gas Turbine (177 MW) Gas Turbine (177 MW) Combined Cycle (252 MW) Solar PV (40 MW) Solar PV (40 MW) Gas Turbine (177 MW) 2021 Wind (100 MW) 2021 Gas Turbine (177 MW) 2022 Wind (100 MW) Gas Turbine (177 MW) Gas Turbine (177 MW) 2023 Wind (100 MW) Wind (100 MW) Wind (100 MW) 2024 Gas Turbine (177 MW) 2024 Wind (100 MW) Gas Turbine (177 MW) Gas Turbine (177 MW) 2026 Wind (100 MW) Combined Cycle (252 MW) Wind (100 MW) 2027 Gas Turbine (85 MW) Gas Turbine (85 MW) 2028 Gas Turbine (40 MW) Solar PV (40 MW) 2029 Gas Turbine (40 MW) 2029 Gas Turbine (177 MW) 2029 Gas Turbine (40 MW) 2030 Gas Turbine (40 MW) 2030 Gas Turbine (85 MW) 2030 Gas Turbine (40 MW) 2030 Gas Turbine (85 MW) Loss of Load Hours 130

143 Scenario Analysis PNM IRP MID LOAD FORECAST WITH ELECTRIC VEHICLES PNM also explored the portfolio impact due to changing load profiles associated with electric vehicles. The results of scenario 26 showed little impact when evaluated with the comparison case scenario 4, even when New Mexico adoption rates for PEVs were modeled at very aggressive values. In later years, when the market reaches maturity, the effects of aggressive adoption rates are shown to accelerate the addition of one gas turbine from 2028 to Since shortterm decisions are unaffected, PNM will monitor the industry periodically to determine if the PEV market changes dramatically, and will reassess in the 2014 IRP. EFFECTS OF ENERGY EFFICIENCY Scenario analysis included low, mid and high forecasts for future energy efficiency resources which are 20year resource projections. The mid and high energy efficiency forecasts meet the minimum EUEA compliance requirements. The low energy efficiency forecast was created to reflect possible reduced targets for energy efficiency savings or higher program cost requirements that do not meet the TRC. The low energy efficiency forecast does not meet the minimum EUEA targets. The Strategist model chose one of the three energy efficiency forecasts as a 20year resource in the first year of the study period. The model chose the energy efficiency forecast that results in the least cost portfolio over the entire 20year period. For a majority of the scenario analysis, the following energy efficiency trends emerged: The low energy efficiency forecast was never chosen in a least cost portfolio, not even in scenario 16 where there are no environmental penalties on other resources. The mid energy efficiency forecast was chosen for CO 2 cost sensitivities of $20/metric ton or lower, such as in scenarios 1 and 2. Based on the projected costs for new energy efficiency programs and moderate environmental costs, the benefit of adding a higher amount of energy efficiency to the system is less than the costs. The high energy efficiency forecast was chosen for CO 2 cost sensitivities of $35/metric ton or higher such as scenarios 3 and 4. For these scenarios, a significant operational cost adder is applied to all existing and new fossil fuel resources. The increased cost of energy to customers is offset by lower cost energy efficiency programs. The only exception to this trend was for scenario 23; which is fully explained in the Retirement of Coal Facilities section. The high energy efficiency forecast was chosen for all high natural gas price sensitivities. Under these scenarios, the higher amounts of energy efficiency provide value to the system by offsetting more costly gas generation. Additionally, PNM analyzed increasing LM resources 20 MW above the existing DR contract amounts to determine if this could defer the 2015 natural gas resource. As shown in Figure 111, the results of scenario 4b are compared to scenario 4a. The additional LM resource serves to delay the gas turbines needed in 2017, 2022 and 2025 by one year each, but not the 2015 or 2016 turbines. Assuming LM could be added at prices comparable to the existing DR contracts, system costs were decreased by approximately $29 million over the 20year study period, making this a more cost effective resource option in 2017 if the additional LM resource could be procured. 131

144 Scenario Analysis PNM IRP FIGURE 111. EFFECTS OF 20 MW LOAD MANAGEMENT IN 2015 Scenario (4a) Inputs Scenario (4b) Inputs Load Gas CO2 Other Load Gas CO2 Other Mid Mid $35 40 MW CT added in 2015 & 2016 Mid Mid $35 40 MW CT added in 2015 & MW Additional DM beginning in d 4a 4e 4b Scenario (4a) Outputs Scenario (4b) Outputs NPV Least Cost Plan (Billions of Dollars) CO2 Emitted Metric Tons) Water Gallons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO2 Emitted Metric Tons) Water Gallons) Loss of Load Hours $ , $ , Scenario (4a) Least Cost Portfolio Scenario (4b) Least Cost Portfolio Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency High Gas Turbine (40MW) 2015 Gas Turbine (40MW) 2016 Gas Turbine (40MW) 2016 Gas Turbine (40MW) 2017 Gas Turbine (177MW) Gas Turbine (177MW) Wind (100MW) 2022 Gas Turbine (177MW) 2022 Wind (100MW) Gas Turbine (177MW) 2024 Wind (100MW) Gas Turbine (177MW) Wind (100MW) 2026 Gas Turbine (177MW) Gas Turbine (85MW) 2029 Gas Turbine (85MW) 2030 Gas Turbine (85MW) 2030 Solar PV (40MW) Similar results were evident in scenario 16c and scenario 20a. The additional 20 MW of DR resource, which decreases the capacity requirements on an annual basis, served to delay the construction of future resources. Overall, the benefits of delaying the construction of resources by one year over the 20 year study period were small in these scenario comparisons. However, if larger increments of DR resource could be procured in the future, cost savings to PNM and its customers could be considerable. RESPONSE TO NATURAL GAS PRICE SENSITIVITIES As discussed earlier, mid and high natural gas price curves were used as sensitivities in this scenario analysis. The high gas sensitivity was used for seven of the scenarios and the remainder of the scenarios modeled the mid gas sensitivity. The scenarios with high gas sensitivity resulted in renewable resource additions (solar PV and wind) consistently being added to portfolios earlier in the study period to hedge against high gas prices; however, these renewable additions did not meet the full RPS requirements. The early study period additions reflect the economic value renewables 132

145 Scenario Analysis PNM IRP provide by offsetting the operation of higher cost gas resources. The comparison of scenario 4 (mid gas) and scenario 6 (high gas) is illustrated in Figure 112. Scenario (4) Inputs FIGURE 112. MID AND HIGH GAS COMPARISON Scenario (6) Inputs Load Gas CO 2 Other Load Gas CO 2 Other Mid Mid $35 Mid High $ Scenario (4) Outputs Scenario (6) Outputs NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Metric Tons) Water Gallons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Metric Tons) Water Gallons) Loss of Load Hours $ , $ , Scenario (4) Least Cost Portfolio Scenario (6) Least Cost Portfolio Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency High Wind (100 MW) Gas Turbine (177 MW) 2015 Solar PV (40 MW) Gas Turbine (177 MW) Wind (100 MW) Solar PV (40 MW) Gas Turbine (177 MW) 2021 Gas Turbine (177 MW) Wind (100 MW) Wind (100 MW) Gas Turbine (177 MW) 2025 Gas Turbine (177 MW) Gas Turbine (85 MW) 2028 Gas Turbine (85 MW) 2029 Gas Turbine (40 MW) 2029 Gas Turbine (40 MW) 2030 Gas Turbine (85 MW) 2030 Gas Turbine (85 MW) The addition of the large gas turbine (177 MW) was the most prevalent in all scenarios even though this results high reserve margins immediately following the addition. This natural gas resource provides large amounts of capacity for the capital cost assumed in this analysis. Smaller gas turbines, such as a 40 MW aeroderivative and an 85 MW small gas turbine, typically were added in later years of leastcost portfolios mainly because the number of large gas turbines that were allowed to be added in the study period was restricted to three resources. The gas price sensitivities did not have a major impact on the type of gas resources that were selected. Scenarios including the high gas sensitivity still resulted in the addition of gas turbines in the near term. This indicates that the addition of gas turbines remains a flexible portfolio option, even when gas prices are high since most of the energy growth from the load forecast is met with energy efficiency savings and gas capacity is needed to meet peak demand. Conversely, energy driven generation additions such as combined cycle units were also added in high gas sensitivity scenarios and under high load conditions. 133

146 Scenario Analysis PNM IRP RESPONSE TO CO2 COSTS The addition of CO2 costs to existing generation and new generation additions has several impacts on the timing and type of resources added. The scenario analysis shows that CO2 sensitivities with a cost of $20/metric ton or less have no impact on future resource build decisions; however, significantly increase operating costs that customers must pay. For example, comparing scenarios 1, 2 and 16 shows the same resource build decisions; however, the overall system costs increase. This is directly attributed to the CO 2 costs. As shown in Figure 113, the increasing CO 2 costs in scenarios 3 and 4 show the need for a gas turbine in Scenario 5 contains carbon costs of $100/metric ton, and the resource need remains unchanged in However, solar PV and wind generation are added earlier in the study period to offset existing CO 2 emitting resources. At these CO 2 levels, higher emitting resources in the fleet, such as coal, are operated at lower output levels or for fewer hours each. Also, since solar PV is added in 2015, enough capacity (22 MW x 55%) is added to the system to delay building a gas turbine until The addition of this solar PV resource resulted from the economic benefit to the system, and indirectly delays the gas turbine construction. Another impact to the very high CO 2 cost in scenario 5 is the change in type of resource needed in 2021 from a gas turbine to a combined cycle turbine. Since the carbon intensity of a generic combined cycle is less than a gas turbine, a combined cycle unit is added to the leastcost portfolio to offset higher emitting existing resources. The scenario analysis shows that CO 2 cost sensitivities do not affect the need for a gas turbine in the near term, unless CO 2 costs are very high. CO 2 costs of $100/metric ton have an impact on the resource type needed in later years. 134

147 Scenario Analysis PNM IRP FIGURE 113. CO 2 EMISSION COST COMPARISON Scenario (4) Inputs Scenario (3) Inputs Scenario (5) Inputs Load Gas CO 2 Other Load Gas CO 2 Other Load Gas CO 2 Other Mid Mid $35 Mid Mid $40 Mid Mid $ Scenario (4) Outputs Scenario (3) Outputs Scenario (5) Outputs NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Water Metric Gallons) Tons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Water Metric Gallons) Tons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Water Metric Gallons) Tons) $ , $ , $ , Scenario (4) Least Cost Portfolio Scenario (3) Least Cost Portfolio Scenario (5) Least Cost Portfolio Year Resource Additions Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency High 2011 Energy Efficiency High Wind (100 MW) Gas Turbine (177 MW) 2015 Gas Turbine (177 MW) 2015 Solar PV (40 MW) Wind (100 MW) 2016 Gas Turbine (177 MW) Wind (100 MW) Wind (100 MW) Solar PV (40 MW) 2020 Solar PV (40 MW) Gas Turbine (177 MW) 2021 Gas Turbine (177 MW) 2021 Combined Cycle (252 MW) Wind (100 MW) Wind (100 MW) Gas Turbine (177 MW) 2025 Gas Turbine (177 MW) Gas Turbine (85 MW) Solar PV (40 MW) 2028 Gas Turbine (85 MW) 2028 Gas Turbine (85 MW) 2028 Gas Turbine (177 MW) 2029 Gas Turbine (40 MW) 2029 Gas Turbine (40 MW) Gas Turbine (85 MW) 2030 Gas Turbine (85 MW) 2030 Loss of Load Hours EFFECTS OF ENVIRONMENTAL UPGRADES The addition of environmental upgrades such as SCR or SNCR technology in the scenario analysis had no direct impact on the timing or amount of resources added for a given scenario. Since SCR or SNCR technology has no direct impact on CO 2 emissions or dispatch of units, the operation of the existing SJGS and Four Corners Power Plant units were identical whether environmental upgrades were added or not. The added costs for environmental upgrades however, do have a direct impact on the total system cost, which would eventually be passed on to PNM customers. When comparing the results of scenario 4 with scenario 8 (SCR SJGS and Four Corners Power Plant), portfolio build decisions are unchanged, including the system dispatch models. The same result applies when comparing scenario 4 with scenario 17 (SNCR on SJGS). Conversely, the total system costs, or NPV of the least cost plans, are more expensive when adding SCR technology. In this IRP, PNM did not model immediate retirement of coal units in response to a potential determination in the EPA regional haze rulings, because alternate resources are not currently or immediately available to replace 1000 MW of PNM coal facilities. PNM has modeled a 2017 retirement which provides insight into the reasonableness of continuing coal operations. Comparing scenarios 13 and 4 shows that retiring 200 MW of coal in 2017 would result in approximately $200 million of increased cost, whereas the additional cost of a SCR technology for that 200 MW of coal would only be $66 million. Therefore, PNM would continue operation of its coal facilities even if customers must bear the large economic burden of SCR costs. 135

148 Scenario Analysis PNM IRP RETIREMENT OF COAL FACILITIES Scenario 13 (mid load) and scenario 23 (high load) simulated the forced retirement of 200 MW of coal generation from PNM s existing fleet. These scenarios were modeled to reflect the elimination of capacity and energy generated from Units 4 and 5 of Four Corners Power Plant. The effects of modeling the retirement of more coal from the portfolio is simulated in scenario 14 for the mid load and scenario 24 for high load. The coal retirement scenarios are independent of the scenarios previously described dealing with the installation of SCR or SNCR environmental equipment. Joint owner and coal supply contractual obligations preclude retirement prior to certain dates (2017 and 2022). Installation of SCR or SNCR would be required sooner than those dates. Therefore, the retirement scenarios would still incur those environmental costs. The retirement of Four Corners Power Plant units 4 and 5 (200 MW total) along with the mid load sensitivity, resulted in Strategist choosing a combined cycle unit (252 MW) to replace the baseload facilities. As shown in Figure 114, the total system costs, or NPV of least cost plan, are higher with the Four Corners Power Plant retirement when comparing this sensitivity with the comparative case (scenario 4). The Four Corners Power Plant retirement is approximately $190 million dollars more expensive than the case without the retirement. This was an expected outcome since a low operating cost resource, such as coal, is being replaced with a higher cost natural gas combined cycle generation. Even when CO 2 costs are high, the cost of constructing new generation is more costly than keeping the existing Four Corners Power Plant and paying increased operating costs associated with CO

149 Scenario Analysis PNM IRP FIGURE 114. FOUR CORNERS RETIREMENT COMPARISON MID LOAD Scenario (4) Inputs Scenario (13) Inputs Load Gas CO 2 Other Load Gas CO 2 Other Mid Mid $35 Mid Mid $35 Retire 200MW at FCGS in Scenario (4) Outputs Scenario (13) Outputs NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Metric Tons) Water Gallons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Metric Tons) Water Gallons) Loss of Load Hours $ , $ , Scenario (4) Least Cost Portfolio Scenario (13) Least Cost Portfolio Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency High Gas Turbine (177 MW) 2015 Gas Turbine (177 MW) Combined Cycle (252 MW) Solar PV (40 MW) Gas Turbine (177 MW) 2021 Gas Turbine (177 MW) Wind (100 MW) Wind (100 MW) Gas Turbine (177 MW) 2025 Gas Turbine (177 MW) Wind (100 MW) Wind (100 MW) 2028 Gas Turbine (85 MW) 2028 Gas Turbine (40 MW) 2029 Gas Turbine (40 MW) 2029 Gas Turbine (85 MW) 2030 Gas Turbine (85 MW) 2030 Solar PV (40 MW) These results show a similar resource mix in the early years of both scenarios. As seen in Figure 11 4, the combined cycle unit is added in 2017 for scenario 13. Since the replacement generation is larger in size (252 MW) than the retired resource capacity (200 MW), the build decisions later in the study period are affected and are different than in scenario 4. In scenario 4, energy from the load forecast is being met with energy efficiency. When baseload generation is removed from the portfolio as in scenario 13, the most economical choice from the pool of resource options is a combined cycle unit. Since combined cycle units cannot be sized to fit a particular capacity, and it is larger than the 200 MW retired capacity, it eliminates the need for solar in 2020 since it can provide adequate energy. Furthermore, the least cost portfolio indicates that the additional capacity is not enough to defer gas turbines in the later years, but is enough to defer the construction of renewable resources. With the retirement of Four Corners Power Plant units under the high load sensitivity, the Strategist model also chooses a combined cycle unit as a replacement. Contrasting the retirement 137

150 Scenario Analysis PNM IRP sensitivity with the comparative case (scenario 22) in Figure 115, the total system costs are greater with the Four Corners Power Plant retirement. In general, the cause and effect of the retirement under the high load case is similar to the mid load case retirement. The only major difference is that the mid energy efficiency forecast is chosen instead of the high energy efficiency program. This is a direct result of two factors: the timing of the retirement and demand savings from the energy efficiency forecasts. The retirement of Four Corners Power Plant in 2017 is one year earlier than the next most economical resource addition. The requirement to replace 200 MW, in addition to load growth in the high load forecast case, accelerates the build decisions after 2018 by three years. Since the delta between the replacement of coal generation and generic combined cycle is greater than the need by 52 MW, it accelerates the timing for future resource additions. This becomes especially important in later years. Because the energy efficiency forecasts do not deviate from each other (under the mid and high EE cases) until after 2020, savings from the high EE forecast are not needed and therefore would be more costly. For this reason, the mid energy efficiency case is chosen in the least cost portfolio. FIGURE 115. FOUR CORNERS RETIREMENT COMPARISON HIGH LOAD Scenario (22) Inputs Scenario (23) Inputs Load Gas CO 2 Other Load Gas CO 2 Other High Mid $35 High Mid $35 Retire 200MW at FCGS in Scenario (22) Outputs Scenario (23) Outputs NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Metric Tons) Water Gallons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Metric Tons) Water Gallons) Loss of Load Hours $ , $ , Scenario (22) Least Cost Portfolio Scenario (23) Least Cost Portfolio Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency Mid Solar PV (80 MW) 2013 Solar PV (80 MW) 2014 Gas Turbine (177 MW) 2014 Gas Turbine (177 MW) Combined Cycle (252 MW) 2018 Combined Cycle (252 MW) 2018 Wind (100 MW) Gas Turbine (177 MW) Wind (100 MW) 2021 Solar PV (40 MW) 2022 Gas Turbine (177 MW) 2022 Combined Cycle (252 MW) Gas Turbine (177 MW) Gas Turbine (177 MW) 2026 Combined Cycle (252 MW) 2026 Gas Turbine (40 MW) 2027 Wind (100 MW) 2027 Combined Cycle (252 MW) 2028 Gas Turbine (40 MW) Gas Turbine (177 MW) 2029 Gas Turbine (177 MW) 2030 Gas Turbine (40 MW) 2030 Wind (100 MW) 138

151 Scenario Analysis PNM IRP The decommissioning costs at Four Corners Power Plant are not captured in either the mid or high load retirement comparisons. PNM has not identified the decommissioning costs that would arise from an early shutdown. These costs would need to be added, resulting in an increase to the overall system costs in scenarios 13 and 23. The effects of forcing retirement of larger amounts of coal generated capacity from PNM s existing portfolio were also analyzed in scenario 14 for mid load and scenario 24 for high load. These scenarios were modeled to reflect the retirement of capacity and energy generated from Units 1 and 2 of the SJGS. The retirement of SJGS Units 1 and 2 (340 MW total) in conjunction with the mid load sensitivity resulted in a combined cycle unit to replace the coal generation. Figure 116 identifies the total system costs to be higher with the coal generation retirement, compared to continuing the operation of the coal facilities (scenario 4). The SJGS retirement is approximately $340 million dollars more expensive than the case without the retirement. Similar to the Four Corners Power Plant retirement, the low operating cost of coal resource is being replaced with a higher cost natural gas combined cycle unit. Even when CO 2 costs are high, the cost of constructing new generation is more costly than keeping the existing SJGS and paying increased operating costs associated with CO 2. As seen in scenario 14, the near term resource builds are identical; however gas turbines are also needed earlier in the study period to accommodate the retirement. This is a result of retiring 340 MW of resources and replacing them with 252 MW of resources. FIGURE 116. SAN JUAN RETIREMENT COMPARISON MID LOAD Scenario (4) Inputs Scenario (14) Inputs Load Gas CO 2 Other Load Gas CO 2 Other Mid Mid $35 Mid Mid $35 Retire 340MW at SJGS in Scenario (4) Outputs Scenario (14) Outputs NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Water Metric Gallons) Tons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Water Metric Gallons) Tons) Loss of Load Hours $ , $ , Scenario (4) Least Cost Portfolio Scenario (14) Least Cost Portfolio Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency High Gas Turbine (177 MW) 2015 Gas Turbine (177 MW) Wind (100 MW) 2020 Solar PV (40 MW) 2020 Solar PV (40 MW) 2021 Gas Turbine (177 MW) 2021 Gas Turbine (177 MW) Combined Cycle (252 MW) 2023 Wind (100 MW) 2023 Gas Turbine (40 MW) 2024 Wind (100 MW) 2024 Gas Turbine (177 MW) 2025 Gas Turbine (177 MW) Gas Turbine (85 MW) 2028 Gas Turbine (85 MW) 2028 Gas Turbine (85 MW) 2029 Gas Turbine (40 MW) Gas Turbine (85 MW) 2030 Combined Cycle (252 MW) 139

152 Scenario Analysis PNM IRP For the retirement of SJGS units in conjunction with the high load sensitivity, the Strategist model also chooses a combined cycle unit to replace the coal generation. Figure 117 identifies the total system costs to be higher with the San Juan retirement compared to not retiring the coal facilities (scenario 4). The retirement under the high load sensitivity results are similar to the results of the mid load sensitivity. The savings realized by retiring the coal facilities do not overcome the cost of replacing the generation with new intermediate gas generation. Contrasting against the retirement of 200 MW of Four Corners Power Plant capacity, the energy efficiency selection is much different. The three additions in the timeframe account for a larger percentage of the requirement needed to meet the deficit by the load growth and elimination of coal. To meet the reserve margin, only a small amount of capacity is required and therefore, it is more economical to meet that with energy efficiency rather than add an additional thermal resource which would far exceed the need in that year. Because thermal units cannot be sized to fit an exact match to the load, the model finds the most economical path to achieve the reserve margin requirements. FIGURE 117. SAN JUAN RETIREMENT COMPARISON HIGH LOAD Scenario (22) Inputs Scenario (24) Inputs Load Gas CO 2 Other Load Gas CO 2 Other High Mid $35 High Mid $35 Retire 340MW at SJGS in Scenario (22) Outputs Scenario (24) Outputs NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Metric Tons) Water Gallons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Metric Tons) Water Gallons) Loss of Load Hours $ , $ , Scenario (22) Least Cost Portfolio Scenario (24) Least Cost Portfolio Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency High Solar PV (80 MW) 2013 Solar PV (80 MW) 2014 Gas Turbine (177 MW) 2014 Gas Turbine (177 MW) Combined Cycle (252 MW) 2018 Combined Cycle (252 MW) Wind (100 MW) 2021 Gas Turbine (177 MW) 2022 Gas Turbine (177 MW) 2022 Combined Cycle (252 MW) Gas Turbine (85 MW) 2024 Gas Turbine (177 MW) 2024 Gas Turbine (177 MW) Solar PV (40 MW) 2026 Combined Cycle (252 MW) 2026 Gas Turbine (85 MW) 2027 Wind (100 MW) 2027 Combined Cycle (252 MW) 2028 Gas Turbine (40 MW) Gas Turbine (177 MW) 2029 Gas Turbine (177 MW) 2030 Gas Turbine (40 MW)

153 Scenario Analysis PNM IRP Because of joint ownership issues related to pursuing a retirement at SJGS, 2022 was used as the most feasible retirement year, and it was assumed that a supply of coal could be obtained through that date. This year coincides with the expiration of the Project Participation Agreement, which is an agreement between all joint owners of the plant that defines the operational duties for the plant. As with the Four Corners retirement sensitivities, early decommissioning would result in increased costs for the SJGS retirement scenarios. EFFECT OF HIGH COAL CAPITAL COSTS Since the results for the scenario analysis did not include the addition of a coalfired resource, the sensitivity of increasing the capital cost of a coalfired facility had no effect on the results. EFFECTS OF COAL FLY ASH COSTS Impacts of coal fly ash regulation were modeled in scenario 11 for a low cost adder, and scenarios 10, 12, and 21 for a high cost adder. For these scenarios, a cost of $100/metric ton for the high case and $20/metric ton for the low case is added to the dispatch cost for all coal generation facilities. FIGURE 118. COAL FLY ASH SCENARIO COMPARISON HIGH LOAD Scenario (4) Inputs Scenario (11) Inputs Scenario (12) Inputs Load Gas CO 2 Other Load Gas CO 2 Other Load Gas CO 2 Other Mid Mid $35 Mid Mid $35 High Coal Capital SCR for SJGS & FCGS $20 Fly Ash Mid Mid $ Scenario (4) Outputs Scenario (11) Outputs Scenario (12) Outputs High Coal Capital SCR for SJGS & FCGS $100 Fly Ash NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Water Metric Gallons) Tons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Water Metric Gallons) Tons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Water Metric Gallons) Tons) Loss of Load Hours $ , $ , $ , Scenario (4) Least Cost Portfolio Scenario (11) Least Cost Portfolio Scenario (12) Least Cost Portfolio Year Resource Additions Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency High 2011 Energy Efficiency High Wind (100 MW) 2015 Gas Turbine (177 MW) 2015 Gas Turbine (177 MW) 2015 Solar PV (40 MW) Gas Turbine (177 MW) Wind (100 MW) 2020 Solar PV (40 MW) 2020 Solar PV (40 MW) Gas Turbine (177 MW) 2021 Gas Turbine (177 MW) 2021 Gas Turbine (177 MW) Wind (100 MW) Wind (100 MW) Wind (100 MW) 2024 Wind (100 MW) Gas Turbine (177 MW) 2025 Gas Turbine (177 MW) 2025 Combined Cycle (252 MW) Gas Turbine (85 MW) 2028 Gas Turbine (85 MW) Gas Turbine (40 MW) 2029 Gas Turbine (40 MW) 2029 Gas Turbine (40 MW) 2030 Gas Turbine (85 MW) 2030 Gas Turbine (85 MW) 2030 Gas Turbine (85 MW) 141

154 Scenario Analysis PNM IRP The $20/metric ton coal fly ash cost sensitivities had minor impacts to resource selections. In Figure 118, scenario 11 shows a similar resource selection to the comparative case, scenario 4. System costs increase as a result of the fly ash costs as fuel switching from coal to gas becomes more favorable due to penalties assessed on coal generation. For these scenarios, coal generation from Four Corners Power Plant and SJGS is reduced and intermediate gas generation, such as Afton and Luna, is fully loaded. The type of resource additions remain unchanged in the least cost portfolio compared to the scenario that did not include effects of coal regulation. In contrast, the $100/metric ton coal fly ash cost sensitivities had noticeable impacts to resource selections for the mid load cases. In Figure 118, scenario 12 results in adding renewable resources earlier to offset the fly ash cost to the coal units. A combined cycle unit is added in 2025 to help displace the high cost coal generation due to the fly ash cost. Overall, the coal fly ash cost sensitivities result in similar outcomes to the $35/metric ton CO 2 cost sensitivity adder. The fly ash costs increase dispatch costs of the coal units, which forces the system to operate higher cost gas turbines or combined cycles resulting in higher overall costs. This ultimately leads to renewable resource additions becoming more valuable in the later years and cost effective to displace a hazardous waste cost. EFFECTS OF A DROUGHT CONDITION The simulated drought conditions in scenario 18 served as the sensitivity for curtailing generation at SJGS and Four Corners Power Plant due to low water availability. The build decision due to the modeled water curtailments at SJGS and Four Corners Power Plant was identical to the comparative case in scenario 4, although the total system costs were slightly different. This is typically an effect of changing the dispatch. A closer look at the threeyear drought generation dispatch shows the reduction in output from both coal plants was compensated by intermediate gas generation at the Afton and Luna power plants and peaking gas turbines. Figure 119 illustrates the maximum capacity produced from the coal plants was not affected; only the energy produced throughout a given year was affected. The full capacity of these two coal plants can be counted towards planning reserve margin since the existing holding ponds mitigate drought conditions. PNM holds senior water rights contracts for both coal plants and, therefore, water curtailments for these two plants have a low probability. FIGURE 119. ENERGY PRODUCTION DURING WATER CURTAILMENT SENSITIVITY GWh GWh (San Juan + Four Corners) Luna + Afton All Other Combustion Turbines San Juan + Four Corners Year 0 142

155 Scenario Analysis PNM IRP A noticeable difference between scenario 18 and scenario 4 is the Loss of Load Hours (LOLH). The LOLH is a measurement of the ability to serve customer demands for a system of resources on an annual basis. In effect, this serves as an assessment of the level of reliability for a system as a whole. For the scenario analysis, the LOLH is calculated annually and summed for the 20year study period. This number is the value in Appendix G for each of the scenarios leastcost portfolios. In Table 114, the LOLH values are compared for years 2013 through 2019 (total hours shown is for 20year study period). The early and later years are purposely not shown to focus on years when the LOLH results in different values. For scenario 18, the high value of LOLH in years 2015 through 2017 characterize the system reliability for these three years. TABLE 115. LOSS OF LOAD HOURS COMPARISON FOR SCENARIOS 4 AND Total Scenario 4 LOLH Scenario 8 LOLH The decreased reliability due to a drought of this magnitude indicates that the current planning reserve margin target of 13% would not be adequate to serve load and maintain system reliability. Increasing reserve margin limits would help to stabilize system reliability since it usually results in adding additional resources. However, an increased planning reserve margin could cause construction of new resources which would ultimately result in an increased cost to PNM customers. NM GHG CAP RULE Scenario 19 contained the sensitivity pertaining to Rule 100. The declining annual emission limit requirements for existing and new resources are shown in Table 116. Based on these limits, the Strategist program then optimized the system for the 20year period. TABLE 116. NM GHG CAP RULE ESTIMATED CO 2 LIMITS FOR SCENARIO 19 NM GHG Cap Rule Estimated CO 2 Limits Year Beyond 2022 Metric Tons 5,440,107 5,276,904 5,113,700 4,950,497 4,787,294 4,624,091 4,460,888 4,297,684 4,134,481 3,971,278 3,971,278 The results for the least cost portfolio for this scenario are shown in Table 117. The resources chosen to meet load requirement in the future consist mainly of low CO2 emitting combined cycle generation, several gas turbines and a solar PV resource. The large combined cycle capacity additions reduce the amount of smaller gas turbines that would alternatively be added to meet customer demands. As discussed earlier in the Scenario Development section, all new nonrenewable resources added to the portfolio contain transmission wheeling costs for delivery of the energy along other utilities transmission systems to bring the energy to New Mexico loads. As a direct result, the cost of adding any new resource will be more expensive compared to other resources in other scenarios. The system costs for this scenario are not directly comparable to any other scenarios in this analysis; however, the cost increases due to the NM GHG rule could be compared to scenario 16 (Mid Load, Mid Gas, $0 CO 2). The NM GHG scenario NPV is approximately $460 million higher than scenario 16. This difference represents the minimum cost to customers if the Rule 100 was in effect. 143

156 Scenario Analysis PNM IRP Although the CO 2 emitted for the fleet of PNM generation in the NMED jurisdiction decreases for this scenario, the total emissions from combining all PNM generators is not significantly reduced since the least cost portfolio additions (which includes natural gas and not more renewables) are not counted in the NMED jurisdiction. TABLE 117. NM GHG RULE SCENARIO RESULTS Scenario (16) Inputs Scenario (19) Inputs Load Gas CO2 Other Load Gas CO2 Other Mid Mid $0 Mid Mid $0 NM GHG Cap Rule Scenario (16) Outputs Scenario (19) Outputs NPV Least Cost Plan (Billions of Dollars) CO2 Emitted Metric Tons) Water Gallons) Loss of Load Hours NPV Least Cost Plan (Billions of Dollars) NM CO2 Emitted Metric Tons) Other CO2 Emitted Metric Tons) Loss of Load Hours $ , $ Scenario (16) Least Cost Portfolio Scenario (19) Least Cost Portfolio Year Resource Additions Year Resource Additions 2011 Energy Efficiency Mid 2011 Energy Efficiency Mid Gas Turbine (177MW) 2015 Gas Turbine (177 MW) w/wheeling Gas Turbine (177MW) 2020 Combined Cycle (252 MW) w/wheeling Gas Turbine (177MW) Combined Cycle (252 MW) w/wheeling Gas Turbine (85MW) Gas Turbine (40MW) Gas Turbine (85MW) 2029 Solar PV (40 MW) 2030 Gas Turbine (40MW) 2030 Gas Turbine (85 MW) w/wheeling EMERGING TECHNOLOGIES Costs of emerging technologies are not yet competitive with those of existing technologies such as gas turbines, wind, and solar. Emerging technologies currently do not enjoy all the tax incentives provided to renewable resources. The DG bestinclass resource, the microturbine, was not chosen in any of the least cost portfolios. The capital cost for the amount of capacity it added to the system and heat rate could not overcome the economies of scale of larger centralized resources. The addition of a utility scale battery to PNM s existing system was also evaluated in the scenario analysis. The leadacid battery was assumed to be a 24 MW peak, 12 MWh rated with 85% efficiency,. PNM assumed cycling the battery once a day in the summer months (JuneSeptember) and four times per week all other months of the year. The assumed capital cost for the battery was approximately $1,400/MW, not including siting or transmission costs. This is a very favorable capital cost assumption compared to current pricing for this technology ($8,000/kW). Based on these assumptions, the Strategist model did not select the utility scale battery in the least cost 144

157 Scenario Analysis PNM IRP portfolio. In general, this type of resource does not provide enough economic benefit to the system to overcome the capital and operating costs of this technology. Although the microturbine and utility scale battery were not shown to be cost effective per the scenario analysis, PNM s Advanced Technology group stays current with emerging technologies and will be involved in future IRPs to inform the IRP Working Group of cost signals or benefits that may drive down costs for these technologies. In addition, special applications or system reliability situations may arise in the future that justify these resources. BASELOAD RESOURCES For this scenario analysis, the need for new baseload resources is generally required when customer demands follow the high load forecast or existing baseload resources are retired. When needed, the new baseload resource chosen is a natural gas combined cycle plant. New coal or nuclear resources were not chosen for any of the scenario leastcost portfolios, even with very high cost adders, such as coal fly ash or CO 2. Given the relatively low projection of gas prices under the mid and high gas sensitivities, the cost of the high coal or nuclear construction resources cannot compete against the favorable operating costs of today s new combined cycle generation. As discussed in Section 7, the ownership leases for PVNGS expire in 2015 and A sensitivity analysis of the expiration of these leases was conducted to determine whether lease extensions should be pursued in the future. Scenario 4 was used as a base scenario, modeling expiration of the ownership leases for PVNGS Units 1 and 2. This sensitivity assumes that PNM and the lessors agree to extend and terminate the leases as of January 1, This equates to a loss of 178 MW of generation from PVNGS Units 1 and 2 beginning in 2020, with 90 MW of PNM ownership remaining through the end of the study period. The results of this sensitivity show that the loss of the PVNGS leases are replaced by combined cycle generation. Not renewing/extending the leases beyond 2020 results in a cost of approximately $212 million more than the comparative scenario 4 system costs. This was expected since the zero carbon resource becomes more valuable if CO2 costs are assumed in the future. However, netted against this cost increase is $161 million in lease rental savings PNM would obtain if the leases were to expire. These cost savings would be equivalent to the lease payments PNM would otherwise be contracted to make if the leases were still in effect. A summary of the results of this analysis can be found in Appendix G, under scenario 4c. RENEWABLE RESOURCES AND RPS REQUIREMENTS The two most cost effective renewable resource additions from this scenario analysis are wind and solar PV. These two technologies are generally added to scenario leastcost portfolios to hedge against CO 2 costs, coal fly ash costs, and high gas prices. As costs increase, wind and solar technologies are added earlier in least cost portfolios. Under mid gas sensitivities and zero CO 2 costs, renewable technologies are not cost effective additions to the system, since they cannot economically compete against dispatchable, full capacity value resources such as gas turbines. Under the REA and Rule 572, utilities are directed to increase renewable energy investment toward target levels, but that investment is limited by the RCT. No portfolio is able to be compliant with both the targets and the cost limits under the scenarios examined. Therefore, for RPS analysis, two sets of target compliance scenarios were modeled to meet Rule 572 requirements. One set modeled meeting the RPS without regard to cost, operations, reliability or diversity (Quantity Compliance) 145

158 Scenario Analysis PNM IRP and the other modeled RPS with full quantity and diversity standards without regard for cost, operations, or reliability (Diversity Compliance). Both compliance cases were tested under scenario 6 (mid load, high gas, $35 CO2 cost) and scenario 16 (mid load, mid gas, zero CO2 cost). TABLE 118. SCENARIO 6 RPS COMPLIANCE SCENARIOS Scenario (6qty) Quantity RPS Analysis Inputs Scenario (6qly) Diversity RPS Analysis Inputs Load Gas CO2 Other Load Gas CO2 Other Mid High $35 Quantity RPS Compliance Mid High $35 Diversity RPS Compliance 6qty Scenario (6qty) Quantity RPS Analysis CO2 NPV Least Emitted Water Cost Plan (Billions of Metric Gallons) Dollars) Tons) Loss of Load Hours 6qly Scenario (6qly) Diversity RPS Analysis CO2 NPV Least Emitted Water Cost Plan (Billions of Metric Gallons) Dollars) Tons) Loss of Load Hours $ , $ , Least Cost Portfolio Least Cost Portfolio Year Resource Additions Year Resource Additions 2011 Energy Efficiency High 2011 Energy Efficiency Mid 2012 Wind (100MW) 2012 Solar PV (50MW) Wind (150MW) Solar PV (40MW) REC Purchase (15MW) Wind (50MW) 2016 Gas Turbine (177MW) 2015 Solar PV (40MW) Wind (50MW) Gas Turbine (177MW) Wind (200MW) Gas Turbine (177MW) 2018 Solar PV (10MW) REC Purchase (5MW) Wind (50MW) Solar PV (40MW) 2025 Gas Turbine (177MW) Wind (150MW) Wind (100MW) 2020 REC Purchase (5MW) Wind (100MW) Gas Turbine (40MW) Wind (100MW) Solar PV (30MW) REC Purchase (5MW) Gas Turbine (177MW) 2029 Gas Turbine (85MW) 2024 Solar PV (10MW) 2030 Gas Turbine (40MW) Gas Turbine (177MW) Solar PV (10MW) Wind (50MW) Gas Turbine (40MW) Solar PV (10MW) 2030 Gas Turbine (85MW) Wind was used as least cost in the Quantity Compliance case to meet the RPS, but solar technologies were allowed to be chosen if it was cost effective. Due to nearterm availability issues, no biomass, geothermal, or other nonwind/solar resources were used to meet the total renewable compliance standard for these scenarios. The Diversity Compliance case included meeting Rule 572 compliance according to diversity targets with each specified renewable type, and low cost wind was used to meet any discretionary renewable requirements. To meet the nonwind/nonsolar diversity requirement of Rule 572, a biomass/geothermal REC purchase was modeled as a proxy. For these scenarios, it is important to note that renewables are added to the portfolio without regard to cost and the RCT. Overall, there were five cases evaluated: scenario 6 Quantity, scenario 6 Diversity, scenario 16 Quantity, scenario 16 Diversity and scenario 2a (Most Cost Effective). The Quantity and Diversity scenarios do not take into account increased operating costs for regulation. The results for these scenarios are shown in Tables 118, 119 and As shown in Table 118, the amount of renewable resources needed to meet the REA diversity targets is substantially higher than meeting the RPS with the leastcost renewable. The cost 146

159 Scenario Analysis PNM IRP difference favors diversity; since, the costs assumed to meet the nonwind/nonsolar requirement for this scenario assume a REC purchase at $35/MWh to reflect the renewable attribute and not the underlying energy. This assumption was based upon a bestguess estimate of future market conditions for the purchase of a geothermal REC. If the nonwind/nonsolar requirement was met with a REC and energy purchase, the resulting cost of the scenario 6 Diversity would increase. Since the amount of nonwind/nonsolar requirements from the scenario 6 Diversity scenario are substantial, the cost increase would also be enough to push the total system costs greater than the scenario 6 Quantity least cost portfolio. Both scenarios in Table 118 are less costly than the comparative scenario 6 because full operational impacts were not factored into the Quantity and Diversity scenarios but were included in scenario 6 through the use of restricted resource combinations. TABLE 119. SCENARIO 16 RPS COMPLIANCE SCEANARIOS Scenario (16qty) Quantity RPS Analysis Inputs Scenario (16qly) Diversity RPS Analysis Inputs Load Gas CO2 Other Load Gas CO2 Other Mid Mid $0 Quantity RPS Compliance Mid Mid $0 Diversity RPS Compliance 16qty Scenario (16qty) Quantity RPS Analysis CO2 NPV Least Emitted Water Cost Plan (Billions of Metric Gallons) Dollars) Tons) Loss of Load Hours 16qly Scenario (16qly) Diversity RPS Analysis CO2 NPV Least Emitted Water Cost Plan (Billions of Metric Gallons) Dollars) Tons) Loss of Load Hours $ , $ , Least Cost Portfolio Least Cost Portfolio Year Resource Additions Year Resource Additions 2011 Energy Efficiency Mid 2011 Energy Efficiency Mid 2012 Wind (100MW) 2012 Solar PV (50MW) Gas Turbine (177MW) Wind (150MW) REC Purchase (15MW) Wind (50MW) Solar PV (40MW) Wind (50MW) Gas Turbine (177MW) Wind (200MW) Gas Turbine (177MW) 2018 Solar PV (10MW) REC Purchase (5MW) Wind (50MW) 2024 Gas Turbine (177MW) 2019 Solar PV (40MW) Wind (100MW) 2020 Wind (150MW) REC Purchase (5MW) 2027 Gas Turbine (85MW) 2021 Wind (100MW) Gas Turbine (40MW) Solar PV (40MW) Solar PV (30MW) REC Purchase (5MW) Gas Turbine (177MW) 2030 Gas Turbine (85MW) Solar PV (10MW) Gas Turbine (177MW) Solar PV (10MW) Wind (50MW) Gas Turbine (40MW) Solar PV (10MW) 2030 Gas Turbine (85MW) Under zero carbon cost scenarios, the amount of renewable resources needed to meet the REA diversity standards and the total quantity of requirements for the study period is similar to the previous two scenarios compared. As with the scenario 6 RPS compliance scenarios, the NPV cost 147

160 Scenario Analysis PNM IRP difference favors diversity, however the nonwind/nonsolar requirement for this scenario assumes a REC purchase at a cost of $35/MWh. In contrast to scenario 6 RPS compliance scenarios, RPS compliance scenarios are more costly than the comparative scenario 16 by a range of approximately $270$280 million over the 20year study period. TABLE SCENARIO 2A RESULTS Scenario (2a) Inputs Load Gas CO 2 Other Mid Mid $20 40 MW CT added in 2015 & 2016 RPS additions under RCT 2a Scenario (2a) Outputs NPV Least Cost Plan (Billions of Dollars) CO 2 Emitted Metric Tons) Water Gallons) Loss of Load Hours $ , Scenario (2a) Least Cost Portfolio Year Resource Additions Energy Efficiency Mid Wind (150 MW) Gas Turbine (40 MW) Gas Turbine (40 MW) Gas Turbine (177 MW) Wind (200 MW) Solar PV (40 MW) Gas Turbine (177 MW) Gas Turbine (177 MW) Gas Turbine (85 MW) Gas Turbine (85 MW) PNM evaluated an additional RPS compliance scenario that included smaller combustion turbines instead of a single large combustion turbine for the initial nonrenewable resource. This analysis was designated scenario 2a, shown in Table 1110, and detailed scenario results are shown in Appendix G. Scenario 2a used the same inputs from scenario 2 (mid load, mid gas, $20 CO 2 cost), and added aeroderivative gas turbines (40 MW each in 2015 and 2016) and wind resources (150 MW in 2014 and 200 MW in 2019). These resources were not economically selected by the model to meet the load serving requirements, however, are needed for operational flexibility, system regulation, and renewable compliance. By looking at the resource selections from scenario 2, the addition of the 177 MW turbine in 2015 is selected as the leastcost resource for the 2015 load and reserve margin requirements. The wind resources in scenario 2a were added to maximize renewable development under the RCT. The mid energy efficiency forecast and new gas (2017 and after) and solar resources were selected by the model as the leastcost resources to serve the load. 148

161 Scenario Analysis PNM IRP The results of scenario 2a show the need for a large combustion turbine in The load growth can be accommodated in 2017 with another 40 MW aeroderivative gas turbine; however, the increasing load and reserve margin requirements will eventually require multiple aeroderivative gas turbine installations or the larger 177 MW unit. Scenario 2a is approximately $126 million more expensive than scenario 2 over the 20year study period. Most of these costs are attributed to the cost of adding renewable resources to meet the RPS. Approximately 30% of the cost (roughly $40 million dollars) over the study period is a result of replacing the 177 MW combustion turbine in 2015 with two aeroderivative gas turbines in 2015 and SCENARIO ANALYSIS CONCLUSIONS COMMON RESULTS All existing PNM resources are least cost over the twenty year planning period. Environmental regulations do not materially change resource selection, but do result in increased customer costs. Energy efficiency is least cost at mid or high levels depending on the scenario. For all mid load scenarios, a gas turbine is needed in 2015 to meet peak demand requirements. For all high load scenarios, a 50 MW resource is needed in year 2013 and natural gas combined cycle is needed as early as 2017 to meet growth in energy requirements. Coal, nuclear, solar trough, and DG resources were not selected in any of the scenario least cost portfolios. These types of resources are very capital intensive even when factoring in tax incentives. None of the least cost portfolios comply with the REA. Additional scenarios were evaluated to meet the standards with and without diversity requirements. Renewable compliance increases portfolio costs. MAJOR DRIVERS OF NEW RESOURCE SELECTIONS The load forecast level is the primary driver for the type, size and timing of resources needed to serve customer demands. Retirement of coal facilities at SJGS or Four Corners Power Plant results in the addition of a combined cycle unit to replace the lost baseload units; additional gas turbine generation is also needed in the years following the retirement. REA requirements largely determine the type, size and timing of renewable resources needed. Higher natural gas prices may improve the cost effectiveness of renewable resources. MINOR IMPACT OF NEW RESOURCE SELECTIONS CO2 cost adders less than $35/metric ton, with the mid natural gas price sensitivities, do not have a noticeable impact on new resources selected in the scenario least cost portfolios. Higher coal capital costs and SCR/SNCR environmental upgrades do not have an impact on resource selections. These are system cost adders that do not affect system dispatch and provide no direct operational system impacts. The drought sensitivity (water curtailment) and the electric vehicle load sensitivity did not significantly impact future build decisions. 149

162 Quantitative Analysis PNM IRP QUANTITATIVE ANALYSIS OVERVIEW Realworld system conditions will vary from assumptions used for scenario analysis, and multiple variations from those assumptions may occur simultaneously. Stochastic financial risk analysis (Stochastic Analysis or Risk Analysis) provides a rigorous analysis by simultaneously varying multiple modeling assumptions and quantifying the impact to the total cost of potential resource portfolios. The IRP evaluation used stochastic financial risk analysis and is an important part of determining the most cost effective portfolio that will perform well, regardless of changes in future system conditions. Scenario analysis determines the impact of discreet changes in the input variables, such as load growth or fuel prices. Stochastic financial risk analysis differs from scenario analysis in that it tests the uncertainty regarding the various conditions, including correlated changes in system variables over a continuous range of expected variables. That is, it looks at what happens when several input variables change from their expected values simultaneously. Sometimes they all change in one direction, sometimes in different directions, and sometimes one changes while another does not. Stochastic analysis can provide insight to determine conditions that are favorable or unfavorable for certain resource choices or combination of choices by identifying portfolio financial risks. A least cost portfolio is determined for each of the 26 scenarios examined in the IRP. Differences in the input assumptions between scenarios can result in a different system resource portfolio mix. For example, a high gas price scenario will result in a recommended portfolio that has less reliance on gasfired plants than the portfolio recommended for a low gas price scenario. Stochastic analysis compares the two portfolios under a range of gas prices and also varies other input variables within the same analysis. The important summary outputs collected from the stochastic analysis are the expected costtocustomers of each portfolio and the risk that the cost could be much higher than that expected level. The expected cost is measured by the mean (average) NPV cost while the risk is measured by the 95 th percentile cost. Optimally, the best portfolio will have the lowest average cost as well as the lowest 95th percentile (i.e., upper tail ) financial risk. However, often the utility is faced with a choice or tradeoff of lower risk vs. lower cost. About the Monte Carlo Analysis There are many methods to perform financial risk assessment; one is the Monte Carlo method. The Monte Carlo simulation uses randomly selected values from variable probability distributions to determine how random variation subject to probabilistic occurrence (stochastic outcomes) affects the cost of the portfolio being modeled. The Monte Carlo analysis used for PNM s IRP consists of the following steps: Step 1: Determine the potential range of values for input variables (including load forecast, natural gas fuel prices, market prices for electricity, and CO 2 costs). Then define a probability distribution for each variable; the likelihood that each value in the range may occur. 150

163 Quantitative Analysis PNM IRP Step 2: Determine the correlation among input variables if any, i.e. the change in one variable directly related to a change in another variable. Step 3: Generate a set of random input conditions, one value from each of the defined variables probability distribution reflecting any correlation among the variables, for each year of the study period. Step 4: Calculate the resource portfolio s total system cost for each selected set of randomly generated variable values using modeling software to optimize dispatch of the selected portfolio of resources. Step 5: Aggregate the results of the random draws from Step 4 and calculate the average cost and cost variability (mean NPV and 95 th percentile risk). Steps four and five then repeat for each portfolio, using the same randomly generated conditions. This analysis subjects each portfolio to the same probable conditions including market sales or purchases that can lower portfolio costs through economical usage of units. Monte Carlo analysis is suitable for complex models because of the computational power of modern computers and software for statistical estimation and calculation. PNM s IRP stochastic analysis applied 300 sets of input variables (300 draws ) 6 to the Strategist model. The least cost portfolios from all 26 scenarios and additional scenarios discussed in Section 11: Scenario Analysis were subjected to evaluation under Monte Carlo analysis. The objective of the simulations is to assess how the various portfolios respond to the variety of possible future conditions. For a more detailed discussion of the Monte Carlo analysis assumptions and methodologies and interpretations, refer to Appendix F, Stochastic Risk Analysis Details. MONTE CARLO INPUT VARIABLES The variables chosen for the Monte Carlo simulations were selected based on both importance to system costs and variability. Variables that do not have a large impact on cost or that are stable and predictable in their values were not examined. The variables discussed below were varied in the Monte Carlo simulations. Details are in Appendix F. Load forecast risk CO 2 cost risk Natural gas price risk Wholesale market electricity price risk LOAD FORECAST RISK Responding to the customer load forecast drives resource selection. There is considerable uncertainty and variability in forecasting load growth. PNM examined three different load forecasts in the scenario analysis (high, mid, low) as shown in Figure 83. The three forecasts reflect the uncertainty over the longterm trends in load growth; however, it is more likely that actual load will fall between these three forecasts rather than a particular one. There is also variability in load from 6 1,000 draws were generated and compared to the distributions of the variables in the 300. There was no significant difference in results between using 1,000 and 300 draws. 151

164 Quantitative Analysis PNM IRP year to year that will be present regardless of which longterm trend may emerge. This variability is largely determined by weather, although other shortterm factors like economic conditions will have some effect. Over the past 20 years, PNM s peak load has grown at an average rate around 3%, yet load growth has varied between 2% and +12% in the last ten years, as shown Figure 121. FIGURE 121. COMPARISON OF ACTUAL ANNUAL PEAK GROWTH DEMAND A robust portfolio will have the flexibility to keep costs low under conditions above or below expected load without violating reliability criteria. In addition, over time, the portfolio must adapt to variation in the longterm growth trend. The stochastic simulations test the portfolios under these varying conditions. The 300 draw simulations vary yearoveryear load growth values from the midload forecast value each year. For example, peak load in 2012 varies among the 300 draws from a low of 1,578 MWs to a high of 1,883 MWs. Figure 122 shows the accompanying normal probability distribution for load in 2011 used in the Monte Carlo analysis. FIGURE 122. PROBALITY DISTRIBTION FOR 2012 LOAD Simulation Fit Comparison for Annual Load Variation from MidForecast (2011) Normal Distribution (Mean = 0.0%, Std Dev = 3.23%, Min 10.25%, Max 12.69%) 5% 5.28% Frequency of Input Values vs. Normal Distribution 95% 5.26% % 10.0% 5.0% 0.0% 5.0% 10.0% 15.0% Input Normal 152

165 Quantitative Analysis PNM IRP CO2 COST RISK A wide range of carbon assumptions was examined in the IRP scenario analyses. The carbon cost assumption varied from $0/metric ton to $100/metric ton of CO 2 in different scenarios. In addition, scenario19 looked at the impact of regulations that directly limited carbon emissions rather than assigning a cost to emissions. The stochastic analysis then examined the resulting scenario portfolios. The Monte Carlo simulation assumed a federal cap and trade regulation program. Emitters are granted an allotment of allowances based on baseline emissions. The amount of allotted allowances declines each year. Emitters can purchase or sell allowances, if their emissions are above or below their allotment. After lengthy discussion and debate among Working Group participants, the following risk distribution was developed. The values for carbon prices varied between $0/metric ton and $40/metric ton in the simulations (2011 dollars). The carbon price distribution rose over time, both with inflation and by the assumed time pattern in Table 121. This reflects lower initial pricing due to delayed implementation and then the growing scarcity of allowances over time as proposed standards take affect and the number of allowances is restricted. TABLE 121. CARBON PRICES Carbon Prices Years $/tonne $0$ $0$ $0$ $0$40 NATURAL GAS PRICE RISK Fuel costs represent a large portion of total generation operating costs. In 2010, fuel costs were just under 50% of PNM s production costs at the company s generating plants 7. Natural gas prices are considered among the most volatile of commodity prices (as are wholesale electricity prices that generally trend with natural gas prices). Also, gasfired generation is increasing relative to both coal and nuclear generation. Gasfired generation is expected to be the primary source of new generation resources for both PNM and the industry. In addition, gasfired generation is being utilized more heavily to balance renewable energy resources. Because of the importance of gas prices and the volatility of those prices, gas prices are included among the variables examined in 7 Fuel costs were 47.9% of production expenses. This does not include figures from generation resources under PPAs (Delta, Valencia, NMWEC). 153

166 Quantitative Analysis PNM IRP the stochastic risk analysis. This captures the impacts of the volatility in gasfired resource requirements, including the variability of renewable resource output. PNM used historic gas price volatility to estimate the variation to be used in the Monte Carlo simulation draws. A data period from July 2005 to January 2011 was studied, as shown in Figure 123. PNM chose this period, with agreement from the Working Group, as it included a number of events that significantly impacted gas prices. In 2005, hurricanes Katrina and Rita caused major supply disruptions. The period also covered a time of strong economic growth and energy demand, followed by a severe recession and drop in demand. Other weatherrelated events impacted prices, including a severe cold snap in February 2011 that affected New Mexico and Texas gas and electricity supplies. Also, gas supplies increased significantly during this time with the development of drilling technologies that allow greater production from shale gas deposits. As a result, variation in prices was quite high during the period. FIGURE 123. HISTORICAL GAS PRICES $16.00 Hurricane Katrina EPNG Permian Basin Daily $14.00 $12.00 Hurricane Rita warm summer, economic bubble, consumption high Hurricanes Ike & Gustav Gas Price ($/mmbtu) $10.00 $8.00 $6.00 Recession Texas/NM Gas Interruption $4.00 $2.00 $0.00 EPNG Permian Basin Daily Daily gas prices over this period averaged $5.71/MMBtu. Prices ranged from a low of $1.99 to a high of $13.62/MMBtu. The data is for natural gas delivered to the El Paso Natural Gas Company pipeline system in the Permian Basin of Southeast NM and West Texas. Natural gas has a very liquid futures market, in which buyers and sellers can contract for sales at future dates. Prices for forward date transactions are quoted realtime. These price quotes for trade dates extend several years into the future. PNM s midgas price forecast is based on the futures 154

167 Quantitative Analysis PNM IRP market price quotes for the nearterm, with annual escalation of 3.5% for the rest of the 20year study period. For the Monte Carlo simulations, volatility based on the historic data was applied to the midgas price forecast. Based on this, gas prices for 2012 in the 300 draws ranged from $1.66/MMBtu to $15.31/MMBtu. The risk simulations take into account the probability (albeit slight) that these extreme values could emerge. Figure 124 shows the probability distribution of gas prices. More details on the Monte Carlo simulations for gas prices are provided in Appendix F.2. FIGURE 124. PROBABILITY DISTRIBUTION OF GAS PRICES Simulation Fit Comparison for Natural Gas Price Variation (2011) Log Normal Distribution (Mean = $4.08, Std Dev = $1.62, Min = $1.19, Max = $13.12) 5% $2.09 Frequency of Input Values vs. Log Normal Distribution 95% $ $0.00 $2.00 $4.00 $6.00 $8.00 $10.00 $12.00 Input Lognorm WHOLESALE ELECTRIC PRICE RISK For the stochastic analysis, the Strategist model was extended to include wholesale electric market transactions to reflect the actual operation of the PNM resource portfolio. The dispatch of the portfolio is allowed to interact with the regional marketplace, where market sales or purchases can lower portfolio costs through economical usage of regional units. For example, at peak load times, PNM may need to run lessefficient units to meet the load. If wholesale power is available at a lower cost than the cost of generating at those units, PNM will purchase power rather than dispatch those units. Similarly, when PNM has spare capacity during offpeak hours, it may be able to sell power at a price that covers generating costs and thereby provide a credit to customer cost. All costs or benefits of market sales are directly passed through to customers and are audited by the NMPRC. Variation in electric prices will partially determine when offsystem sales or purchases are economical. On an hourly basis, the incremental generation cost of regional utilities will generally set the electricity market price. Historically, this has been highly correlated to natural gas prices. 155

168 Quantitative Analysis PNM IRP Usually, gasfired units generate at the margin as base load and renewable resources generally run at near available capacity. Figure 125 shows a statistical estimation of the relationship between natural gas and electricity prices. Daily prices for wholesale electricity (at the Palo Verde market hub) were compared with daily natural gas prices (El Paso Permian index). The figure illustrates a linear regression estimation that indicates a strong relationship between gas costs and power prices. FIGURE 125. GAS AND ELECTRICITY PRICE RELATIONSHIP In the future, CO2 costs attached to electric generation will affect electric prices. The amount of CO2 per MWh will depend on the efficiency or heat rate of the plant setting the market price. There has not yet been a history of market prices of CO2 that can be correlated to electricity price. For the stochastic analysis, PNM assumed that the market price of electricity will track the cost of CO2 at a ratio of approximately $0.40/MWh for each $1/metric ton of CO2 cost. This reflects an assumption of 117 pounds (lbs) of CO2 per MMBtu of gas, and a natural gas combined cycle plant operating with a heat rate of 7,500 Btu/kWh is, on the margin, setting the price for electricity. For the Monte Carlo draws, the price of electricity varies with the price of gas and the price of CO 2 and also includes additional uncorrelated variability. This additional variation is included in the Strategist model in hourly price curves for dispatch modeling. As a consequence of the volatility in gas and carbon price draws, electricity prices vary sharply also. For more details, see Appendix F3. SIMULATION RESULTS The Strategist model calculated the NPV of the total system cost for each of the scenario portfolios for each of the 300 simulation draws. The simulation results for each scenario portfolio produce a measure of cost and a measure of risk. The cost of that portfolio is the mean value of the 300 total 156

169 Quantitative Analysis PNM IRP system costs calculations. This is the expected NPV of costs to customers. The statistic selected to measure risk is the value representing the 95 th percentile of the 300 system cost results. That is, there is 5% likelihood that the actual costs of this portfolio will be greater than this value 8. The combination of cost and risk indicated by these measures can be shown graphically as in Figure FIGURE 126. PLOTTING PORTFOLIO RISK AND COST MEASURES A riskier portfolio will produce a flatter and more spreadout bell curve representing greater variation in the likely results. A flatter curve indicates a higher probability that the actual result will differ from the average or expected amount. (See Figure 127 for a plot of the 300 draw results of total system costs for Portfolio 4.) 8 The use of a 5% probability tail is a common measure of the dispersion of values in a probability distribution. For example, tail refers to the high values at the end of the familiar bellshaped distribution curve showing that only 5% of outcomes can be expected to have a value above that level. Other frequently used measures include a 2 ½% tail or 1% tail. Samples indicate these measures were consistent with the 5% test results used in the simulations. 157

170 Quantitative Analysis PNM IRP FIGURE DRAW SIMULATION The mean value and 95 th percentile results for all scenario portfolios are summarized in Table F1 in Appendix F. CARBON COST SCENARIOS SIMULATIONS COMPARISON A number of scenarios varied the assumption of carbon cost. The cost ranged from $0/metric ton of CO 2 up to $100/metric ton of CO 2. Scenarios 1, 2, 3, 4, 5 and 16 assumed different carbon prices, but used the same assumptions for load growth, gas prices and other inputs. For scenarios at $35/metric ton or higher, different resources are chosen to be built or acquired. Figure 128 plots the risk and cost results of those scenarios. FIGURE 128. CO 2 COST EXAMPLE; RISKCOST TRADEOFF 158

171 Quantitative Analysis PNM IRP The horizontal axis measures the mean value of the Monte Carlo analysis. The vertical axis plots the difference between the mean cost and the 95 th percentile cost. A comparison of Portfolio 3 and Portfolio 5 shows a higher cost for Portfolio 5. Portfolio 5 assumed $100/metric ton CO2 and selected more renewable resources than portfolios built with the expectation of lower CO2 prices. Portfolio 5 results in higher system cost than the other portfolios over the full range of possible CO2 prices. It is important to note that the variability in the other simulation variable inputs also determines these portfolio costs and risks. For example, Portfolio 16 relies only on gasfired plant additions. Portfolio 4 invests in more renewables and energy efficiency resources. Gas price variation will therefore impact Portfolio 16 to a greater degree. A similar relationship can be seen between Portfolio 3 and Portfolio 4. This illustrates that portfolio differences designed to address carbon costs will also impact the risk exposure to gas prices, load changes and other variables. CARBON COST EXAMPLE VALUING THE TRADEOFFS The optimal result for a portfolio is low cost and low risk, plotted closest to the lower left corner of the graph. Portfolio 3 had much lower cost than Portfolio 5 with virtually the same risk measure. However, other comparisons do not produce a clear preference. Portfolio 16 (built for $0 CO 2) has slightly lower cost than Portfolio 4 (built for $35 CO 2), but Portfolio 16 has greater variation in cost. To choose between the two, PNM must make a judgment as to the relative importance of risk versus cost. One possible tradeoff preference is shown in Figure 129 RiskCost Indifference as an indifference line. The slope of the line indicates the tradeoff between risk and reward. It implies that for any portfolio that falls on the line, utility customers are equally welloff compared with another portfolio on the line. Any portfolio that has lower cost and risk is better; it has a preferred riskcost combination. The line slopes downward, which indicates that when risk increases, cost must decrease to maintain indifference. FIGURE 129. RISKCOST INDIFFERENCE 159

172 Quantitative Analysis PNM IRP OTHER EXAMPLES FROM SIMULATION RESULTS RETIREMENT OF COAL UNITS Several portfolios resulted from the retirement of some of PNM s current coal plant units. For example, Portfolio 13 covered the retirement of all of PNM s 200 MW interest in Four Corners Power Plant. Portfolio 14 covered the retirement of 340 MW of PNM s total of 746 MW interest in the SJGS. Retirement of the coal capacity results in a significant increase in customer costs. As shown in Figure 1210, the portfolios that retire coal have higher risk than portfolios that retain the coal capacity. While reducing coal capacity lowers risks from carbon cost increases, those portfolios are more vulnerable to high gas and electricity prices and high load growth. The certainty of higher capital costs associated with replacing coal facilities dramatically raises the expected cost, making existing coal facilities least cost alternatives. FIGURE 1210 PORTFOLIOS INCLUDING COAL RETIREMENTS IMPACT OF BUILDING FOR HIGH LOAD GROWTH Figure 1210 also shows the simulation results for two portfolios which assumed high load growth, Portfolios 22 and 25. The table indicates there are significant costs associated with building a system ahead of actual load growth, although risk exposure is not increased and reliability was improved. COSTS OF INCREASING RENEWABLE ENERGY INVESTMENT Figure 1211 shows the risk results of portfolios that meet the target levels of the RPS without being constrained by the RCT provisions in the RPS rules. The mean value expected cost is much higher for these portfolios ($500$600 million) under the simulation results. 160

173 Quantitative Analysis PNM IRP The most cost effective portfolio adjusted the least cost portfolio selections to reflect additional objectives and constraints as discussed in Section 2,Most CostEffective Portfolio. Importantly, resources were selected that provided greater system reliability and operational advantages and renewable resource additions were increased to help move toward the RPS target levels. Figure 1211 illustrates cost and risk comparisons of the most cost effective portfolio as compared to least cost portfolios and portfolios that meet the RPS target levels for energy from renewable sources. The most cost effective portfolio adds renewables that are consistent with an expected reasonable cost threshold limitation. The amount of renewable resource additions selected is based on an expansive RCT calculation assumption (significant CO2 costs, etc.), but the portfolio still does not fully reach the target renewable energy levels. The two RPS portfolios in the figure were developed to meet the RPS targets for total renewable energy without regard to RCT limitation 9. The most cost effective portfolio shows higher mean expected cost than the least cost portfolios under the simulation analysis, but lower cost versus the RPS target portfolios. FIGURE RPS TARGETS VS. LEAST COST PORTFOLIOS $320 $310 RPS Targets & Reliability: Risk Cost Effects (300 Draws: CO2, P E, P G, Load) Port 2 Least Cost w/o RPS or Reliability Attributes 5% Risk Tail ($million) $300 $290 $280 $270 Port 4 Most Cost Effective RPS Target RPS, $0 CO2 RPS, high gas $260 $250 $6,650 $6,700 $6,750 $6,800 $6,850 $6,900 Expected Portfolio Cost (Mean NPV $million) 9 The RPS portfolios do not fully meet RPS type diversity targets or meet system reliability and operational requirements. Portfolio costs would be somewhat higher if those conditions were to be met. 161

174 Quantitative Analysis PNM IRP OBSERVATIONS FROM RISK SIMULATIONS Results from the stochastic risk analysis can be summarized: Differences in risk among the portfolios tend to be small relative to differences in mean cost. The portfolios tend to be dominated by PNM s existing plants. New resources represent a relatively small amount of capacity and energy compared with plants already in place. Base load coal and nuclear plants continue to provide a large portion of low cost generation. Reiring coal plants increases costs without significantly reducing risk. Renewables have less risk exposure to carbon and gas price increases but higher system costs due to more expensive capital. Gas resources have less exposure to load variability and electricity prices and tend to be lower cost than renewables and have less exposure to load growth variation. Risk is generally lower with portfolios that have a diverse mix of coal, nuclear, gas and renewables. 162

175 Qualitative Analysis PNM IRP QUALITATIVE ANALYSIS In addition to a quantitative analysis, PNM conducted a qualitative analysis to capture other important issues to identify the most costeffective resource portfolio. The qualitative analysis is an evaluation of factors that cannot be quantified in the scenario analysis and risk analysis. Five categories of issues are discussed below: operational, technological, financial, economical and behavioral, and political. Some of the qualitative issues fit in multiple categories. PNM evaluated each of the factors to determine the risk involved, the potential impact on the plan, and mitigation strategies both to individual resources and to the portfolio to yield the most cost effective portfolio. OPERATIONAL RESERVE MARGIN AND LOSS OF LOAD The scenario analysis used the NMPRC approved reserve margin of 13%, or a minimum of 250 MW. The 250 MW represents PNM s single largest hazard of 240 MW with an additional adjustment for weather potential. To avoid a major increase in the planning reserve margin, PNM restricted new resources to 252 MW. Using the single largest hazard and weather adjustments is the method PNM uses to determine an appropriate reserve margin. Recently, other utilities have determined that this method may not result in a sufficient reserve margin to maintain acceptable system reliability. Other utilities have switched to a 1 in 10 methodology, which increases planning reserves such that the probabilistic outage rate is 1 day in 10 years (or 24 hours for 10 years). If this method were applied in the PNM IRP process, increased resources may be required, which would likely result in planning reserve margin being higher than 13%. Increasing the number of dispatchable new resources and decreasing the size of dispatchable new resources improves the overall system reliability by limiting impacts in the event of an outage. In combination with other factors, PNM is mitigating the risk of more stringent planning requirements by proposing smaller units in its future resource portfolio. Additionally, PNM continues to mitigate reliability risk by ensuring that common failure modes of generating resources do not result in a higher than 250 MW loss of generation. OPERATING RESERVES: Planning reserve margins are used in longrange planning to ensure adequate resources are identified to serve future peak load requirements. In contrast, operating reserves are resource reserves used to respond to existing loads and resources in realtime. The most cost effective portfolio proposes that two aeroderivative turbines are added to the system in 2015 and These types of resources are capable of achieving full output in 10 minutes and their full capacity can be counted towards PNM s operating reserves. The aeroderivative fast start capability could not be captured in Strategist modeling since the benefits for these units are typically realized in realtime system operations. Therefore, PNM performs a qualitative check to verify whether the least cost model is acceptable for reliable operations. NERC RELIABILITY CRITERIA AND NATIONAL STANDARDS NERC s goal is to maintain a high degree of reliability for individual utility systems so that the system as a whole is not impacted from a single utility reliability event. Since PNM s 2008 IRP, trends in NERC compliance have leaned towards more stringent reliability standards. Using smaller aeroderivative turbines to follow loads and intermittent resources in years 2015 and 2016 enhances portfolio cost effectiveness and improves PNM s ability to comply with NERC reliability 163

176 Qualitative Analysis PNM IRP standards. Future enhancements to larger turbines, that incorporate more flexible operating characteristics of the smaller aeroderivatives, may increase this technology s effectiveness as discussed in the following technological section. TECHNOLOGICAL TECHNOLOGY DEVELOPMENT, AVAILABILITY AND TIMING Most of the least cost portfolios in this IRP included a large gas turbine as the first resource addition. The large gas turbine characteristics used in the models assumed performance enhancements that are typically attributed to aeroderivative technology such as lower heat rates, low turndown, and faststart capability. These capabilities on a large scale turbine have not been demonstrated and are based on manufacturer projections. To mitigate operational risk, PNM prefers new technologies to be field tested by the industry before implementing them. Since the aeroderivative turbine is a proven technology, PNM has selected aeroderivative turbines over large gas turbines until the manufacturer projections are demonstrated. PNM has retained the large turbine for consideration in 2017 due to these expected operational enhancements. Through this IRP process, PNM has explored many emerging technologies, including new designs of natural gas turbines, solar technologies, and battery technologies; however, PNM is certain other technologies will be developed that provide benefits to the utility industry. PNM understands that this IRP needs to be flexible enough to acknowledge and take advantage of new technologies. PNM continues to follow new technology development and incorporates new technology at an appropriate time and scale to minimize risks and maximize potential benefits. One way that PNM does this is through collaborations with research leaders such as the Electric Power Research Institute (EPRI) and laboratories such as Sandia National Laboratories. These collaborations help put PNM in contact with other utilities where information can be exchanged on programs or technologies that are applicable and beneficial for PNM. This allows PNM to gain valuable information from utilities evaluating technologies that PNM is not currently developing. This collaborative approach, gives PNM and other utilities a broader technology perspective without having to assume the risk of large scale deployments. PNM and other NM entities are participating in a battery storage solar demonstration project which has been funded by DOE. This project leverages the research collaboration of other organizations and provides a greater ability to share learning within the industry. This project will help guide the industry in making future technology assessments. At the same time, PNM will generally follow the same strategy of monitoring research and development, analyzing impacts of technology on the system, and adopting technology when beneficial to PNM its customers. Although this plan effectively incorporates the known technologies and their current characteristics, PNM will continue to monitor new technologies and improvements to existing technologies to determine if they indicate a shift in future resource development. 164

177 Qualitative Analysis PNM IRP FINANCIAL Investments in power plants are the biggest component of electric utility capital requirements and are recovered over the life of the investment. PNM s ability to finance new capital projects and the cost associated with financing the projects ultimately impacts the customer. Over the past several years, PNM has been focusing on improving its financial metrics to raise its credit rating above investment grade and lower the cost of debt. Credit rating agencies evaluate many factors, with a primary focus on the amount of cash generated in relation to the debt. Quicker recovery of costs translates to stronger financial metrics. Credit agencies also look at diversification and risks of the portfolio, similar to the risks discussed throughout the IRP. Timing and magnitude of capital additions should align with cost recovery. Renewable additions are more capital intensive than natural gas additions and represent a greater financial investment, and therefore risk, if costs are not recovered in an assured and timely manner. PNM will be proposing a renewable rate rider in 2012 to lower this financial risk and lower the costs that are charged to customers from both financing costs and carrying costs. PNM will continue to seek future energy efficiency costs through a rate rider to keep costs low to customers by lowering financial risk and carrying costs. The remainder of the resource additions to PNM s portfolio is natural gas generation, which has the lowest financial risk amongst generation resource types since it is less capital intensive. To keep financial risk low, PNM will seek CCN approval with a cost recovery request for the assets prior to construction to assure recovery of costs associated with the projects. Also, when evaluating new renewable and natural gas additions, PNM will determine whether it should own and finance the generation asset, or purchase the power through a longterm agreement. Each project will be evaluated to keep customer costs low and not degrade PNM s financial metrics. Resource requirements will also be affected by developments in the national and local economy and by developments in financial markets. Uncertain future conditions regarding employment, inflation and interest rates will all affect the demand for electricity and its cost of production. ECONOMICAL AND BEHAVIORAL There are many aspects of PNM s IRP that rely on customers (from residential to large industrial) making choices, including investments in energy efficiency, distributed generation, batteries, and electric vehicles or responding to price signals for conservation. Each consumer has a unique energy usage profile and will not necessarily be motivated by industry price signals in the same ways. PNM has concluded that although electric vehicles and battery usage is increasing, penetration levels are relatively low compared to overall energy usage, and actual adoption rates can vary with minimal impact to the results of the IRP. Energy efficiency, demand response, and distributed generation have a much greater impact. Overall, current price signals for these programs are resulting in the expected response rates. PNM annually evaluates energy efficiency programs so that program payments and participation rates stay within expected ranges and meet cost thresholds. As previously discussed, customer behavior is sometimes motivated economically, but other factors shape customer energy choices. The demand for electricity is derived from known factors such as the need to power factories, lighting, cooling and heating homes, appliance usage, or to charge cell phone batteries and laptops. Changes in technologies or consumer preferences can dramatically 165

178 Qualitative Analysis PNM IRP influence PNM s load. Customers may make choices based on concern for the environment, interest in new technology, desire for simplicity, or many other factors. As such, electric load forecasts are subject to uncertainty and do not always follow adoption rates based on economic predictions and can be higher or lower. POLITICAL New policies, rules and regulations that affect the electric utility industry, and resource planning efforts, continue to evolve. This IRP has considered known policies, rules and regulations and presents a 20 year portfolio recommendation based on a range of potential implications. However, during a 20year planning horizon, additional policies, rules and regulations implemented at both the federal and state levels will create new implications for PNM s resource plan. The IRP Working Group expressed diverse views in this area that reflected the state and national struggle in developing new energy policy. Some members believe that energy policies must change to protect and improve the environment, while others believe that some potential policies will not improve the environment, but would cause significant economic harm and should therefore not be developed. FEDERAL POLICIES Over the past several years, Congressional legislation has been introduced that would result in federal regulation of greenhouse gas emissions, institute nationwide renewable portfolio standards, and would promote generation technology development for resources, including renewables and nuclear generation. While there are no current legislative proposals that appear likely to receive Congressional approval, the past proposals should be viewed as source material for future proposals. One example is the Clean Energy Standard concept that President Obama introduced in the 2011 State of the Union address. This concept is under development in the Senate Energy Committee and may result in a future legislative proposal that could encompass some form of greenhouse gas emission reduction, technology development and a national renewable portfolio standard. PNM will continue to evaluate its planning assumptions related to anticipated federal energy policies. An example of a developing federal regulation that could impact PNM s resource planning assumptions is the anticipated release of a new Ambient Air Quality Standard for ozone. The new ozone standard is expected to be lower than the existing standard, but the extent and impact of the decrease is unknown. When the new standard is announced, it is possible that San Juan County will be deemed nonattainment for ozone. Nonattainment status would require NMED to develop a compliance plan for the county. The compliance plan should consider all sources that contribute to ozone levels in the county, which include the electric generation plants in the county. The multiple levels of uncertainty surrounding this issue (the level of the standard, San Juan County s attainment status, the sources that will be affected if a compliance plan is needed) make planning for this regulation difficult. As the uncertainty resolves, PNM will update its resource planning accordingly. NEW MEXICO POLICIES This IRP has evaluated the impact of the statelevel policies and the portfolio recommendation documents the impacts the policies have on PNM s most cost effective portfolio. To mitigate risk associated with new state regulation, PNM remains actively involved with legislators and regulators in the development of energy policies, rules and regulations. 166

179 Qualitative Analysis PNM IRP RESOURCE SITING Political uncertainty also impacts resource siting, including transmission development. Some communities accept generation resource development, while others do not. Even renewable resource development in New Mexico has met with challenges, including implementation of local ordinances that restrict or prohibit development. Transmission lines that can cross multiple communities, including sovereign nations have additional permitting challenges, where a complete path is necessary before any part of the project is considered feasible. PNM manages siting risk by assessing community acceptance and permit feasibility and incorporating this in planning and site selection efforts. 167

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181 Appendix A Glossary PNM IRP APPENDIX A GLOSSARY ACRONYMS AC: Alternating Current; Air Conditioning ADI: ACE Diversity Interchange Afton: Afton Generating Station (see also Afton CC) Afton CC: Afton CombinedCycle Generating Station APS: Arizona Public Service BAC: Balancing Area Coordinator for the WECC PSA planning process BART: Best Available Retrofit Technology BB Line: BlackwaterBA 345 kv line BBER: Bureau of Business and Economic Research at the University of New Mexico BNCC: BHP Navajo Coal Company Btu: British Thermal Unit CAA: Clean Air Act Case 3137 Stipulation: Stipulated Agreement that settled Utility Case 3137, which established a 13% reserve margin target. CC: Combinedcycle CCAE: Coalition for Clean, Affordable Energy CCN: Certificate of Convenience and Necessity CCS: Carbon capture and sequestration; carbon capture and storage CO 2: Carbon dioxide. CPS: Control Performance Standards CT: combustion turbine DC: Direct current; Blackwater ACDCAC converter station DeltaPerson: Delta Generator located in Albuquerque at Rio Bravos and I25 DG: Distributed generation. DR: Demand response EE: Energy Efficiency. EGU MACT: National Emission Standards for Hazardous Air Pollutants from Coal and Oil Fired Electric Utility Steam Generating Units and Standards of Performance for Fossil Fuel Fired Electricity Utility, IndustrialCommercial Institutional, and Small Industrial Commercial Institutional Generating Units EIB: Energy Information Board EPA: Environmental Protection Agency EPACT: Energy Policy Act of 2005 EPC: Engineering Procurement and Construction EPE: El Paso Electric Company 169

182 Appendix A Glossary PNM IRP EPRI: Electric Power Research Institute ERO: Electric Reliability Organization EUEA: Efficient Use of Energy Act 6217 NMSA FERC: Federal Energy Regulatory Commission FIP: Federal Implementation Plan gals: Gallons GE: General Electric GHG: Greenhouse Gas GWh: Gigawatthour HAP: Hazardous Air Pollutants HVAC: Heating, Ventilation, Air Conditioning IGCC: Integrated Gasification Combined Cycle plant IRP: Integrated Resource Plan kv: Kilovolt; a measure of voltage, 1,000 volts KW: Kilowatt, also shown as kw; a measure of capacity equal to 1,000 watts kwh: Kilowatthour, a measure or energy produced or consumed L&R: Loads and Resources Las Vegas CT: Las Vegas Generating Station Combustion Turbine plant lbs: Pounds LM: Load Management LSE: Load Serving Entity MACRS: Modified Accelerated Cost Recovery System MM: Million MMBtu: Million British Thermal Units, also shown as Mbtu. MRel: Most reliable; abbreviation used in section ten tables and figures MW: Megawatt MWh: Megawatthour NAAQS: National Ambient Air Quality Standards NAES: North American Energy Services NDI: Normal Direct Irradiance NEC : Navopache Electric Cooperative NERC: North American Electric Reliability Council NG: Natural gas; abbreviation used in tables and figures NITS: Network Integration Transmission Service NM: New Mexico NMAC: New Mexico Administrative Code NMED: New Mexico Environmental Department NMEIB: New Mexico Environmental Improvement Board 170

183 Appendix A Glossary PNM IRP NMPRC: New Mexico Public Regulation Commission (also referred to as Commission) NMSU: New Mexico State University NMWEC: New Mexico Wind Energy Center NNM System: Northern New Mexico transmission (also referred to as WECC Path 48) NOX: Nitrogen oxides NPV: Present value of net cash flows (net present value) NRC: Nuclear Regulatory Commission NSR: New Source Review NTUA: Navajo Tribal Utility Authority O&M: Operations and maintenance OATT: Open Access Transmission Tariff OLE: Ojo Line Extension OSM: Office of Surface Mining PA: Public Advisory PAFC: Phosphoric acid fuel cell PEV: Plugin Electric Vehicle PM: Particulate matter PNM: Public Service Company of New Mexico POD: Point of Delivery POR: Point of Receipt PPA: Power Purchase Agreement PSA: Power Supply Assessment PV: Photovoltaic PVNGS: Palo Verde Nuclear Generating Station located near Phoenix, Arizona RCRA: Resource Conservation and Recovery Act RCT: Reasonable Cost Threshold REA: Renewable Energy Act 6216 NMSA REC: Renewable Energy Certificate Reeves: Reeves Generating Station located in Albuquerque, New Mexico RFP: Request for Proposal RPS Rule: New Mexico Administrative Code regarding the Renewable Portfolio Standard RPS: Renewable Portfolio Standard Rule 572: New Mexico Administrative Code regarding the Renewable Portfolio Standard SCR: Selective Catalytic Reduction SIP: Solar REC Incentive Program SJCC: San Juan Coal Company SJGS: San Juan Generating Station located near Farmington, New Mexico SNM System: Southern New Mexico transmission (also referred to as WECC Path 47) 171

184 Appendix A Glossary PNM IRP SNCR: Selective NonCatalytic Reduction SO 2: Sulfur dioxide SOFC: Solid oxide fuel cell SPC: Supercritical pulverized coal SPP: Southwest Power Pool SPS: Southwestern Public Service Company SRIP: Solar REC Incentive Program Approved in Case UT for customer sited solar generation SRSG: Southwest Reserve Sharing Group STG: Steam turbine generator SWAT: Southwest Area Transmission Planning Oversight Committee Tcf: Trillion cubic feet TEPPC: Transmission Expansion Planning Policy Committee TNMP: TexasNew Mexico Power TOU: Time of Use TPL: Transmission Planning Standards TRC: Total Resource Cost ratio of energy efficiency program benefits to the program costs rates U.S.: United States of America VER: Variable Energy Resources WAPA: Western Area Power Administration WECC Path 47: Southern New Mexico transmission (also referred to as SNM System) WECC Path 48: Northern New Mexico transmission (also referred to as NNM System) WECC: Western Electricity Coordinating Council WestConnect: Collaborative group of western utilities providing transmission 172

185 Appendix A Glossary PNM IRP IRP TERMINOLOGY 95 th percentile: A value on a scale of 100 that indicates the percent of a distribution that is equal to or below 95% of the distribution (also referred to as uppertail) ACE Diversity Interchange Power system control areas within three major (and essentially separate) areas of North America are interconnected electrically, thus enjoying vastly improved reliability and economy of operation compared to operating in isolation. Each must continually balance load, interchange and generation to minimize adverse influence on neighboring control areas and interconnection frequency. This requires investment in control systems and the sacrifice of some fuel conversion efficiencies to achieve the objective of complying with minimum control performance standards set by the North American Electric Reliability Council (NERC). Control also increases wear and tear on machinery in the pursuit of these goals. Area control area (ACE) diversity interchange (ADI) offers a means of reducing this control burden without undue investment or sacrifice by any participant in a group. (Source: IEEE, http: //ieeexplore.ieee.org/xplore/login.jsp?url=/iel1/59/8797/ pdf?arnumber=387953) Aeroderivative: A type of gas turbine for electrical power generation Availability factor: The ratio of the time a generating facility is available to produce energy at its rated capacity, to the total amount of time in the period being measured, as defined by the IRP Rule Avoided costs: The incremental cost to a utility for capacity and/or energy that could be avoided if another incremental resource addition such as energy efficiency were added that deferred or eliminated the need for the original addition Base load: A resource that is most economically used by running at a capacity factor of 65% or greater on an annual basis. See also capacity factor. Biomass resource: As defined by the IRP Rule, a recognized renewable resource type that uses renewable fuels such as agriculture or animal waste, small diameter timber, salt cedar and other phreatophyte or woody vegetation removed from river basins or watersheds, landfill gas and anaerobically digested waste biomass. See also renewable energy Biomass Study: PNM Biomass Assessment: Status Report Cap and Trade: A regulatory body sets a cap on emissions of a designated pollutant, and sells permits equivalent to a firm s emissions. Firms that need to increase their emission permits must buy them from other those who require fewer permits. Capacity factor: Actual energy generated over a certain time period divided by theoretical ability to generate electricity over that same time period. Capacity factor is most often referenced as an annual calculation. Capacity uprate: The maximum power level at which a nuclear power plant may operate Carbon dioxide: Carbon dioxide (CO 2) is an important greenhouse gas because it is thought to contribute to global warming. While it is not currently a regulated pollutant, it is the subject of pending federal legislation seeking to make it a regulated pollutant. That legislation would seek to 173

186 Appendix A Glossary PNM IRP reduce its CO 2 production by penalizing power plants for its emission into the atmosphere. An NMPRC Order in Case No UT requires that electric utilities use the following standardized prices for carbon emissions in their IRP filing: $8, $20 and $40 per metric ton for their low, medium and high price sensitivities, respectively. Centralized solar: Thermal solar facility that concentrates sunlight to collect heat and uses that heat to create steam that then drives a steam turbine to create electric generation (also referred to as concentrating solar) Climate change: A significant change in measures of climate, including temperature, precipitation, or wind, that lasts for an extended period of time, resulting from natural factors or human activities that change the atmosphere s composition and the land surface. Combined cycle gas turbine: For electric generation, combined cycle refers to a gas turbine that generates electricity and heat in the exhaust used to make steam, which then drives a steam turbine to generate additional electricity. Constrained transmission: A transmission system that can no longer accommodate additional capacity to meet demand is constrained. Conventional resources: Coal, nuclear and natural gas resources that have historically been the most commonly used to supply electricity (also referred to as traditional resources) Demand response: A resource comprising programs that compensate electricity users in exchange for the ability to interrupt or reduce their electric consumption when system demand is particularly high and/or system reliability is at risk. Demand: Usage at a point in time, measured in MW or kw Demandside resources: As defined by the IRP Rule, energy efficiency and load management, as those terms are defined in the Efficient Use of Energy Act Designated network resource: Dispatchability: The ability of a generating unit to increase or decrease generation, or to be brought on line or shut down at the request of a utility's system operator Distributed Generation: Electric generation that is sited at a customer s premises, providing energy to the customer load at that site and/or providing electric energy for use by multiple customers in contiguous distribution substation areas. In this report, refers to PNM customersited, renewable distributed generation program for solar photovoltaic systems under 10 kilowatts in size. Duty Cycle: Generating facility design that determines how a facility is operated. Duty Cycle classifications are baseload, intermediate or peaking. EE Rule: Energy Efficiency Rule ( New Mexico Administrative Code) Emergency energy: Energy purchases to meet unserved load 174

187 Appendix A Glossary PNM IRP Energy efficiency: Measures, including energy conservation measures, or programs that target consumer behavior, equipment or devices to result in a decrease in consumption of electricity without reducing the amount or quality of energy services, as defined by the IRP Rule Energy: Usage over a period of time, measured in GWh, MWh, or kwh Equivalent availability: Typically referred to as Equivalent Availability Factor (EAF), the proportion of hours in a given time period that a resource is available to generate at full capacity. Financial risk: Expected cost to the customer and the variability and uncertainty of future cost outcomes. Fixed cost: Costs that are independent of output. Contrast variable costs. Forced outage rate: Percent of time a unit is not operational when it is expected to be in service Geothermal Study: Geothermal Resource Development Needs in New Mexico Geothermal: Electric generation fueled by heat from geologic formations, which qualifies as a renewable resource under NMAC Heat rate: The ratio of energy inputs used by a generating facility expressed in BTUs (British Thermal Units), to the energy output of that facility expressed in kilowatthours, as defined by the IRP Rule Intermediate: A resource that is most economically run at capacity factors between 20% and 65% of the time on an annual basis. See also capacity factor. Itron Potential Study: Public Service New Mexico Electric Energy Efficiency Potential Study, dated September 20, 2006 IRP Rule: Integrated Resource Plan for Electric Utilities, NMPRC Rule NMAC. Jurisdictional load: Case 3137 Stipulation identifies jurisdictional load as New Mexico retail load and wholesale firm requirement customers contracted prior to September 2, Load duration curve: Illustration of the relationship between generating capacity requirements and capacity utilization. The load duration curve helps determine which type of resource best matches system load requirements. Load and Resources: A load and resources table shows annual balance between load and the resources to meet the load, and includes the reserve margin calculation Load factor: Peak demand divided by average demand Load forecasting: The prediction of the demand for electricity over the planning period for the utility, as defined by the IRP Rule Load management: Measures or programs that target equipment or devices to decrease peak electricity demand or shift demand from peak to offpeak periods, as defined by the IRP Rule 175

188 Appendix A Glossary PNM IRP Loadfollowing resource: This resource has a response rate that can meet normal fluctuations in load. Loss of load probability: Percent of time load is not served Marginal cost: The highest system resource cost for the hour Mean: The expected value of a random variable (of a probability distribution), which is also called the population mean Monte Carlo: Risk analysis technique utilizing multiple iterations calculated using random draws for sensitivity variables using a defined distribution for the variables Most costeffective resource portfolio: Those supplyside resources and demandside resources that minimize the net present value of revenue requirements proposed by the utility to meet electric system demand during the planning period consistent with reliability and risk considerations, as defined the IRP Rule Nameplate capacity: The rated output of an electrical generator; it can also refer to the rated capacity of a power plant. Net Present value: The difference between the present values of cash inflows and present value of cash outflows. Network transmission service: The transmission of capacity and energy from network generating resources to PNM s load. Nonspinning reserves: The extra generating capacity that is not currently connected to the system but can become available after a short delay. Particulate matter: A complex mix of extremely small particles and liquid droplets, including acids, organic chemicals, metals and soil and dust, creating particle pollution. Peak demand: Occurs when demand for energy is at its greatest Peak shaving: A strategy used to reduce electricity use during times of peak demand, typically employed through demandresponse programs. Peaking: A resource that is most economically run at a capacity factor of less than 20%. See also capacity factor Photovoltaic solar: Solar generation that uses photovoltaic panels to convert sunlight directly to energy Planning period: The future period for which a utility develops its IRP. For purposes of this rule, the planning period is 20 years, from Plugin hybrids: Hybrid automobiles whose batteries are recharged by plugging into an electric socket Point to point transmission service: Delivery of power from one location to another, without branching to other locations. 176

189 Appendix A Glossary PNM IRP Portfolio: A combination of resource additions/assets over the planning period that meet the reserve margin criteria Probability distribution: Describes the likelihood a random parameter over a range of possible values Public utility: As defined by the IRP Rule, public utility or utility has the same meaning as in the Public Utility Act, except that it does not include a distribution cooperative utility, as defined in the Efficient Use of Energy Act. Qualifying facilities: FERC established a new class of generating facilities which would receive special rate and regulatory treatment to support implementation of Public Utility Regulatory Policies Act of Generating facilities fall into two categories: qualifying small power production facilities and qualifying cogeneration facilities. Rankine cycle: A heat engine with a vapor power cycle commonly found in power plants. Rate rider: According to State Statute 6233H, "Rate" means every rate, tariff, charge or other compensation for utility service rendered or to be rendered by a utility and every rule, regulation, practice, act, requirement or privilege in any way relating to such rate, tariff, charge or other compensation and any schedule or tariff or part of a schedule or tariff thereof. Regional Entity: According to NERC, NERC works with eight regional entities to improve the reliability of the bulk power system. The members of the regional entities come from all segments of the electric industry: investorowned utilities; federal power agencies; rural electric cooperatives; state, municipal and provincial utilities; independent power producers; power marketers; and enduse customers. These entities account for virtually all the electricity supplied in the United States, Canada, and a portion of Baja California Norte, Mexico. Regional haze: According to the EPA, regional haze is visibility impairment that is produced by activity that emits fine particles and their precursors over a geographic area. Reliability: The ability of the electric system to supply the demand and energy requirements of the customers when needed and to withstand sudden disturbances Renewable energy: As defined by the IRP Rule, electrical energy generated by means of a low or zero emissions generation technology with substantial longterm production potential and generated by use of renewable energy resources that may include solar, wind, hydropower, geothermal, fuel cells that are not fossil fueled and biomass resources. See biomass resource Renewable resources: Generation resources that are based on a renewable fuel supply Retail sales: The sale of energy to end users. Risk plot: The process of transposing a distribution histogram by measuring the mean and the 95 th percentile and plotting the mean on the xaxis and the 95 th percentile on the yaxis. Scenario: A combination of sensitivity values used to generate portfolios Sensitivity: A variable that has a significant impact on risk evaluation 177

190 Appendix A Glossary PNM IRP Solar: Electric generation fueled directly by sunlight Solar hybrid: A thermal solar facility with the ability to supplement heat from the sun with heat derived by burning natural gas Spinning reserves: Backup energy production capacity which can be available to a transmission system within ten minutes and can operate continuously for at least two hours after being brought online. Spot prices: The price quoted for immediate settlement (payment) of a commodity. Stochastic Analysis: Stochastic financial risk analysis Strategist : The resource portfolio modeling software that PNM uses for resource plan optimization. Strategist is a registered trademark of Ventyx. Total System Costs: Total sum of annual costs for meeting the system s energy requirements with all resources. Tariff: Open Access Transmission Tariff Upper tail: A value on a scale of 100 that indicates the percent of a distribution that is equal to or below 95% of the distribution (also referred to as 95 th percentile) TriState: TriState Generation and Transmission cooperative Valencia: Valencia Generation Facility located near Belen, New Mexico Variable costs: Costs that change with unit output. Contrast fixed costs Water intensity: A measure of the water resource needed to generate over a defined period. Wheeling: Transportation of electric power over transmission lines Wind: Electric generation fueled by wind turbines 178

191 Appendix B Load Forecast Data PNM IRP APPENDIX B LOAD FORECAST DATA Hourly load forecasts numbers are input to the resource optimization model, which then processes the hourly data into a typical week for each month. The typical week shape changes dramatically season to season. The following figure presents the typical week load shapes for four months, January, April, July and October showing seasonal variation with regard to both magnitude of the daily peak as well as time of day for the monthly peak. This shows the importance of modeling load data throughout the year to capture the need for different types of resources. DETAILED ENERGY EFFICIENCY FORECAST The following tables show the programs and associated cumulative annual savings and annual budgets for each of the energy efficiency cases presented in the IRP in Section 7 Reviewing Future Resource Options. The scenarios presented are based on the gross energy savings PNM is able to claim to meet the EUEA savings targets. PNM can claim 12 months of savings for every measure taken during a calendar year. The load impact is less than these annualized savings amounts as the load impact for each measure only impacts the months the measure was implemented. For example, a compact fluorescent bulb purchased in December through the Residential Lighting Program would provide twelve months of savings towards meeting the EUEA goals, but only one month of load savings for that year. The load impact is summarized in Table

192 Appendix B Load Forecast Data PNM IRP

193 Appendix B Load Forecast Data PNM IRP

194 Appendix B Load Forecast Data PNM IRP