2013 Integrated Resource Plan

Transcription

1 2013 Integrated Resource Plan Energy Efficiency Modeling Workshop Wind Integration Study Technical Workshop Portfolio Development Roundtable Discussion June 20,

2 Agenda Energy efficiency modeling workshop Lunch Break (1/2 hour) 11:30 PT/12:30 MT 2012 Wind Integration Study workshop Portfolio development roundtable discussion 2

3 Energy Efficiency Modeling Workshop 3

4 Modeling Concerns Raised by Stakeholders Energy efficiency resource cost-effectiveness determination using System Optimizer is not transparent Claim that the definition of price breakpoints between bundles is arbitrary and causes less resources to be selected relative to other resource types Claim that the Company is underestimating the amount and speed of achievable, cost-effective resource acquisitions in states other than Oregon Energy efficiency ramp rates are conservative, particularly in the eastern states, and may be favoring supply-side resources in the near term 4

5 Model Transparency: Methodology Overview Two basic modeling approaches in the industry: Resource optimization (PacifiCorp approach) Load decrement approach Resource specifications constrained by System Optimizer model design Specifications for: Measure bundles Levelized costs Maximum vs. weighted average Cost credits: T&D investment deferral, risk mitigation, other Capacity Load shapes and peak capacity contribution 5

6 Measure Bundles 2011 IRP and IRP Update included 9 different measure (cost) bundles Current modeling requires 1,560 individual resources Current Model Setup (count of resources) Measure Bundles CA OR WA UT ID WY Grand Total Westmain Westmain Walla Walla Walla Walla Yakima Utah Goshen Utah Utah Wyoming $.00 to $ >$.07 to $ >$.09 to $ >$.11 to $ >$.13 to $ >$.15 to $ >$.18 to $ >$.26 to $ >$.83 to $ Grand Total

7 Modeling Levelized Cost Maximum Levelized Cost $70/MWh Subtract T&D investment Deferral $54/kW-year adjusted to MWh (T&D*1000/annual energy) Example 54x1000/5445= $10.70 /MWh Risk Mitigation cost adjustment Subtract $14.98/MWh Other Cost Adjustments Washington s I % Market Price Adjustment around $10.01/MWh Example Modeled Cost = $34.31/MWh 7

8 Load Shapes and Capacity Contribution Hourly load shape composed of fractional values representing each hour s demand divided by maximum demand in any hour for the shape System Optimizer uses a single annual load shape repeated for all simulation years; Planning and Risk model allows multiple annual shapes Capacity planning contribution derived from annual energy patterns Average of July daily fractional values for hours 14 (2 pm) through 19 (7 pm) The averaging period accounts for variability in the timing of the daily peak hour over the simulation period Capacity Contribution = 87% 8

9 Levelized Cost Methodology Costs in $/Generated MWh for comparison with supply-side options Inclusion of conservation credit, non-energy benefits, etc. varies by state Perspective Total Resource Utility State OR WA ID CA WY UT Included In: State and Sector-Specific Line Losses Potential Study Customer Cost Potential Study Utility Investment Potential Study Annual Incremental O&M Potential Study Secondary Fuel Impacts Potential Study Non-Energy Impacts Potential Study 10% Conservation Credit IRP T&D Deferral Benefits IRP Risk Mitigation Benefits IRP 9

10 2012 DSM Potential Assessment Update Key updates from 2010 Assessment Incorporate updated load forecast New codes and standards Effects of PacifiCorp s recent DSM activity Update/revisit measure costs, savings, lifetime, and applicability factors Includes findings from recent program evaluations Coordination of measures and methods with Northwest Power and Conservation Council, Energy Trust of Oregon, and other best practices All economic screening of resources, including for Oregon, performed in IRP model Final report to be included as appendix to IRP 10

11 Resource Ramping Ramping performed as part of potentials assessment Measure-level ramp rates based on those used in the Council s 6 th Power Plan State-specific market ramp rates used to reflect maturity of market, PacifiCorp programs, and realistic short-term acquisition Jurisdictional potentials are achieved within planning period Model selections used to set Class 2 acquisition targets 11

12 New Resource Modeling Functionality Current SO model does not allow for annually varying capacity for a single resource option; hence a resource needs to be defined for each year Based on a 20-year simulation, this limitation multiplies the number of resources needed by 20 for each measure bundle and location New SO model allows a vector of maximum annual capacities to be associated with a single resource, reducing the number of resources by 20-fold; data processing algorithms modified in both SO and Planning and Risk models to accommodate this change With the number of bundles no longer serving as a significant modeling constraint, bundles can be defined with narrower and more uniform price ranges Improvement to resource selection accuracy Reduces judgment needed to define bundle price breakpoints 12

13 New Resource Modeling Functionality With the new functionality, the Company proposes to disaggregate measures into narrower price bundles and test resource selection impact relative to the current bundle definitions Will the new functionality address stakeholder concerns? If not what do stakeholders propose? 13

14 Resource Selection Reporting Developed pivot table report that shows resource capacity selected by measure bundle, state, and year Can augment to show amount selected relative to total available Sum of Capacity Year DSM_ST DSM Name Grand Total CA DSM, Class 2 [00-07] DSM, Class 2 [08-09] CA Total ID DSM, Class 2 [00-07] DSM, Class 2 [08-09] ID Total OR DSM, Class 2 [00-07] DSM, Class 2 [08-09] DSM, Class 2 [10-11] OR Total UT DSM, Class 2 [00-07] DSM, Class 2 [08-09] UT Total WA DSM, Class 2 [00-07] DSM, Class 2 [08-09] DSM, Class 2 [10-11] WA Total WY DSM, Class 2 [00-07] DSM, Class 2 [08-09] WY Total Grand Total ,

15 2012 Wind Integration Study Technical Workshop 15

16 Agenda Overview of the wind study Step-by-step example of regulation reserves calculations Example is for the 97% tolerance level (the same approach is done for the 93% and 95% tolerance level) We will track a single hour to show how forecast errors are processed and applied to establish regulation reserve results Interim results of regulation reserve calculations Cost estimation 16

17 Overview of the Wind Study Compile 10-minute wind & load data ( ) Determine need for reserves beyond what is required for contingency Regulation reserves (following & regulation) Variability and uncertainty in wind and load Develop operational forecasts Compute/record forecast errors Process forecast errors (three tolerance levels: 93%, 95%, 97%) Apply forecast error data to historical operation data to establish reserve demand Ramp reserves Flexibility required to manage system fluctuations with perfect foresight Estimate reserve and incremental system balancing costs 17

18 Reserves Requirements Contingency reserves outage insurance, not to be consumed by other requirements Ramp Reserves minimum flexibility required to manage variability Regulation Reserves Sufficiency determined to cover uncertainty to a reasonable expectation Planning Reserves not in scope 18

19 Regulation Reserve Calculation Steps 1. Sorting errors into forecast bins by component (following and regulation for both load and wind) 2. Calculation of component need from forecast bin data 3. Compilation of component need a) Plots b) Tables 4. Application of component need to historical data 5. Calculation of total requirement for each interval 6. Calculation of total requirement for a given period 7. Calculation of failure rate to test results 19

20 1. Sorting Errors into Forecast Bins by Component Load following example (same concept applies to load & wind regulating and wind following) Bins are defined by every 5th percentile of recorded data (20-bins), separately for East and West, for a given period (January 2011 as shown) Bins are arranged by forecast quantity and the errors tabulated as below Note MW would be sorted into bin #14 at right, as it is between MW and MW. EAST DATE / TIME LOAD FOLLOWING FORECAST LOAD FOLLOWING ERROR BIN ASSIGNMENT 01/01/ :50 6, /01/ :50 6, /01/ :50 6, /01/ :50 6, /01/ :50 6, /01/ :50 6, /01/ :50 6, /01/ :50 6, East Bin Number Percentile Load Forecast MAX 7, , , , , , , , , , , , , , , , , , , , MIN 5,

21 2. Calculation of Component Need from Forecast Bin Data Reserves Requirements for forecasts within Bin 14 Errors in bin 14 Example: Bin Down Reserves Load Forecast Up Reserves Sample key values from bins by error coverage tolerance (97% illustrated above, same approach applied to 93% and 95% tolerance levels) Up and Down reserves are estimated above as follows: 68 MW would be the 98.5 percentile, -90 MW would be the 1.5 percentile of bin #14, pertaining to next-hour load forecasts between 6387 MW and 6493 MW (errors are forecast minus actual) The same process is used to calculate the component need for load and wind regulating and wind following 21

22 3a. Compilation of Component Need into Plots The reserves requirements (here for Load Following, January 2011) may also be represented graphically. Bin #14 is centered at roughly 6440 MW load forecast for the next hour. The change in need around bins 5 and 14 are influenced by the daily load ramp for the period shown (January 2011) 22

23 3b. Compilation of Component Need into Tables Bins arranged by component forecast quantity Component reserves quantities indicated by forecast values Bins added to the top and bottom to catch any forecast values exceeding the calculated bins (MAX and MIN) According to this example, a nexthour load forecast of 6410 MW in January, in the East system, would call for 90 MW of up reserves and 68 MW of down reserves for the load following component. January 2011 Following Load West East Bin Up Load Down Up Load Down Forecast Forecast MAX MIN

24 4. Application of Component Need to Historical Data, Load Following Time East East East East East East East East Following Forecast Load: Load Following Up demand (with perfect foresight) Load Following Down demand (with perfect foresight) Load Following Up Reserves Specified by Tolerance Level Load Following Down Reserves Specified by Tolerance Level Actual Load (10-min Avg) Actual Load (Hourly Avg) 01/01/ :40 6, , /01/ :50 6, , /01/ :00 6, , /01/ :10 6, , /01/ :20 6, , /01/ :30 6, , /01/ :40 6, , /01/ :50 6, , Load Following forecast of MW prescribes 89.6MW and 68.2MW of Up and Down reserves, respectively (blue columns) The demand (green columns) calculates the component reserves demand for each interval with perfect foresight, in this case the average of the 1:00 hour ( MW) minus the forecast of MW. Following reserves are represented in one interval per hour, regulating reserves in six intervals per hour. 24

25 4. Application of Component Need to Historical Data, Load Regulating Load Regulating forecast of 6,470.5MW prescribes 121.4MW and 94.2MW of Up and Down reserves, respectively (blue columns) The demand (green columns) calculates the component reserves demand for each interval with perfect foresight, in this case the average of the ten minutes starting at 1:00 a.m. (6, MW) minus the forecast of 6,470.5 MW. 25

26 4. Application of Component Need to Historical Data, Wind Following East East East East East East East East Following Forecast Wind: Wind Wind Following Following Up Down demand (with demand (with perfect perfect foresight) foresight) Wind Follow Up Reserves Specified by Tolerance Level Wind Follow Down Reserves Specified by Tolerance Level Time Actual Wind (10-min Avg) Actual Wind (Hourly Avg) 01/01/ : /01/ : /01/ : , /01/ : , /01/ : , /01/ : , /01/ : , /01/ : , Process repeated for wind following The actual wind generation for the 1:00 hour (average MW) is compared to the forecast wind generation (1, MW) The process is continued for regulating forecasts and demands 26

27 4. Application of Component Need to Historical Data, Wind Regulating East East East East East East East East Wind Regulating Forecast Wind Regulating Up demand (with perfect foresight) Wind Regulating Down demand (with perfect foresight) Wind Regulating Up Reserves Specified by Tolerance Level: Wind Regulating Down Reserves Specified by Tolerance Level: Actual Wind Time (10-min Avg) 01/01/ : (41.90) /01/ : (37.59) /01/ : (82.49) /01/ : (69.23) /01/ : (51.37) /01/ : (50.76) Wind Regulating forecast of 999.5MW prescribes 137.3MW and 75.6MW of Up and Down reserves, respectively (blue columns) The demand (green columns) calculates the component reserves demand for each interval with perfect foresight, in this case the average of the ten minutes starting at 1:00 a.m. ( MW) minus the forecast of MW. 27

28 5. Calculation of Total Requirement for Each Interval Each of the four component reserve requirements are represented in each ten-minute time interval The total reserves demand prescribed is the root sum square of the four component demands Assumes no significant short-term correlation 1 This total reserves demand is calculated in each time interval 1 Western Wind and Solar Integration Study, prepared by NREL, (May, 2010), p. 92. The report is available for download from the following hyperlink: 28

29 5. Calculation of Total Requirement for Each Interval Time East East East East East East East Flag if Up Flag if Down Reserves Reserves Specified at Specified at Total Up Total Down Given Given Reserves Reserves Total Up Total Down Tolerance Tolerance Specified by Specified by Reserves Reserves Level is Level is RSS at Given RSS at Given Demand Demand Insufficient to Insufficient to Tolerance Tolerance (with perfect (with perfect Cover Cover Level Level foresight) foresight) Demand Demand 01/01/ : (167.82) (27.86) /01/ : (37.59) (37.25) /01/ : (82.49) (61.66) /01/ : (69.23) (22.81) /01/ : (51.37) (26.51) /01/ : (50.76) (23.85) 0 0 The total hourly (shaped) regulation reserves for a given tolerance level is calculated in the purple columns The total reserves requirements are compared to the calculated reserves demands (in green); and whether or not there is a failure (demands greater than specified reserves) is evident in that interval is noted. 29

30 6. Calculation of Total Requirement for a Given Period The total regulation reserves requirement is calculated for each ten minute interval by month, East and West, and for each tolerance level (97%, 95%, 93%) The hourly regulation reserves requirement is the average of each hour s respective ten-minute intervals The monthly regulation reserves requirement is the average of each month s respective ten-minute intervals The annual regulation reserves requirement is the average of each year s respective monthly requirements 30

31 6. Calculation of Total Requirement by Year, Interim Results for 97% Tolerance Level Total Reserves beyond Contingency (MW) Regulation West Regulation East Ramp Total Total Reserves beyond Contingency, Incremental from Wind (MW) Regulation West Regulation East Ramp Total The above reflect the annual average of the hourly up reserves demands on a historical basis. By 2011, the incremental regulation requirement from wind is approximately 7% of the wind capacity. 31

32 7. Calculation of Failure Rate to Test Results Failure Rate, 2011 Operational Data West East January 3.1% 2.6% February 3.7% 2.6% March 3.4% 2.8% April 3.2% 2.9% May 3.4% 3.0% June 3.5% 3.0% July 3.4% 3.1% August 3.3% 3.0% September 2.8% 2.5% October 2.7% 3.0% November 2.9% 2.5% December 3.1% 2.5% Annual Average 3.2% 2.8% The number of failed intervals is used to gage the reasonableness of the reserves requirements 0% failure rate would represent excessive reserves requirements A high failure rate would indicate insufficient requirements 32

33 Regulation Reserves Cost Estimation The Planning and Risk model supplies reserves in 5 categories: Input Field Definition Reserve Requirements Entered AS1 Up Regulation Ramp and Regulation AS2 Down Regulation not used AS3 Spin Contingency AS4 NonSpin Contingency AS5 30 Minute NonSpin not used Different qualities of reserves are specified to fill different reserves demands Segregation assures Regulation and Contingency requirements appropriately met 33

34 Regulation Reserves Cost Estimation Step 1 incorporates actual load and idealized wind energy, plus regulation reserves required for load to calculate a base system cost to serve. Step 2 exchanges the ideal wind energy delivery for actual, and adds the incremental regulation reserves required for wind. The difference between Steps 2 and 1 represents the cost of inter-hour and intra-hour wind reserves. Steps 3 and 4 incorporate day-ahead load forecasts and separate dayahead load balancing from wind balancing. Step 5 calculates the total system cost, using the system commitment from step 4, derives a day-ahead system balancing charge for wind generation. PaR Model Simulation Forward Term Load Profile Wind Profile Incremental Regulation Reserve Day-Ahead Forecast Error Actual Ideal Shape None None Actual Actual Yes None Regulation Reserve Cost = System Cost from PaR Simulation 2 less System Cost from PaR Simulation Day-Ahead Forecast Day-Ahead Forecast Yes None Actual Day-Ahead Forecast Yes For Load Actual Actual Yes For Load and Wind System Balancing Cost = System Cost from PaR Simulation 5 (which uses the unit commitment from Simulation 4) less System Cost from PaR Simulation 2 34

35 Portfolio Development Roundtable 35

36 Portfolio Development Goals Address public stakeholder concerns that portfolios don t exhibit enough resource diversity for risk assessment Integrate Energy Gateway scenarios as part of core case evaluation using consistent set of input assumptions Utah 2011 IRP Acknowledgement Order states: We remind the Company its existing system should represent only facilities which have already received a CPCN or for which the Company has a binding contract in place. All other facilities should be included in core or sensitivity cases as options. Range of core cases should distinguish economic performance of each Energy Gateway scenario Incorporate geothermal resources as part of an alternative RPS compliance strategy 36

37 Energy Gateway Project Segments 37

38 Energy Gateway Scenarios Five Energy Gateway Scenarios Segments Comments 1 Reference C Mona-Oquirrh-Terminal 2 System Improvement C, D, and G 2013 Business Plan 3 West/East Balancing Area Consolidation C, D, E, G, H Increase interchange between PACE and PACW 4 Triangle C, D, G, F East side wind and improved reliability 5 Full Gateway C, D, E, G, H, F All Energy Gateway segments For each Energy Gateway scenario, the Company could run the System Optimizer with the same set of portfolio core cases; strawman list currently includes 21 core cases, resulting in 105 portfolios Transmission capital costs included as out-of-model fixed cost adjustments Use average PVRR across each set of EG portfolios to inform selection of final EG portfolios for preferred portfolio selection Evaluate EG scenarios as part of acquisition path analysis Alternative transmission scenarios could be developed and run against the core cases 38

39 Scenario Development Framework Energy Gateway Scenarios Portfolio Development Themes Scenario Assumptions Reference Segment C Only Reference GHG Regulation/Gas Reliance Targeted Clean Technology Focus Market Reliance CO2/Gas Prices State/Fed Energy Policies Tech. Cost/Performance Resource Constraints Renewables Floor System Improvement Segments C, D, G Balancing Area Consolidation Segments C, D, E, G, H (Hemingway to Bethel) Reference GHG Regulation/Gas Reliance Targeted Clean Technology Focus Market Reliance Reference GHG Regulation/Gas Reliance Targeted Clean Technology Focus Market Reliance CO2/Gas Prices State/Fed Energy Policies Tech. Cost/Performance Resource Constraints Renewables Floor CO2/Gas Prices State/Fed Energy Policies Tech. Cost/Performance Resource Constraints Renewables Floor Triangle Segments C, D, F, G Reference GHG Regulation/Gas Reliance Targeted Clean Technology Focus Market Reliance CO2/Gas Prices State/Fed Energy Policies Tech. Cost/Performance Resource Constraints Renewables Floor Full Gateway Segments C, D, E, F, G (Hemingway to Bethel) Reference GHG Regulation/Gas Reliance Targeted Clean Technology Focus Market Reliance CO2/Gas Prices State/Fed Energy Policies Tech. Cost/Performance Resource Constraints Renewables Floor 39

40 Portfolio Development and Modeling Process State Retail Load Forecasts RPS Rules (including REC Trading) Energy Gateway Scenario Specifications Alternative Resource Achievable Potential Assumptions Alternative Natural Gas Price Forecasts RPS Scenario Maker Minimum RPS Compliance Resource Schedules Cases System Optimizer Execution Portfolios PaR Model Execution (Generate Risk Adjusted Portfolio Costs) Eligible Resource Options RPS resource schedules used to specify lower bounds on resource capacity selection; model allowed to select more. Will incorporate minimum schedules with and without Geothermal. Alternative CO2 Cost Scenarios Alternative Wind/Solar Technology Trends Market Purchase Constraint Assumptions Alternative Load Forecasts Planned environmental investments required for coal resources will be analyzed endogenously among all the scenarios. Risk Assessment Acquisition Path Analysis 40

41 Scenario Assumptions Attributes by Scenario Type CO2 Cost None ($0/ton) Medium ($16/ton, starting in 2022 escalating at inflation) High ($34/ton, starting in 2018 escalating at inflation+5%) Hard Emissions Cap Natural Gas/Electricity Cost Medium Low High State/Federal Energy Policies 1/ No RPS rules Current state RPS rules - Wind only strategy Current state RPS rules - Wind and geothermal strategy Federal Clean Energy Standard (CES) Federal RPS Renewable PTC extension past 2012 High achievable energy efficiency potential Load Forecast Medium Low High 1 in 10 Peak Weather 1 in 20 Peak Weather Technology Game-changers Wind/Solar - Increased capacity factors, reduced cost 2/ Advanced Energy Storage - Commercially Viable/Favorable Costs Resource Constraints Constrain FOT selection to maximum availability Prevent FOT selection in PacifiCorp East Constrain distrib. solar selection to max. achievable potential 1/ RPS rules establish a lower bound resource constraint only. 2/ Apply info from industry RFI on capacity factor assumptions. 41

42 Sample Core Cases CORE CASES Themes State/Federal Energy Policies 2/ No RPS rules Current state RPS rules - Wind only strategy X X X X X X X X X X X X X X X X X X Current state RPS rules - Wind and geothermal strategy X Federal Clean Energy Standard (CES) X Federal RPS X X X X X X X X X X X X Renewable PTC extension past 2012 X X X X X High achievable energy efficiency potential X Load Forecast Medium X X X X X X X X X X X X X X X X X X X X X Low High 1 in 10 Peak Weather 1 in 20 Peak Weather Technology Game-changers Wind/Solar - Increased capacity factors, reduced cost 3/ Advanced Energy Storage - Commercially Viable/Favorable Costs Resource Constraints Constrain FOT selection to maximum availability Prevent FOT selection in PacifiCorp East Constrain distrib. solar selection to max. achievable potential 1/ Fixed resources from Business Plan portfolio. 2/ RPS rules establish a lower bound resource constraint only. 3/ Apply info from industry RFI on capacity factor assumptions. Reference GHG Regulation/Gas Reliance Targeted Clean Technology Focus X Market Reliance Hard Gas Price Bookends Medium Medium Medium High CO2 High CO2 High CO2 Accel. Accel. Accel. Emissions 2013 CO2 Cost/ CO2 Cost/ CO2 Cost/ Cost/ Cost/ Cost/ CO2 Cost/ CO2 Cost/ CO2 Cost/ Cap/ Energy Distributed Geothermal Maximum Status Business Low Cost High Cost Medium Low Gas High Gas Medium Low Gas High Gas Medium Low Gas High Gas Medium Efficiency Solar RPS Federal Federal System No East Case Description Quo Plan 1/ Supply Supply Gas Price Price Prices Gas Price Prices Price Gas Price Price Price Gas Price Mandates Mandates Strategy CES RPS Availability Reliance Case Number CO2 Cost None ($0/ton) X X X X Medium ($16/ton, starting in 2022 escalating at inflation) X X X X X X X X X X High ($34/ton, starting in 2018 escalating at inflation+5%) X X X Hard Emissions Cap X Natural Gas/Electricity Cost Medium X X X X X X X X X X X X Low X X X X High X X X X X X 42

43 Sample Sensitivity Cases Sensitivity Cases Themes Extreme Extreme Weather: Weather: Advanced 5th 10th Energy No RPS Low High Percentile Percentile Storage Case Description Loads Loads Peaks Peaks Case Number CO2 Cost None ($0/ton) X Medium ($16/ton, starting in 2022 escalating at inflation) X X X X X High ($34/ton, starting in 2018 escalating at inflation+5%) Hard Emissions Cap Natural Gas/Electricity Cost Medium X X X X X X X Low High State/Federal Energy Policies 2/ No RPS rules X X Current state RPS rules - Wind only strategy X X X X X Current state RPS rules - Wind and geothermal strategy Federal Clean Energy Standard (CES) Federal RPS Renewable PTC extension past 2012 High achievable energy efficiency potential Load Forecast Medium X X X Low X High X 1 in 10 Peak Weather X 1 in 20 Peak Weather X Technology Game-changers Wind/Solar - Increased capacity factors, reduced cost 3/ Advanced Energy Storage - Commercially Viable/Favorable Costs Resource Constraints Constrain FOT selection to maximum availability Prevent FOT selection in PacifiCorp East Constrain distrib. solar selection to max. achievable potential 1/ Fixed resources from Business Plan portfolio. 2/ RPS rules establish a lower bound resource constraint only. 3/ Apply info from industry RFI on capacity factor assumptions. Alternative Load Forecasts X Other Wind/Solar Technology Resurgence X 43

44 Meeting Schedule Next Meeting: July 13, 2012 Transmission Planning Portfolio Case Development August 2, 2012 Load and resource balance, resource adequacy and conservation voltage reduction 44