Minnesota Statewide Energy Efficiency and Carbon Saving Potential Study

Transcription

1 Minnesota Statewide Energy Efficiency and Carbon Saving Potential Study Advisory Committee Meeting #1 Great River Energy Elm Creek Boulevard Maple Grove, MN June 13, 9:00 am 12:00 pm

2 Advisory Committee Purpose Provide input on key study parameters and policy recommendations Act as liaison for their organizations; consult with other internal stakeholders and subject-matter experts within their organizations, and keep them informed as needed

3 Today s Agenda Meeting kick-off Project overview Modeling approach / data needs Discussion on key study issues Policy preview Audience comments / next steps Meeting Objectives: Understand the overall study goals, main tasks involved, and timeline Understand the technical approach that will be used, and provide feedback on that approach Provide feedback on three additional key areas: Proposed underserved/emerging markets to include in study Proposed primary data collection plan Whether to include delivered fuels in scope of study

4 Study Overview Study Goals Project Team Review Main Study Tasks Stakeholder Involvement Project Schedule

5 DSM Study Goals 1. Estimate statewide natural gas and electric energy efficiency and carbon saving potential in Minnesota for Produce actionable data resources for utilities regarding which market sectors, geographical areas, service territories, end uses, measures and programs should be targeted to help realize cost-effective energy efficiency potential. 3. Provide multiple opportunities for stakeholders to participate in the project to help advance robust energy policies and CIP programs in Minnesota.

6 Team Organization

7 DSM Project Team Center for Energy and Environment Jenny Edwards Demand-Response Mike Bull Stakeholder Work + Policy Recs Carl Nelson Project Manager + Programs Dave Bohac Emerging Tech Chris Plum Emerging Tech + Contract Admin Optimal Energy Seventhwave Matt Socks Modeling + Data Phil Mosenthal Jeanette LeZaks Scott Pigg Doug Ahl Behavior programs + Market Studies + Data ACEEE National Best Practices E SOURCE Emerging Tech, Programs

8 Summary of Main Study Tasks Data collection Existing New Measure research Gaps in TRM Emerging technology Programs research Technology-based Behavioral Demand-response Estimate potential Underserved markets analysis Policy recommendations

9 Data Collection Ensure robust inputs for the model Provide useful information for program implementation, when possible Collect existing data, as well as collect new primary data to fill in gaps in existing data

10 Data Collection Example Small commercial characterization field study 1400 survey completions Almost 100 site visits to 4 small business segments that comprise a majority of energy load

11 Underserved and Emerging Market Sectors Goal: Identify program and policy options to increase CIP achievements in three focus areas. Method: Focus areas will be researched in more detail. We will make recommendations regarding: Applicable measures Achievable potential Program and policy barriers and opportunities

12 Measure Research Review of TRM to find gaps Inclusion of most promising emerging technologies that could provide new savings opportunities in 2020 and beyond

13 Efficiency Programs Research Conduct best practices analysis and make recommendations for new or improved program models that could save additional energy and carbon

14 Behavioral Programs Recommendations for and analysis of new behavioral program designs that build upon or are more impactful than the typical approaches now common

15 Demand Response Recommendations for demand response measures and programs that can reduce peak demand and save additional energy and carbon

16 Four Types of Potential to be Calculated Technical The theoretical maximum amount of energy use that could be displaced by efficiency Economic Maximum Achievable Program Subset that is cost-effective Subset that is achievable considering market barriers, given the most aggressive program scenario possible Subset of achievable, given constraints in implementing a particular portfolio of programs

17 Policy Recommendations Recommendations for how Minnesota can maximize energy and carbon reductions through policy changes to the existing framework

18 Stakeholder Input Advisory Committee Approximately 15 members, with at least one rep for each sector Quarterly meetings, first meeting end of May, early June Individual Interviews Approximately 20, to be completed by the end of June Phone survey of approximately 40 stakeholders Sector meetings 5 Sectors: Utilities, Implementers/Trade Allies, Clean Energy, Consumers, Local Governments, At least one meeting for each sector by fall of 2017 Technical issue workshops Cross Sector meetings, on specific technical issues (TBD) Public Forums Two Forums: Fall 2017, Winter 2018 (topics TBD)

19 Schedule April June Summer Fall Winter Spring 2018 August 2018 Begin collection of existing data from utilities Deadline to apply for Advisory Committee 1 st Advisory Committee meeting Data gaps identified, and primary data collection begins Sector stakeholder meetings Start technical issue workshops 2 nd Advisory Committee meeting 1 st Forum Primary data collection completed Preliminary model runs completed 3 rd & 4 th Advisory Committee meetings 2 nd Forum 5 th Advisory Committee meeting Draft of report Final report completed

20 Potential Study Methodology Overview

21 Study Overview A 10-year EE potential study for the period An estimate of the EE potential for electricity and natural gas. An estimate of the EE potential for the residential, commercial (including institutional and agricultural), and industrial sectors. The study does not include transportation efficiency. Estimates of technical, economic, maximum achievable, and program potential.

22 Four Types of Potential to be Calculated Technical The theoretical maximum amount of energy use that could be displaced by efficiency Economic Maximum Achievable Program Subset that is cost-effective Subset that is achievable considering market barriers, given the most aggressive program scenario possible Subset of achievable, given constraints in implementing a particular portfolio of programs

23 A Note on Cost-Effectiveness Measures the relative performance or economic attractiveness of an energy efficiency investment compared to a baseline of not making the investment. Compares the present value of costs & benefits of efficient equipment with those of baseline (nonefficient) equipment.

24 Analysis Regions Separate results for each of eleven utilities or groupings of utilities, as follows: Seven groupings of investorowned utilities (IOUs) Cooperative utilities in Climate Zone 7A Cooperative utilities in Climate Zone 6A Municipal utilities in Climate Zone 7A Municipal utilities in Climate Zone 6A

25 Individual Utilities Allocation of Potential Potential Models IOU IOU IOU IOU Cooperative utilities Coop Coop Coop Coop Coop Coop Municipal utilities Muni Muni Muni Muni Muni Muni

26 Top-down Analysis Begins with energy sales forecast Disaggregated by sector, segment (typically building type), and end-use Measure savings expressed as a percentage of total applicable end-use energy Generally by building type and market (new construction, renovation, replacement, retrofit) Measure costs in terms of $/kwh or $/MMBtu saved Penetrations are a percent of total available savings In contrast to bottom up analysis which expresses costs and savings per widget.

27 Analytical Workflow

28 Baseline Sales Forecast and Disaggregation Forecast energy sales by sector over analysis period (i.e ) Separates new construction vs. existing building sales Disaggregate forecast by segment and end-use Adjust forecasts as necessary to reflect baseline: Remove embedded program efficiency Estimate embedded codes & standards impacts Remove opt-out industrial sales Remove non-building sales (e.g., transportation)

29 Proposed Segmentation, Building Types Table 1: Building Type Segmentation by Sector Residential Commercial/Industrial Single Family Small Office Multifamily (2-4 units) Large Office Multifamily (5+ units) Small Retail LI Single Family Large Retail LI Multifamily (2-4 units) Warehouse LI Multifamily (5+ units) Small Education Large Education Hospitals Lodging Food Service Data Center Public Assembly Agriculture Industrial Other

30 Proposed Segmentation, End-Uses (Electric) Table 2: Electric End-Use Segmentation by Sector Residential Commercial Industrial Space Heating Space Heating Motors Water Heating Cooling - Material Handling Air Conditioning Ventilation - Material Processing Refrigerators Water Heating - Pumps Cooking appliances Lighting - Fans & Blowers Clothes washers Cooking - Other Motors Clothes dryers Refrigeration Compressed Air Dishwashers Office equipment Electro-Chemical Electronics Computing Process Heating Pools, hot tubs Other Process Cooling Lighting HVAC Lighting Other

31 Proposed Segmentation, End-Uses (Gas) Table 3: Natural Gas End-Use Segmentation by Sector Residential Commercial Industrial Space Heating Space Heating Process Heating Water Heating Water Heating Conventional Boiler Other Cooking Space-heating Other Other, Process Other, Non-Process

32 Estimate Applicable End-Use Energy Determined from the Sales Disaggregation & Equipment Saturations By end-use and building type Applicability (to a particular technology) Feasibility (technically feasible) Turnover rate (natural replacement) Not-complete (retrofit) Energy Savings = Sales (kwh or MMBtu) x Applicability Factor x Feasibility Factor x Turnover Factor (replace-ment only) x Not Complete Factor (retrofit only) x Savings Fraction x Net Penetration Rate

33 Interactions and Exclusivity Stock adjustments Measure interactions e.g., building shell improvements interact with efficient cooling/heating equipment Mutually exclusive measures i.e., can do one or other, but not both

34 Measure Characterizations Inputs describing all aspects of the measure (e.g., costs, savings, lifetimes) Relative to an appropriate baseline Characterizations may vary by market and program intervention strategy Measure will include: Conventional measures Emerging technologies and practices Behavioral measures Load management and DR

35 Measure Characterization Inputs Full measure characterizations include numerous inputs General Inputs Sector Primary Fuel and End Use Secondary Fuel and End Use Measure Effective Useful Life (EUL) Baseline EUL (if different) % Savings (Primary Fuel, relative to baseline) Secondary Fuel Savings (relative to primary fuel savings, MMBtu/kWh or kwh/mmbtu) Efficient Equipment Cost Baseline Equipment Cost Incremental Cost per kwh or MMBtu Saved Measure Interactions Measure Mutual Exclusion Early Replacement Retrofit Inputs: Baseline Remaining Useful Life (RUL) Baseline Cost per kwh or MMBtu Saved Baseline Shift Savings Factor Measure Inputs by Building Type: Loadshape and Peak Coincidence Factors Applicability Feasibility Not Complete RET % Savings (if variable by building type) kwh-kw ratio Penetrations O&M and Water Inputs: Efficient Component Life Efficient Component Replacement Cost Baseline Component Life Baseline Component Replacement Cost O&M Levelized Annual Cost Water Savings

36 Interactions and Exclusivity Stock adjustments Measure interactions E.g., building shell improvements interact with efficient cooling/heating equipment Mutually exclusive measures

37 Measure Penetrations Penetration curves model energy efficiency adoption over time Technical and economic penetrations assume all technical or cost-effective potential, respectively, is captured over the analysis period. i.e., penetration curves are largely formulaic Achievable and program potential penetrations consider market barriers Costs Customer Awareness/Willingness Equipment/Contractor Availability Budget Constraints Other market barriers

38 Measure Penetrations

39 Portfolio Cost-Effectiveness Screening Full accounting of technology costs, including capital, fuel, operation and maintenance, and cost offsets such as nonelectricity savings and non-energy benefits. Proper accounting for the benefits, calculated using annual values of long-run avoided energy costs. Precise treatment of various timing effects such as baseline shifts Conduct standard cost-effectiveness tests, e.g., Utility, Participant, Societal, and Ratepayer Impact

40 Cost-Effectiveness Screening Inputs Financial Inputs (e.g., inflation and discount rates) Avoided costs Line loss factors Load shapes Peak coincidence factors Program non-measure (non-incentive) costs Measure inputs

41 Avoided Costs (Electric, Natural Gas) Estimates of current and future costs for energy on the margin Used to calculate $ benefits of saved energy Avoided cost components typically include: Generation (electric) or commodity (gas) energy Peak capacity Transmission and Delivery capacity

42 Watts Load Shapes Distribute annual savings by energy period Generally by end use and building type Can derive from hourly 8760 usage data Specific to geographic region & climate Summer Summer Summer Winter Off- Winter Loadshape Name On-Peak Energy Off-Peak Energy Intermed. Energy Peak Energy Intermed. Energy Grocery_Cool 44.1% 15.8% 23.8% 0.8% % 0.40 Grocery_ElecDHW 16.7% 3.9% 9.1% 9.3% 61.0% 0.35 Grocery_ElecTotl 18.7% 9.6% 11.1% 15.5% 45.1% 0.30 Grocery_Heat 0.0% 0.0% 0.0% 48.6% 51.4% 0.25 Grocery_InLight 17.8% 6.2% 9.6% 12.3% 54.2% 0.20 Grocery_OutLight 6.9% 15.5% 7.1% 34.4% 36.1% 0.15 Grocery_Refrig 16.0% 9.6% 9.9% 17.9% 46.5% 0.10 Grocery_Vent 14.2% 9.7% 9.4% 19.5% 47.2% 0.05 Residential, Single Family, Lighting Hour of Day

43 Peak Coincidence Factors Portion of demand reduction occurring at peak demand Can derive from 8760 usage data Based on max kwh/kw ratio Summer Gener. Capacity Winter Gener. Capacity Loadshape Name Grocery_Cool Grocery_ElecDHW Grocery_ElecTotl Grocery_Heat Grocery_InLight Grocery_Misc Grocery_OutLight Grocery_Refrig Grocery_Vent

44 Emissions Factors CO 2 e, SOx, NO 2 Electric (tonne/kwh), Gas & Petroleum (tonne/mmbtu) Factors for energy generation offset on the margin Monetized benefits as externalities

45 Fundamental Equation Energy Savings = Sales (kwh or MMBtu) x Applicability Factor x Feasibility Factor x Turnover Factor (replacement only) x Not Complete Factor (retrofit only) x Savings Fraction x Net Penetration Rate

46 Electric Measure Potential Example LED Linear Replacement Lamp, REPL

47 Electric Measure Potential Example LED Linear Replacement Lamp, REPL

48 Example Outputs Charts and Figures

49 Example Outputs Charts and Figures

50 Example Outputs Charts and Figures

51 Key Outputs of Analytical Tools Full documentation of measure characteristics and sources Measure- and program-level savings by year, at meter and at generation. Program costs by year, including incentive and non-incentive costs. Cost-effectiveness based on net benefits and benefit/cost ratio, for each measure and each install year, for each program, and for the total portfolio of programs. Program-level summaries of costs and benefits, discounted to the base year. Summary of Utility and Societal costs, total and per kwh saved. Levelized costs by program and for the portfolio. Emissions reductions by measure and by program.

52 Discussion on Key Study Issues Issues 1. Proposed underserved/emerging markets to include in study 2. Primary data collection plan 3. Modeling of delivered fuels opportunities should this be included in the scope? Process Discussion today Provide any additional feedback by June 23 rd Finalize by June 30th

53 Potential Policy Items for Discussion Accounting for Behavioral and Operational Savings Value of Carbon Reductions due to CIP Integration of Demand Response with CIP Strategic Electrification/Fuel Switching Basing CIP Target on Potential Other?

54 ACKNOWLEDGEMENTS This project is supported by: Minnesota Conservation Applied Research and Development (CARD) Grant Program

55 Questions / Comments? Contact: Carl Nelson at cnelson@mncee.org