1 / 53

Cost-effectiveness Workshop Four: Demand Response

Cost-effectiveness Workshop Four: Demand Response. Energy Division October 19 th , 2012. Workshop Agenda. Introduction and Overview 10:00 – 10:15am Topic 1: External Budget Allocation 10:15 – 11:15am Break 11:15 – 11:30am

didina
Download Presentation

Cost-effectiveness Workshop Four: Demand Response

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Cost-effectiveness Workshop Four: Demand Response Energy Division October 19th, 2012

  2. Workshop Agenda • Introduction and Overview 10:00 – 10:15am • Topic 1: External Budget Allocation 10:15 – 11:15am • Break 11:15 – 11:30am • Topic 2: Portfolio vs. Program Analysis 11:30am – 12:15pm • Lunch 12:15 – 1:15pm • Topic 3: Avoided Cost Adjustment Factors 1:15 – 2:15pm • Break2:15 – 2:30pm • Topic 4: Dual Participation 2:30 – 3:15pm • Topic 5: Participant Costs 3:15 – 3:45pm • Topic 6: Optional Benefits 3:45 – 4:15pm • Summation and Next Steps 4:15 – 4:30pm

  3. Regulatory Overview • D.10-12-024 (December 2010): • Adopted the Demand Response Cost-effectiveness Protocols • Ordered a workshop and Energy Division guidance on how to prepare the cost-effectiveness analysis portion of the 2012-14 Demand Response application (subsequently A.11-03-001 et al) • D.12-04-045 (May 2012): • Approved the 2012-14 Demand Response Program budgets • Ordered staff to provide guidance on the format to be used for any cost-effectiveness analysis required in the utilities’ compliance filings • Ordered workshops to address and develop cures for deficiencies in the Protocols

  4. Demand Response Workshop Objectives • To provide parties the opportunity to discuss the aspects of the demand-side cost-effectiveness framework that are particular to demand response programs. • To correct any deficiencies or ambiguities in the DR Cost-Effectiveness Protocols and Reporting Template. • To explore new ideas of how the DR cost-effectiveness framework could be improved to provide a more accurate measure of the cost-effectiveness of demand response programs. This workshop will not re-visit cost-effectiveness issues common to all demand-side programs discussed during the June cost-effectiveness workshops.

  5. Topic 1: External Budget Allocation • Utilities are required to include all money related to Demand Response programs in their cost-effectiveness analysis of each program. This includes money from Category 4, 6, 7 and 8 budgets in addition to the Category 1, 2, 3, or 10 program administration budgets. The cost-effectiveness analysis of each program may also include funds approved in other proceedings, such as incentives approved in General Rate Cases.

  6. External Budget AllocationDiscussion Question 1 • How can we better and more clearly allocate Category 4, 6, 7 and 8 budgets to the cost-effectiveness analysis of each program?

  7. External Budget AllocationDiscussion Question 1 (cont.) • ED May 2012 guidelines required utilities to use the following format when filing their post-Decision Advice Letters: ED intends to add this reporting format to the DR Reporting Template.

  8. External Budget AllocationDiscussion Question 1 (cont.) • ED January 2011 guidelines state: If a budget is requested for a DR activity which supports more than one DR program, that portion of that budget that includes administrative costs of the types listed above must be divided among the DR programs it supports. The allocation of budget should be based, whenever possible, on the actual work performed as part of that activity. ..If it is unknown or unclear how the activities support specific DR programs, then the budget should be proportionally allocated among the DR programs supported by that activity based on the total costs of each DR program.

  9. External Budget Allocation Discussion Question 2 • Which budgets from proceedings other than the three-year Demand Response budget proceedings should be included, and how should they be allocated? • GayatriSchilberg, consultant to TURN, prepared the following presentation on this topic.

  10. External Capital Costs in DR CE Method Presentation of Gayatri Schilberg, Senior Economist, JBS Energy, Inc. on behalf of TURN gayatri@jbsenergy.com (916) 372-0534 Oct 19, 2012 CPUC Protocols Workshop

  11. Issues Covered Here • Inclusion of Information Technology (IT) Costs from other proceedings • Treatment of Capital Costs in the Cost-Effectiveness (CE) Tests

  12. Inclusion of IT Costs from Other Proceedings “If the Commission allowed the Utilities to include and exclude the cost of an activity as they deem fit, we would never know the true costs of a program.” (D.12-04-045)

  13. Proposal Include expenditure from other proceedings if: • Planned, requested, or approved • DR drives or is supported by project (calc %) • Both new project and upgrades to existing • Capital (5-year deprec for software) and also O&M • SCE: Multi-year project cost inflated to year of completion

  14. Multi-Year Software Costs

  15. Sample Software Cost—E3 Method

  16. Sample Software Cost– SCE Method

  17. All Years of Cost and BenefitShould be Included Consensus Framework: “Cost-effectiveness will be performed on a lifecycle basis, comparing the net present value of benefits and costs. The lifecycle will ordinarily cover either the expected economic life of the major investment under that DR program, or the period in which benefits will occur due to the costs that will be incurred during the DR program cycle.”

  18. Problems with 3-Year CE Method • Mismatch of time frame of costs and benefits • Drops off 2-4 years of capital software costs. • Drops off 7 years of costs for Auto DR • Inadequate to analyze startup enrollment and marketing costs • Mix of cash flow and present value methods

  19. Proposal • Lengthen CE analysis to cover length of cost and benefit stream (at least 5 and possibly 10 years) • May require assumption that benefits and A&G costs remain same (real $) for length of period • May require estimates of future software upgrades (e.g. in year 6) • Present value and collapse into 1 indicator?

  20. Additional Issues • May require greater CE evaluation of software in GRCs • Additional cost of software may sink DR program.

  21. Topic 2: Portfolio versus Program Analysis • During the 2012-14 budget cycle, it was difficult to determine the usefulness of the portfolio cost-effectiveness results, since the definition of the demand response “portfolio” was not clear.

  22. Portfolio vs. Program Analysis Discussion Questions • How could we better define the demand response portfolio so as to better analyze Demand Response cost-effectiveness at the portfolio level? • Should Demand Response programs approved in proceedings other than the three-year Demand Response budget proceedings, such as General Rate Cases, be included in the definition of the Demand Response portfolio? • Should non-program budgets approved in proceedings other than the three-year Demand Response budget proceedings be included in the definition of the Demand Response portfolio? • Assuming we can develop an acceptable definition of the Demand Response portfolio, would that be preferable to cost-effectiveness analysis at the program level?

  23. Topic 3: Avoided Cost Adjustment Factors

  24. Adjustment Factors Discussion Questions • How could the E3 method for determining the A factor (and the monthly capacity allocations) be refined and improved? • Are the current adjustment factors sufficient and appropriate for measuring the avoided costs of all types of existing Demand Response programs (e.g., reliability, price-responsive, load control), as well as future Demand Response resources (e.g., Demand Response products designed to respond to intermittent generation)? • How could the accuracy and consistency of the other avoided cost adjustment factors be improved?

  25. A Factor – Availability • How could the E3 method for determining the A factor (and the monthly capacity allocations) be refined and improved? *enhanced program only

  26. A Factor – Availability

  27. ‘A’ Factor Discussion E3 Proposal for A Factor Allocation Approach

  28. Existing Method:Allocation of Capacity Value • Because capacity value reflects the cost of maintaining resource adequacy to meet peak loads, the avoided costs allocate capacity value over the top 250 load hours of the year • This allocation methodology serves as a proxy for relative loss of load expectation (rLOLE) From Workshop held on Tuesday, November 2, 2010

  29. Comparison of Proxy to Actual LOLE • Utilities presented LOLE model results (red line) that show higher relative emphasis on the top net load hours than the current ‘250 hour methodology’ (blue line) • R-Power (green line) is a curve fit to the LOLE results Figure from PG&E Testimony, October 1, 2012

  30. Post-workshop comments on demand-side cost-effectiveness • Utility comments on capacity allocation • Loss of Load Expectation modeling is the most appropriate method for capacity allocation. • The current ‘250 hour’ methodology undervalues programs targeted toward the highest net load hours. • The current methodology is also ill-equipped to deal with the shift in critical hours as renewable penetrations increase. • Utility proposals for allocation methodology • Short term: adopt an exponential distribution that better approximates relative LOLE • Long term: use LOLE modeling to directly determine capacity allocation

  31. Potential Issues with the Current Short-term Solutions • LOLE models do show that on any given year we will likely only have one or two critical days with capacity shortage, but we cannot predict when exactly during the year the highest need hours will occur. • Allocating full capacity value to programs with limited availability can result in overvaluation. • For example: If a program could be called for many hours, but only on certain days of the week, hours of the day, or months of the year, its attributed value should accurately reflect this.

  32. Proposed Addition to the Proposed Methodology • Two step solution for DR Programs. Separate capacity valuation factor into two components. • Availability. The ability to be called in any hour. This should reflect the hours when a capacity shortage could occur. • Programs that are always available get 100% • Programs that are not always available get less than 100% • Dispatchability. The number of times, duration, and frequency that may occur based on the program design. • Programs that can operate in all of the required hours in a typical year will get 100% • Programs that are limited to short duration calls, or infrequent calls get less than 100% • New A Factor = Availability Factor * Dispatchability Factor

  33. LOLE Heat Map for Availability 20,000 MW Solar & Wind Combined No Renewables Month Month Weekday Weekday Hour Hour Month Month Weekend Weekend Hour Hour

  34. Availability Based on Month, Hour, and Day type • Weekdays contain 93% of relative value

  35. Availability Hours Duration Curve

  36. Example: Dispatchability Heat Map • Example for dispatchability based on demand response call frequency and duration • Forecasts and ability to hit priority days will spread the value over a larger number of days Duration of each DR call (hr) # of days/year Critical Peak Pricing (CPP) Capacity Bidding Program (CBP)

  37. Potential short term solution • Use the availability heatmap to accurately capture when programs should be available • This is the missing dimension in the current proposal • Use a distribution that better fits LOLP modeling results to build the dispatchability heat map. • Methodology would require returning the ‘exponential distribution weighting factors’ to chronological order and then analyzing program value as a function of the call frequency and duration. • In the longer term, a direct LOLP modeling approach can be developed New A Factor = Availability Factor * Dispatchability Factor

  38. Transparency • Availability heat map results are from an LOLP model developed by E3 for the CAISO • Modeling methodology has been publically vetted • Algorithms are well established in academic literature • All source data used for the examples can be made public • Working to release the model publically or we could update it and focus on DR-specific issues for future use • Dispatchability heat map algorithms can be made publically available, or we can use the utility proposed exponential fit of LOLP information

  39. B Factor – notification time • Day Ahead – currently 88% • Day Of – currently 100% for all day-of programs including: • 3 hour notice • 2 hour notice • 1 hour notice • 30 minute notice • 15 minute notice • 10 minute notice Very Valuable! How can we better estimate these?

  40. B Factor – notification time The B factor calculation should be done by examination of past DR events to determine how often the additional information available for shorter notification times would have resulted in different decisions about events calls...By examining past events, an estimate can be made of how often a curtailment event would have been accurately predicted, not predicted but needed, or predicted but not needed in advance of the notification time required by a particular program. ..It may not be possible to apply this method to anything other than the distinction between day-of and day-ahead programs...It may also be possible to determine the B factor by examining the relationship between real-time and day-ahead energy prices in current CAISO markets. -- DR cost-effectiveness protocols

  41. C Factor – trigger C factors used in 2012-14 application: • PG&E AC cycling and BIP – 95% • Everything else – 100% Do all DR programs really have flexible triggers?

  42. C Factor – trigger • The C factor may be determined in a manner similar to the B factor…by examination of past DR events to determine how often a different trigger would have resulted in different decisions about event calls. Note that this includes both when a more flexible trigger might have resulted in an event call that was not actually made, and when an event call was made because a particular trigger condition was reached (such as high temperature) even though the program was not actually needed.   • The C factor may be determined by creating a ratio of number of events called to maximum numbers of events permitted for each program. This can be done for the lifetime of the program, for a particular year, or for a particular representative time period. • -- DR cost-effectiveness protocols

  43. C Factor – trigger

  44. C Factor - Trigger

  45. D Factor – T&D • Right time • Right place • Right certainty • Right availability Can we more clearly define these terms?

  46. Topic 4: Dual Participation Load Impacts Effect on Cost-Effectiveness BIP DBP 500 MW 50 MW 40 MW BIP and DBP (dually-enrolled) customers 460 MW BIP-only customers 10 MW DBP-only customers A B C Current Cost-effectiveness Analysis: BIP: A and B customers; DBP: C customers only (following Resource Adequacy rules)

  47. Topic 4: Dual Participation Load Impacts Effect on Cost-Effectiveness Discussion Questions For Resource Adequacy purposes, the load impacts of customers who participate in more than one Demand Response program are counted only in one of the programs. Should we continue to account for load impacts this way when we measure program cost-effectiveness? What are other alternatives for analyzing cost-effectiveness of programs which included dually-participating customers? For example, should we look at the combined cost-effectiveness of two programs if there are customers participating in both programs?

  48. BIP DBP 500 MW 50 MW 40 MW BIP and DBP (dually-enrolled) customers 460 MW BIP-only customers 10 MW DBP-only customers A B C • Current analysis: • BIP: A and B customers • DBP: C customers only • (following Resource Adequacy rules) • Alternatives for additional analyses: • BIP + DBP (A + B + C) • Total DBP (B + C) • Separate (A, B, and C) • Some or all of the above

  49. Topic 5: Participant Costs Participant Costs (net of equipment costs) are defined in the DR cost-effectiveness protocols as the sum of value of service loss and transaction costs. Because we do not know how to measure value of service loss or transaction costs, we use 75% of the incentives paid to customers as a proxy value. • Should we continue to use a percentage of the incentives paid to customers as a proxy measurement for participant costs, or should we try to measure value of service loss and transaction costs? • If we continue to use a percentage of the incentives paid to customers as a proxy measurement for participant costs, is 75% a reasonable estimate?

  50. Topic 6: Analysis of Optional Benefits • Optional benefits identified in the 2010 Demand Response Cost-effectiveness Protocols include: • Environmental benefits (other than the avoided environmental costs for GHG), • Market and reliability benefits, and • Non-energy benefits. • Each benefit may be quantified by utilities. Any quantification should be supported by an explanation of the derivation. • If a value cannot be estimated, utilities shall provide a qualitative analysis, or an explanation of why it is not possible to describe the possible magnitude and impact.

More Related