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Demand Response Cost-effectiveness Protocols

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Presentation on theme: "Demand Response Cost-effectiveness Protocols"— Presentation transcript:

1 Demand Response Cost-effectiveness Protocols
Thursday, January 6, 2011 Eric Cutter, Snuller Price, Nick Schlag: E3

2 Agenda 10:00 - Introductions 10:15 – Avoided Cost Calculator
11:30 – DR Reporting Template 12:30 – Lunch 1:30 – Adjustment Factors 3:00 – Break 3:15 – Utility Proposals 3:45 – Administrative Costs 5:00 - Adjourn January 7, 2011

3 DR Process November DR Workshop Proposed Decision Comments
Overview of Avoided Costs, DR Reporting Template Proposed Decision Comments Reply Comments Final Decision Today’s January Workshop Updates since November DR Workshop based on comments

4 Introduction

5 Two Tools Avoided Cost Model DR Reporting Template
Publicly available data Non-proprietary tool DR Reporting Template Standardized inputs Non-proprietary tool Common metrics for output

6 Avoided Cost Model and Relationships
Benefits Included Energy purchases or generation cost Generation Capacity T&D Capacity GHG Emissions Losses Ancillary Services Procurement Reduction Reduced RPS procurement Renewable Integration Reducing overgen, Ramp CPUC proceedings with similar approach Energy Efficiency DG Cost-effectiveness Permanent Load Shifting CEC proceedings with similar model Title 24 Time-Dependent Valuation for evaluation of building standards Exported to DR Reporting Template Calculated by Avoided Cost Model Really clear that stuff on bottom is not included in DR, add box Under Development

7 Use of Avoided Costs Across Proceedings
Same avoided costs from Avoided Cost Model DG Avoided Cost Framework Each proceeding determines how to apply avoided costs Used for DG (CSI, SGIP) and DR EE still using previous approach ALJ will provide guidance regarding application of avoided costs and DR protocols to PLS

8 Cost-effectiveness Results
DR Reporting Template Increased emphasis on consistency and transparency Single, transparent Excel workbook for calculating and reporting cost-effectiveness results Easy to compare and aggregate results Avoided Cost Program Impacts Cost-effectiveness Results

9 Avoided Cost

10 Avoided Cost Calculator Updates
Key Changes to Avoided Cost Calculator CT dispatch Allocation of generation capacity value Financing assumptions and pro forma calculation CT Dispatch Example

11 Changes to the CT Dispatch Calculations
Several stakeholders were concerned that the capacity factor of the CT was too high Added a 10% minimum bid margin to the CT dispatch algorithm, similar to CAISO methodology CAISO Market Performance Report Adjusted CT operations based on historical temperature profiles Heat rate adjustment Reduced output

12 Integration of Temperature Effects into Capacity Value
Temperature affects the operations—and hence the capacity residual—of a new CT in three ways: Operating Cost: High temperatures result in increases in the heat rate, which in turn increases the cost of generating a unit of energy Operating Performance Penalty: At high temperatures, the output of a CT is reduced, lowering the revenues the unit can earn by selling into the real-time market Peak Performance Penalty: During peak periods, when temperatures are also high, the output of the CT is reduced below nameplate, which increases the CT’s residual value per kW generated during the peak

13 CT Dispatch: Summer Peak Performance Penalty
Output curve based on GE LM6000 with SPRINT technology and dry cooling:

14 CT Dispatch: Heat Rate Adjustment Based on Temperature
Heat rate curve based on GE LM6000 with SPRINT technology and dry cooling

15 Capacity Allocation Several stakeholder suggested that using a single year of historical load data to allocate capacity value was not representative After the December workshop, E3 provided several alternatives including utility LOLP and four years of historical data Final decision allocates capacity value based on four years of historical load data ( )

16 Capacity Allocation Based on Four Historical Years
Percent of Total Capacity Value by Month

17 ComparisonCapacity Allocation
The allocators used to value DR peak impacts are based on the average of the allocators calculated for the period In most months, this serves as a reasonable approximation of PG&E’s LOLP Percent of Total Capacity Value by Month

18 Financial Pro Forma Updates
Correction of CT MACRS term from 20 to 15 years Addition of property tax and insurance costs Property tax: 1.1% of capital costs per year Insurance: 0.6% of capital costs per year Addition of Manufacturing Tax Credit 9% of half of plant W2 wages (4.5%), based on CEC COG Model Adjustment of debt/equity shares to reflect current financing climate – still assuming 3rd party owned CT Increased debt share in capital structure from 50% to 60%

19 Example CT Dispatch To calculate the value of capacity, E3 assumes that a CT will participate in the CAISO real-time market Consistent with CAISO Annual Market Report The parameters that determine the CT’s net revenues include the real-time prices, the cost of fuel, the unit’s heat rate and O&M, and ambient temperature

20 Example CT Dispatch Step 1: Forecast hourly real-time market prices based on heat rates from July 2009 through June 2010

21 Example CT Dispatch Step 2: Calculate operating cost ($/MWh) for a CT in each month as a function of the gas price, heat rate, and variable O&M

22 Example CT Dispatch Step 3: Sort real-time market prices (and corresponding CT operating costs) in descending order (top 1000 hours shown below)

23 Example CT Dispatch Step 4: Calculate the CT’s revenue assuming it operates when the real-time price exceeds its variable cost plus the 10% bid adder

24 Resulting California Net Cost of CT
Calculation of the final residual value includes several further adjustments Energy revenues reduced by 7% for plant outages A/S market participation assumed to increase gross revenues by 11% (based on CAISO market report)

25 Data Sources and References

26 DR Reporting Template

27 DR Reporting Template Avoided Cost Model DR Reporting Template
Publicly available data Non-proprietary tool DR Reporting Template Standardized inputs Non-proprietary tool Common metrics for output

28 Using the DR Template Make sure latest inputs are copied from the Avoided Cost Calculator Create a new tab for your program Note! One tab for each ‘DR program’ Input load impacts for the DR program Input costs for the DR program Review cost-effectiveness results Run sensitivity analysis

29 DR Reporting Template Avoided Cost Inputs Program Impacts
Program Costs Results Optional Benefits T&D Costs Adjustment Factors What constitutes a program Adding New Program Divide into Avoided cost calc, IOU input, Template calculation or how to use Add steps for How to If factors are different, different tab

30 DR Reporting Template Inputs from Avoided Cost Calculator

31 DR Reporting Template Inputs that are IOU Specific

32 Program Impacts Adjusted Wtd. Avg.

33 Program (Ratepayer) Costs
Administrative Costs Incentive Costs Equipment Costs (Amortized) Net Bill/Revenue Reductions Total Ratepayer Costs

34 Program (Ratepayer) Costs
4. By Category 1. Program Costs 2. Equipment Costs 3. Amortization 4. Total

35 Participant Costs X 75% Incentive Costs Net Bill/Revenue Reductions
Equipment Costs (Amortized) Total Ratepayer Costs X 75%

36 Participant Costs + - 1. Program Costs 4. Estimate Costs
X 75% 4. Estimate Costs - 2. Equipment Costs 3. Amortization 5. Total

37 Cost Tests TRC PAC

38 Cost Tests RIM PAC

39 Avoided Cost Benefits Capacity Energy T&D GHG

40 Optional and CAISO Market Benefits

41 Adjustment Factors & T&D Values

42 Base Case Results

43 Sensitivities Blue cells at ED discretion Sensitivity values (blue cells) set at discretion of CPUC Energy Division

44 Add New Program Definition of Program Add Program
Any program or sub-program with distinct features Availability, Notification Time, Trigger etc. Distinct A-E factors Add Program

45 Portfolio Results Total DR portfolio cost and results entered in separate tab Account for dual participation DR Reporting Template cannot simply sum across programs automatically Ensure that portfolio impact, costs and benefits are accurate and representative Calculation will need to be performed by utility outside of DR Reporting Template Back into representative average A-E factors to that portfolio impacts X avoided costs = portfolio benefits

46 Questions and Excel Demo Example

47 Factor Analysis

48 Factor Analysis Framework
Make appropriate adjustments for differences between DR resource and resources used to determine Avoided Costs Combustion Turbine, T&D infrastructure etc. Allow some flexibility for utility specific values and approaches Reduce analysis to single percentage factor for easy comparison across programs and utilities Must be supported by analysis and explanation

49 Adjustment Factors A Factor – Availability
Maximum number, duration and timing of DR calls B Factor – Notification Time Length of program notification time C Factor – Trigger Flexibility in when DR calls may be made D Factor – T&D Capacity value Marginal vs. Avoided T&D costs Right Time: Coincidence of DR calls with local T&D system peaks Right Place: Ability to target DR calls based on local conditions Right Certainty: Reliable enough for T&D deferral E Factor – Energy Value Energy value when DR is call as compared to average On-Peak energy prices

50 Adjustment Factor Examples
E3 Produced example approaches for analysis supporting each factor Suggested approaches only: utility may suggest/develop alternative approaches Must support analysis with public data Can use proprietary data (e.g. LOLP), but also perform analysis with public data

51 A Factor (Availability)
Percentage of Generation Capacity Value captured by maximum number of DR call hours permitted Constraints Maximum Number of Calls per Year Maximum Number of Calls per Month Maximum Number of Hours per Call Public Data 4 years of CAISO load data Percentage of peak CAISO load hours captured by DR Program

52 A Factor (Availability)
Reverse Legend

53 B Factor (Notification Time)
Percentage of Generation Capacity Value captured with minimum notification time Constraints Minimum advanced notification time Public Data CAISO Load Forecasts (Day Ahead and Two Day Ahead) CAISO Actual Loads Percentage of actual peak CAISO load hours predicted by forecasts Compare to 10 minutes for CT Don’t expect greater granularity than Day Ahead/Day Of Perhaps show CAISO RPS report and forecast error

54 B Factor (Notification Time)

55 C Factor (Trigger) Percentage of Generation Capacity Value captured by DR Program Trigger Constraints Conditions under which DR Call may be made Public Data CAISO Day Ahead System Load Forecast Temperature Data Market Heat Rate Percentage of actual peak CAISO load hours captured by Trigger

56 C Factor (Trigger) Examples
Example Triggers CAISO System load above 43,000 MW Marginal heat rate above 15,000 BTU/kWh CAISO Stage 1 emergency imminent “Extreme or unusual” temperature conditions C Factor Comparisons Historical comparison of trigger events to peak loads Real-time peak loads not captured by trigger Triggered calls when not needed in real-time Ratio of actual historical calls to allowable calls

57 C Factor (Trigger) Trigger: CAISO System Load above 43,000 MW

58 D Factor (T&D Capacity Value)
Percentage of T&D Capacity Value captured by DR Program Constraints DR Calls made based on CAISO system conditions Public Data CAISO Day Ahead System Load Forecast Temperature Data Percentage of Climate Zone peak load hours captured by Trigger based on system conditions

59 D Factor Adjustment (T&D)
Two Adjustment Factors Marginal vs. Avoided T&D costs Reduced marginal cost for costs that are unavoidable in a shorter to medium time-frame Admin and General Expenses, O&M labor ‘Right time’ and ‘right place’ adjustment Alignment of DR calls to local distribution and regional transmission constraints

60 Marginal vs. Avoided T&D Cost
Marginal Cost Transmission Distribution Total PG&E $ $ $ SCE $ $ $ SDG&E $ $ $ Avoided Cost $ $ $ $ $ $ $ $ $ Adjustment Factors 64% 71% 69% 76% 57% 66% 63% 68%

61 D Factor (T&D Capacity Value)
Coincidence of system capacity needs and expected distribution peak loads for each climate zone.

62 E Factor (Energy) Percentage adjustment to average Summer On-Peak Energy Price Constraints Expected hour of DR calls may have energy prices that are higher or lower than average On-Peak prices. Public Data Hourly Avoided Costs CAISO Hourly Market Prices Calculate Ratio of expected average energy prices during DR calls to average On-Peak energy prices.

63 E Factor (Energy) Example
Example Adjustments for Energy Price 2-4 hour calls for AC program expected during hours with average price much higher than ~ $80/MWh DR program targeted to locally constrained area with congestion DR Program with more flexible calls (24/7/365) would have average price closer to $55/MWh

64 Utility Proposals

65 Administration Costs

66 Allocation of Administration Costs
All costs that support individual programs should be included in individual program costs General Overhead, Administration and Marketing budgets must be allocated by some method that is justified by the utility Suggested Allocators: Actual program workload # of customers MWs Incentive Costs Avoided Cost Benefits

67 Add example


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