1. Pacific Gas and Electric Company Long Term Procurement Plan Proceeding Renewable Integration Model Results and Model Demonstration October 22, 2010 Workshop

2. 1 Outline Part 1 – Review of RIM Methodology and Inputs Part 2 – Results With PG&Es October 22, 2010 Assumptions Part 3 - Results With Assumptions from Different Parties Part 4 - Closing Thoughts

3. 2 RIM objectives Understand and quantify the integration requirements and cost of higher levels of intermittent resources Study integration impacts under different scenarios quickly Transparent, user friendly model

4. 3 RIM uses a variety of inputs to determine renewable integration requirements and costs Inputs Model Outputs Renewable Integration Model (RIM) Detailed profiles and variability for load & generation Forecast errors for load & generation Operating Flexibility Requirements (Reg, Load Following, Day-Ahead, Ramp) Resources required to integrate Intermittent renewables Fixed and variable cost of integration Cost of conventional resources Installed intermittent renewable generation To the extent possible, RIM uses the same inputs as CAISOs study

5. 4 Intra 5-min variability 5-min forecast error Intra-hour variability Hour-ahead forecast error Day-ahead forecast error RegulationLoad-followingDA Commitment RIM is a statistical model that accounts for variability and unpredictability Minute-by-minute actual5-minute forecastHour-ahead forecast Day-ahead forecast Regulation –RIM uses parameters that describe deviations from relevant scheduling –Two primary parameters: intra 5-min volatility and average 5-minute forecast error Load following –RIM uses parameter that describe deviations between the 5-minute and the hour-ahead schedules –Two primary parameters: intra-hour variability and average hour-ahead forecast error Day-ahead commitment –Deviation between day-ahead and hour-ahead schedule The model uses all 5 statistical parameters shown in diagram

6. 5 Steps in Estimating Resource Requirements Reliability Requirement Operating Flexibility Requirement Forecast Peak Load Renewable Reliability Contribution (NQC) Planning Reserve Margin Renewable Hourly Generation Operating Flexibility Hourly Requirement Projected Hourly Load Residual Reliability Requirement MW Additional Capacity Required for integration Residual Operating Flexibility Requirement Forecast Peak Load + Planning Reserve Margin – Reliability Contribution of Renewables (NQC) Reliability Requirement Hourly Load + Hourly Operating Flexibility Services – Hourly renewable generation Operating Flexibility Requirement

7. 6 Integration costs Fixed Costs Fixed cost of resources in excess of reliability requirement Variable Costs Fuel and operating costs of resources providing flexibility services Emission Costs Emission costs based on the incremental fuel use by resources providing integration services

8. 7 RIMs results vary depending on inputs RIM is a flexible tool RIMs results vary depending on inputs and assumptions used Range of results is illustrated by: –PG&Es October 22, 2010 Assumptions –Other Parties assumptions and sensitivities

9. 8 Model improvements and inputs changes implemented since Aug 25 workshop Intra 5-min variability 5-min forecast error Intra-hour variability Hour-ahead forecast error Day-ahead forecast error RegulationLoad-followingDA Commitment Minute-by-minute actual5-minute forecastHour-ahead forecast Day-ahead forecast Modified forecast errors –Day-ahead forecast errors for load, wind, and solar from other studies * –Hour-ahead forecast errors for load and wind from CAISO improved error data set –5 minute load forecast errors from CAISO improved forecast error –5 minute wind forecast error corrected Decreased service level standard deviations Added capability for user to exclude day-ahead commitment if desired * Sources: SPP WITF Wind Integration Study by Charles River Associates, and DOEs Solar Vision Study Draft May 28, 2010.

10. 9 Outline Part 1 – Review of RIM Methodology and Inputs Part 2 - Results With PG&Es October 22, 2010 Assumptions Part 3 - Results With Other Parties Assumptions Part 4 - Closing Thoughts

11. 10 Renewable resource scenarios The RPS scenarios will be updated to reflect the LTPP Scoping Memo The current scenarios are: 1.20% Reference Case in 2020 2.27.5% Reference Case in 2020 3.33% Reference Case in 2020 All scenarios include additional self-gen PV treated as PV supply to capture the integration requirement Intermittent Renewable Generation Scenarios Scenarios MW

12. 11 Input changes decrease operating flexibility requirements MW October 22, 2010 Operating Flexibility Requirements (Summer Season, 2020) August 25, 2010 Operating Flexibility Requirements (Summer Season, 2020) MW Operating flexibility requirements decrease by about 1,000 MW (Step 1 results)

13. 12 Additional flexible resources are needed for integration above PRM MW 20% RPS Scenario need about 1,000 MW 27.5% RPS and 33% RPS need about 4,600 MW and 4,800 MW, respectively * The All Gas Scenario does not need additional flexible resources above PRM requirement. Resource Requirements for Integration (MW) by Scenario in 2020*

14. 13 The contribution of wind/solar to reliability affects renewable integration need Wind/solar reliability value (NQC) is so large that the system has: Surplus reliability resources (i.e., it has NQC surplus), but Unmet operating needs to cover net load and increased flexibility Resource Requirements for (MW) by Scenario in 2020* (4,000) (3,000) (2,000) (1,000) - 1,000 2,000 3,000 4,000 5,000 6,000 20%23.5%27.5%33% Reliability Requirement Additional capacity needed to meet load and flexibility need NQC surplus

15. 14 Shift in critical hour drives results Renewable additions shift critical hour to hours when there is low renewable production Net Load in 27.5% and 33% RPS Scenarios in 2020 (Aug 16, 2020)

16. 15 The bulk of the integration cost is fixed costs On a $/MWh basis, 27.5% RPS has higher integration costs than 33% RPS because fixed costs are divided by smaller amount of wind/solar generation Integration Costs by Scenario, $/MWh in 2020 $/MWh *

17. 16 Outline Part 1 - Review of RIM Methodology and Inputs Part 2 - Results With PG&Es October 22, 2010 Assumptions Part 3 - Results With Other Parties Assumptions Part 4 - Closing Thoughts

18. 17 Parties questions and sensitivities Is there a need for day-ahead commitment requirement? Whats the sensitivity of results with 90% vs. 95% coverage of forecast errors? Whats the combined effect of sensitivities TURN explored? What if the system can integrate 20% RPS with 15%- 17% PRM in 2020?

19. 18 Is there a need for day-ahead commitment requirement? Day-ahead or multi-hour commitment is needed because more than 50% of the existing fleet requires 5 hours or more to start If day-ahead commitment is not considered, resource need decreases by less than 1,000 MW in 33% RPS Reference Scenario 33% RPS Scenarios Resource Requirement for Integration (MW) in 2020

20. 19 Whats the sensitivity of results with 90% vs. 95% coverage of forecast errors? Assuming forecast errors are normally distributed*, Maximum operating flexibility requirements decrease ~ 1,500 MW from 95% to 90% (Step 1 results) Capacity need for integration decreases by less than 500 MW from 95% to 90% (Step 2 results) * Calculated by RIM using 2 standard deviations (for 95% coverage), and 1.65 standard deviations (90% coverage), assuming normal distribution of forecast deviations. Regulation Load following Day-ahead commitment Maximum operating flexibility requirements (MW) (Step 1 Results) Capacity need for integration (MW) (Step 2 Results)

21. 20 Whats the combined effect of sensitivities TURN explored? RIMs flexibility allows the user to test sensitivity of results Operating Flexibility Requirements (Step 1 Results) (Summer Season, 33% RPS in 2020) Resource Need for Integration (MW) 33% RPS Scenario in 2020 (Step 2 Results) Oct. 22 AssumptionsTURN Suggestions Forecast error coverage2.0 Std Deviation1.65 Std Deviation Day AheadYesNo Load DA & HA Correlation0.51 Resource need for integration (Step 2 results) 4,800 MW3,800 MW

22. 21 What if the system can integrate 20% RPS with 15%-17% PRM in 2020? Assuming the system with 15%-17% PRM can integrate 20% RPS in 2020, resource need for 33% RPS is reduced by ~1,000 MW 4,800 MWRIM estimate for 33% RPS in 2020 - 1,100 MWRIM estimate for 20% RPS in 2020 3,700 MWRIM estimate for 33% RPS in 2020, assuming system can integrate 20% RPS with 15%-17% PRM in 2020

23. 22 Outline Part 1 - Review of RIM Methodology and Inputs Part 2 - Results With PG&Es October 22, 2010 Assumptions Part 3 - Results With Other Parties Assumptions Part 4 - Closing Thoughts

24. 23 Insights from analysis Critical need hours shift from afternoon to evening Increased forecast uncertainty and variability also contribute to integration need/cost There is a substantial amount of intermittent renewable NQC that does not reduce resource need

25. 24 Next steps Update RPS scenarios based on scoping memo Continue work with CAISO and other parties to improve model inputs and model functionality –Calibrate balance year assumption or find simplified ways to represent existing system integration capability –Calibrate variable integration cost inputs Welcome suggestions for improvements to the model

26. 25 Appendix

27. 26 Forecast errors and variability

28. 27 Regulation-up requirements comparison

29. 28 Load Following-up requirements comparison

30. 29 Integration need in 27.5% vs. 33% RPS scenarios MW August 16, 2020 Peak day for operating need - 27.5% RPS Scenario Relative to 33% RPS Scenario, 27.5% RPS Scenario has: - Lower operating flexibility requirement, but - Higher net load (due to lower RPS generation) MW August 16, 2020 Peak day for operating need - 33% RPS Scenario * NQC Surplus is also referred to as Residual Reliability Requirement Operating flexibility requirement Operating flexibility requirement Net effect is 200 MW reduction in integration need in 27.5% RPS Scenario compared to 33% RPS Scenario 4,600 MW Integration need 4,800 MW Integration need

31. 30 Resource additions by scenario Wind/solar additions reduce conventional gas- fired resources, primarily combined cycles NQC of Resources by Scenario, NQC MW 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 All gas20%27.50%33% Total Wind/solar CT CC

32. 31 The normal distribution (public domain image)