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Pacific Gas and Electric Company Long Term Procurement Plan Proceeding Renewable Integration Model Results and Model Demonstration October 22, 2010 Workshop. Outline. Part 1 – Review of RIM Methodology and Inputs Part 2 – Results With PG&E’s October 22, 2010 Assumptions

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  1. Pacific Gas and Electric CompanyLong Term Procurement Plan ProceedingRenewable Integration ModelResults and Model DemonstrationOctober 22, 2010 Workshop

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

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

  5. RIM is a statistical model that accounts for variability and unpredictability Day-ahead forecast Minute-by-minute actual 5-minute forecast Hour-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. Steps in Estimating Resource Requirements Operating Flexibility Requirement Reliability Requirement Operating Flexibility Hourly Requirement Renewable Hourly Generation Renewable Reliability Contribution (NQC) Planning Reserve Margin Forecast Peak Load MW Projected Hourly Load Residual Operating Flexibility Requirement Additional Capacity Required for integration Residual Reliability 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. 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. RIM’s results vary depending on inputs • RIM is a flexible tool • RIM’s results vary depending on inputs and assumptions used • Range of results is illustrated by: • PG&E’s October 22, 2010 Assumptions • Other Parties’ assumptions and sensitivities

  9. Model improvements and inputs changes implemented since Aug 25 workshop Day-ahead forecast Minute-by-minute actual 5-minute forecast Hour-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 DOE’s “Solar Vision Study” Draft May 28, 2010.

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

  11. Renewable resource scenarios The RPS scenarios will be updated to reflect the LTPP Scoping Memo The current scenarios are: • 20% Reference Case in 2020 • 27.5% Reference Case in 2020 • 33% ReferenceCase in 2020 Intermittent Renewable Generation Scenarios MW Scenarios All scenarios include additional self-gen PV treated as PV supply to capture the integration requirement

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

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

  14. 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* 6,000 5,000 4,000 3,000 Reliability Requirement 2,000 1,000 Additional capacity needed to meet load and flexibility need - (1,000) (2,000) NQC surplus (3,000) (4,000) 20% 23.5% 27.5% 33%

  15. 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. 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. Outline • Part 1 - Review of RIM Methodology and Inputs • Part 2 - Results With PG&E’s October 22, 2010 Assumptions • Part 3 - Results With Other Parties’ Assumptions • Part 4 - Closing Thoughts

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

  19. 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 Scenario’s Resource Requirement for Integration (MW) in 2020

  20. What’s 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) Maximum operating flexibility requirements (MW) (Step 1 Results) Capacity need for integration (MW) (Step 2 Results) Day-ahead commitment Load following Regulation * Calculated by RIM using 2 standard deviations (for 95% coverage), and 1.65 standard deviations (90% coverage), assuming normal distribution of forecast deviations.

  21. What’s the combined effect of sensitivities TURN explored? RIM’s flexibility allows the user to test sensitivity of results Resource Need for Integration (MW) 33% RPS Scenario in 2020 (Step 2 Results) Operating Flexibility Requirements (Step 1 Results) (Summer Season, 33% RPS in 2020)

  22. 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

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

  24. 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. 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. Appendix

  27. Forecast errors and variability

  28. Regulation-up requirements comparison

  29. Load Following-up requirements comparison

  30. Integration need in 27.5% vs. 33% RPS scenarios Net effect is 200 MW reduction in integration need in 27.5% RPS Scenario compared to 33% 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) August 16, 2020 Peak day for operating need - 27.5% RPS Scenario August 16, 2020 Peak day for operating need - 33% RPS Scenario 4,600 MW Integration need 4,800 MW Integration need MW MW Operating flexibility requirement Operating flexibility requirement * NQC Surplus is also referred to as Residual Reliability Requirement

  31. NQC of Resources by Scenario, NQC MW 16,000 14,000 12,000 10,000 Total Wind/solar 8,000 CT 6,000 CC 4,000 2,000 0 All gas 20% 27.50% 33% Resource additions by scenario Wind/solar additions reduce conventional gas-fired resources, primarily combined cycles

  32. The normal distribution (public domain image)

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