1. NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy operated by the Alliance for Sustainable Energy, LLC Debra Lew Greg Brinkman Bri-Mathias Hodge National Renewable Energy Laboratory Golden, Colorado USA Western Wind and Solar Integration Study: Scenarios and Data Inputs

2. NATIONAL RENEWABLE ENERGY LABORATORY Scenario reminder Penetration by Energy High WindIntermediateHigh Solar 11%WECC TEPPC 2020 8% wind 3% solar 22% 33%25% wind 8% solar 16.5% wind 16.5% solar 8% wind 25% solar 2 Use NREL ReEDS model to expand generation fleet subject to geographical and electric power system constraints (and select regional distribution) Solar consists of 40% CSP and 60% PV CSP has 6 hours of storage

3. NATIONAL RENEWABLE ENERGY LABORATORY High wind (25% wind, 4.8% PV, 3.2% CSP)

4. NATIONAL RENEWABLE ENERGY LABORATORY Intermediate (16.5% wind, 9.9% PV, 6.6% CSP)

5. NATIONAL RENEWABLE ENERGY LABORATORY High solar (8% wind, 15% PV, 10% CSP)

6. NATIONAL RENEWABLE ENERGY LABORATORY Renewable generation profiles Solar Remake all solar generation data, down to 1-min resolution PV is 60% of solar, CSP is 40% Distribution to regions based on the ReEDS results Distribution within regions based on the following rules: Rooftop PV is 40% of PV where possible Capacity distributed by population (same capacity per person) Maximum capacity per grid cell of 1 kW/person All scenarios use same sites with different capacity per grid cell Distributed utility PV is ~20% of PV Sited near population areas Scenarios use subset of sites “Remote-site” utility PV is 40% of PV Sited based on capacity factor Scenarios use subset of sites 6

7. NATIONAL RENEWABLE ENERGY LABORATORY Renewable generation profiles Wind Sited by capacity factor within ReEDS region Close capacity factor sites were sometimes substituted so not all wind was in same location Use WWSIS phase 1 data set Statistically downsampled data available for subhourly analysis Load 2006 1-min data available from WECC VGS 2004 or 2005? 7

8. NATIONAL RENEWABLE ENERGY LABORATORY Sample map of solar sites 8

9. NATIONAL RENEWABLE ENERGY LABORATORY Choosing buses to inject renewables Bus location data from Energy Visuals, Inc. Remote-site resources Sited to nearest bus >=230 kV No limit on renewable injection (MW) per bus Transmission buildout should solve overloaded line problems Rooftop PV, distributed UPV Distribute by load distribution factors for each load zone 9

10. NATIONAL RENEWABLE ENERGY LABORATORY Bri-Mathias Hodge Wind forecasting error distributions 10

11. NATIONAL RENEWABLE ENERGY LABORATORY Wind Forecasting Error Distributions Using forecast errors taken from operational systems Aggregated at the ISO level Map errors from WWSIS 1 through a model error distribution and tweak to generate more realistic error distributions 11

12. NATIONAL RENEWABLE ENERGY LABORATORY CAISO Day-Ahead Distribution κ = 1.5025 γ= -0.393 Total Capacity: ~950 MW 12

13. NATIONAL RENEWABLE ENERGY LABORATORY ERCOT Day-Ahead Distribution κ = 1.0299 γ= -0.0616 Total Capacity: ~9000 MW 13

14. NATIONAL RENEWABLE ENERGY LABORATORY Xcel Wind Plant κ = 1.05 γ= -0.65 Total Capacity: ~300 MW 14

15. NATIONAL RENEWABLE ENERGY LABORATORY Mapping Forecast Errors WWSIS Forecast Errors Model Production Forecast Errors 95% Normalized Forecast Error -1 0 1 15

16. NATIONAL RENEWABLE ENERGY LABORATORY 3-day seam fix 3TIER Western Wind Resources Dataset Increased variability at 3-day seams – was not found to be a problem with hourly MAPS simulations in WWSIS1. Every 3 rd day was removed from statistical analysis in WWSIS1 Jack King has re-analyzed the dataset and is using a 2 nd order Butterworth filter to create expected standard deviations of wind output. This will be used for WWSIS2, pending verification of statistical properties. 16

17. NATIONAL RENEWABLE ENERGY LABORATORY Retirement Scenarios All scenarios (including base case TEPPC 2020) Probably use WECC TEPPC DWG projections May need to add capacity if additional units are retired from TEPPC 2020 case Gas CC added in locations where capacity is retired Sensitivity analysis on additional retirements for renewable scenarios Amount retired will be based on capacity value of renewables 17

18. NATIONAL RENEWABLE ENERGY LABORATORY Startup/cycling costs Sensitivities Default generic values from WECC assumptions Minimum by category from APTECH results Maximum by category from APTECH results (input data will not be made public) Potentially one more scenario with a distribution of cycling costs from the APTECH estimates for each category, based on random assignment or independent variable (e.g., age) It is not important to get the correct cycling cost at the each unit – only that the general distribution is correct Units that are projected to be cycled may be different from units that are actually cycled for various reasons Apply different cost for hot, warm, cold starts, and ramping penalties if necessary 18

19. NATIONAL RENEWABLE ENERGY LABORATORY Smaller working groups We will have smaller working groups on the following topics: Solar generation and forecast data creation Wind forecast error correction APTECH startup costs How to apply distributions of generic data to specific units NDAs required to see any information on distributions, but not to see minimum costs by category Please let us know if you would like to be involved 19

20. NATIONAL RENEWABLE ENERGY LABORATORY Questions? Greg Brinkman 303-384-7390 gregory.brinkman@nrel.gov Debbie Lew 303-384-7037 debra.lew@nrel.gov Bri-Mathias Hodge 303-384-6981 bri.mathias.hodge@nrel.gov 20

21. NATIONAL RENEWABLE ENERGY LABORATORY Transmission zones Run zonally initially. Nodal runs at a later date for deeper dives. Propose to use these 20 TEPPC zones. Aiming at more rather than less zones to better approximate actual current operations. Commit and dispatch within each zone with no hurdle rates between zones to allow for interzone transfers. 21

22. NATIONAL RENEWABLE ENERGY LABORATORY Capacity (GW) by state for 3 scenarios 22 HighWindIntermediateHighSolar WindPVCSPWindPVCSPWindPVCSP AZ4.34.84.01.49.5 0.214.59.7 CA11.111.63.05.916.13.85.419.49.2 CO5.52.50.23.92.60.23.05.11.3 ID1.10.0 1.00.0 0.50.0 MT5.90.10.04.00.10.01.00.10.0 NM4.20.40.12.82.10.30.53.20.6 NV2.80.90.61.44.10.60.26.60.6 OR0.0 SD2.30.0 1.90.0 0.30.0 TX0.00.20.0 0.40.0 0.50.0 UT1.10.90.00.62.20.00.34.90.0 WA0.0 WY9.00.0 6.80.0 1.50.0 Total47.321.37.829.637.114.413.054.221.3