1. Wind Power Capacity Assessment Mary Johannis, BPA, representing Northwest Resource Adequacy Forum Northwest Wind Integration Forum Technical Working Group October 29,2009

2. NW Wind Integration Forum2 March 2007 NW Wind Integration Action Plan ACTION 1: By July 2007, the Northwest Resource Adequacy Forum (NWRA Forum) should reassess its 15 percent pilot sustained wind capacity value using currently available data on wind plant operation during periods of peak load. In 2008, the NWRA Forum should further refine the sustained peaking capacity value of wind power using the improved wind resource data set of Action 3 and other available data.

3. October 29, 2009NW Wind Integration Forum3 Phase I: Reassess15% Wind Capacity Value July 25, 2007 Forum Technical Committee Meeting –Wind Capacity Subgroup  calculate wind capacity value based on contribution to meeting load during sustained peak period of cold snap/heat wave events –Contract with BorisMetrics to translate wind speed data into simulated data, to perform quality control of existing wind generation data and to evaluate the wind capacity value January 17 & February 28, 2008 Tech Meetings –BorisMetrics developed a 4 th degree polynomial constrained econometric model to backcast hourly project output as a dependent variable of Pendleton wind speeds (E. & W. Gorge areas) –Concern that statistical attributes of backcast generation do not match actual wind generation attributes, i.e. many more instances of zero generation in actual records than in backcast simulation

4. October 29, 2009NW Wind Integration Forum4 Phase I: Placeholder Wind Capacity Value of 5% Selected Historical record is insufficient to calculate statistically significant wind capacity factor over 18 hour sustained peak period during cold snaps Median capacity factor over 6 peak hours during cold snaps is 7.3% Adverse wind capacity factor ≈ 5% BPA Analysis: 1/ 1/ 7/8/08 Forum Tech Committee Meeting

5. October 29, 2009NW Wind Integration Forum5 PHASE II: Long-term Plan to develop Wind Capacity Value Need sufficient years of hourly wind generation by wind site for GENESYS to perform Monte Carlo picks Options: –Backcast Wind Generation using historical Anemometer records –Develop Temperature-Correlated Synthetic Wind Generation Records

6. October 29, 2009NW Wind Integration Forum6 BorisMetrics Contract Identified Issues Can wind speed be used to backcast wind generation? –Example: East Gorge Generation Dec 2006 –Why is there so little generation when the wind is blowing? –This example points outs problem with using off-site anemometer to backcast wind generation

7. October 29, 2009NW Wind Integration Forum7 BorisMetrics Contract Identified Issues Can a unique function calculating generation based on wind speed be determined?

8. October 29, 2009NW Wind Integration Forum8 BorisMetrics Contract Identified Issues Pendleton Anemometer Data not Clean

9. October 29, 2009NW Wind Integration Forum9 Vansycle Backcast Case Study Vansycle has an anemometer on-site –½ mile from the nearest generator –6 miles from the furthest generator Wind speed data is available in 10 minute intervals for period Scada data is available in 5 minute intervals for period Vansycle Backcast should be doable –Relatively long-term Generation Record –Relatively clean Anemometer Record Wind Turbine Power Characteristics: –Cut-in wind speed 4 m/s (8.9 mph) –Nominal wind speed 15 m/s (33.6 mph) –Stop wind speed 25 m/s (55.9 mph)

10. October 29, 2009NW Wind Integration Forum10 Vansycle Study  Backcasting not feasible Lessons learned: –High R 2 of multivariate regression (without zeros) and residual analysis indicates that Persistence is an important feature in regression –Other regressions have artificially high R 2 by including zeros –Prediction interval of.3 is not sufficiently tight to backcast Backcasting Wind Generation for NW is NOT feasible –Even on-site wind anemometers can be miles from some wind turbines resulting in the LACK of a unique correlation –Due to the persistence feature of the regression cannot use other means to reflect randomness in the correlation –Insufficient on-site anemometer data to backcast the entire NW wind generation fleet Conclusion: Develop Temperature-Correlated Synthetic Wind Generation Records

11. October 29, 2009NW Wind Integration Forum11 Synthetic Wind Generation using K th Nearest Neighbor Method What is Kth Nearest Neighbor Method? –For a time series of size N, randomly select a single or two consecutive of the N observations then select the third based on how “close” the lag(s) for the selected observation are to the randomly selected observation(s) For example, select two hours where the capacity is 0.3 & 0.4, respectively, then pull from observations that have capacities that are close to.3 for the observation 2 hours prior and.4 for the hour prior. Creating a subset of the K “closest” observations to draw from maintains the structure that is expected in the time series. Methodology is undergoing peer review –A cross-correlated time series synthetic study presented to joint conference of Western North American Region of the Biometric Society and the Institute of Mathematical Statistics –Paper using method for wind fleet capacity factor data submitted to IEEE –Kth Nearest Neighbor Method presented to NERC RIS-IVGTF team

12. October 29, 2009NW Wind Integration Forum12 Goal of Historic Temperature Correlated Synthetic Wind Gen It has been well established that temperatures affect load where extreme high or low temperatures translate into high loads. The synthetic wind power generation data recreates certain statistical characteristics of the original or observed wind power generation data set. The characteristics to focus on are: –Distribution/Density –Lag Structure or Persistence –Cross-Correlation The long-term temperature-correlated wind generation records will be incorporated into the existing resource adequacy studies using the GENESYS model, which will perform Monte Carlo picks on temperature-years, thus pointing to synthetic wind generation and loads

13. October 29, 2009NW Wind Integration Forum13

14. October 29, 2009NW Wind Integration Forum14 Wind Generation vs. Temperature

15. October 29, 2009NW Wind Integration Forum15 Forum Wind Methods consistent with other Wind Forums NERC: Joint Integration of Variable Generation Task Force (IVGTF) – Resources Issues Subcommittee (RIS) Task 1.2 (Capacity Value) and Task 1.4 (Flexible Resources to integrate Variable Generation) Teams –IVGTF Report: http://www.nerc.com/docs/pc/ivgtf/IVGTF_Report_041609.pdf http://www.nerc.com/docs/pc/ivgtf/IVGTF_Report_041609.pdf WECC: Variable Generation Subcommittee (VGS) Planning Work Group Northwest: PNW Resource Adequacy Forum/NW Wind Integration Forum

16. October 29, 2009NW Wind Integration Forum16 Wind Capacity Value Methods Effective Load Carrying Capability (ELCC) approach –Evaluate effective wind capacity contribution based on LOLP studies with and without wind generation & same target (GENESYS Approach) –Need sufficient wind generation data to simulate full range of generation under various conditions, especially if wind and loads correlated at times –Need realistic depiction of combined uncertainties Contribution of variable generation to system capacity during high-risk hours using historical data –Investigate contribution of wind capacity during heat wave and cold snap events in PNW because of evidence of statistical relationship between lack of wind generation when it gets very hot or very cold (Forum Wind Capacity Subgroup Approach) Correlation between resource contribution and the resource mix by system (e.g. what is appropriate for a hydro based system) –Wind may contribute more in energy-limited system if certain amount of wind generation can be counted upon during drought

17. October 29, 2009NW Wind Integration Forum17 Counting Wind toward Capacity Adequacy in the NW January 2009 Cold Snap

18. October 29, 2009NW Wind Integration Forum18 Synthetic Wind Generation: Historic Cold Snaps

19. October 29, 2009NW Wind Integration Forum19 Synthetic Wind Generation: Historic Cold Snaps

20. October 29, 2009NW Wind Integration Forum20 Simulated Wind Generation: Historic Heat Waves

21. October 29, 2009NW Wind Integration Forum21 Simulated Wind Generation: Historic Heat Waves

22. October 29, 2009NW Wind Integration Forum22 Observed Wind over all hours: Regional Load Duration Treating the wind as negative load changes the duration curve. –Minimum distance between the two curves is about 1.6% of the nameplate. –99.5% of the hours have a 6.8% of the nameplate or greater “contribution” of wind toward reducing the load durations.

23. October 29, 2009NW Wind Integration Forum23 NW Wind Capacity Value using quasi-ELCC Approach Difference between the percentiles of the load durations show us: –Between the 10 th and 90 th percentiles the contribution of the wind fleet was fairly flat with a slight trend of more energy during the lower loads. –During the highest observed loads the difference is minimal. ELCC Focus

24. October 29, 2009NW Wind Integration Forum24 NW Wind Capacity Value over 6 peak hours (high risk hrs) Alternately looking at the differences between the six peak hours with and without wind yields: –A minimum difference of zero. –97% of the time, contribution is only.03% of nameplate in aMW. –91% of the time, “contribution” of 1% of the nameplate in aMW.

25. October 29, 2009NW Wind Integration Forum25 18-hour wind capacity 2006 First Day 18hr Mean Load (aMW) 18hr Mean Load Less Wind (aMW) Difference (aMW) % of Integrated Fleet Nameplate Jan 20061/16/200626260.0925471.7788.3934.52% Feb 20062/16/200628775.728097.36678.3429.70% Mar 20063/8/200626556.6725366.261190.4152.12% Apr 20064/17/200622856.122194.6661.528.96% May 20065/16/200624012.6723953.7358.942.58% Jun 20066/26/200626325.4526045.51279.9412.26% Jul 20067/23/200627300.826920.43380.3716.65% Aug 20068/7/200624653.8123934.57719.2431.49% Sep 20069/5/200623707.8923402.34305.5513.38% Oct 200610/30/200626282.4326114.24168.197.36% Nov 200611/27/200630132.929882.64250.2610.96% Dec 200612/18/200629122.2929120.182.110.09%

26. October 29, 2009NW Wind Integration Forum26 18-hour wind capacity 2007 First Day 18hr Mean Load (aMW) 18hr Mean Load Less Wind (aMW) Difference (aMW) % of Integrated Fleet Nameplate Jan 20071/15/200730014.6230001.9612.660.55% Feb 20071/31/200728100.3328072.5627.771.22% Mar 20072/27/200726696.825667.811028.9945.05% Apr 20074/2/200723559.3323089.03470.320.59% May 20075/30/200723417.0723392.2924.781.08% Jun 20076/19/200723667.923336.97330.9314.49% Jul 20077/10/200726801.6726639.63162.047.09% Aug 20078/13/200724816.5224733.0483.483.65% Sep 20079/10/200722875.1722729.48145.696.38% Oct 200710/31/200724168.5923924.87243.7210.67% Nov 200711/26/200727626.2827150.03476.2520.85% Dec 200712/10/200728796.6328521.3275.3312.05%

27. October 29, 2009NW Wind Integration Forum27 18-hour wind capacity 2008 First Day 18hr Mean Load (aMW) 18hr Mean Load Less Wind (aMW) Difference (aMW) % of Integrated Fleet Nameplate Jan 20081/22/200830891.6930822.2569.443.04% Feb 20082/4/200827867.2226529.091338.1358.59% Mar 20083/26/200825613.5124654.68958.8341.98% Apr 20083/31/200825289.7824821.24468.5420.51% May 20085/17/200823016.0822142.59873.4938.24% Jun 20086/30/200826012.5825591.03421.5518.46% Jul 20087/7/200825511.9425088.61423.3318.53% Aug 20088/13/200826222.1626016.39205.779.01% Sep 20089/15/200822821.7622705.31116.455.10% Oct 200810/22/200822961.1222564.17396.9517.38% Nov 200811/24/200824885.2524809.1776.083.33% Dec 200812/15/200832175.0831638.4536.6823.50%

28. October 29, 2009NW Wind Integration Forum28 Status of Wind Discussions 10/16/09 Resource Adequacy Forum Technical Committee Meeting –Evidence suggests that 5% Placeholder Value for Wind Capacity is too high –Use different WINTER & SUMMER values for Wind Capacity in regional Planning Reserve Margin (PRM) Calculation: PRM = (∑ 1 18 hr regional resources – regional 1 in 2 load)/ ∑ 1 18 hr regional 1 in 2 load Current physical resource adequacy thresholds are: –PRM winter ≥ 23% –PRM summer ≥ 24%

29. October 29, 2009NW Wind Integration Forum29 Next Steps In the Short-term, refine Wind Capacity Value in PRM Equation –SOME OPTIONS: Select 95 th percentile wind from summer & winter all hour wind vs. load duration curves ~ Slide 23 Select 95 th percentile wind from summer and winter 6 peak or 18 peak load hour duration curves ~ Slide 24 Using actual (and possibly synthetic) wind generation data over historical heat wave and cold snap events, calculate average wind capacity contribution over 18 hour sustained peak or 6 peak hour period In the Long-term, perform true ELCC evaluation using Monte Carlo picks of temperature-years to point to loads and wind generation –Create additional long-term temperature-correlated synthetic wind generation records for use in GENSYS