Wind Power Capacity Assessment Mary Johannis, BPA, representing Northwest Resource Adequacy Forum Northwest Wind Integration Forum Technical Working Group October 29,2009
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. October 29, 2009 NW Wind Integration Forum 2
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 October 29, 2009 NW Wind Integration Forum 3
Phase I: Placeholder Wind Capacity Value of 5% Selected Probability of Occurance 0.4 0.3 0.2 0.1 0.0 BPA Analysis: 1/ Median = 7.3 % 50% of observations are below this value 50% of observations are above this value Mean or Average = 17.2 % Distribution of Wind Fleet's Capacity Factors In BPA's Control Area Newer Technology Historical Data Averaged over 6 Peak Hours (n = 60) During Winter 3 Day Cold Spells Nov, Dec and Jan from 2002-2008 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Capacity Midpoint (%) 1/ 7/8/08 Forum Tech Committee Meeting 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% October 29, 2009 NW Wind Integration Forum 4
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 October 29, 2009 NW Wind Integration Forum 5
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 October 29, 2009 NW Wind Integration Forum 6
BorisMetrics Contract Identified Issues Can a unique function calculating generation based on wind speed be determined? October 29, 2009 NW Wind Integration Forum 7
BorisMetrics Contract Identified Issues Pendleton Anemometer Data not Clean Pendleton Ave Annual Anemometer Data Height, reading method, and meter location are noted 12 11 37' manual T-107 bldg 53' man terminal bldg 20' manual terminal bldg 30' automatic terminal bldg 10 9 8 7 6 5 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 Ave Annual Wind Speed (mph) 2006 20' automatic terminal bldg Year October 29, 2009 NW Wind Integration Forum 8
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) October 29, 2009 NW Wind Integration Forum 9
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 October 29, 2009 NW Wind Integration Forum 10
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 October 29, 2009 NW Wind Integration Forum 11
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 October 29, 2009 NW Wind Integration Forum 12
19.54% Average Observed Capacity Factor 33.1% 20.7% Based on 2006 through 2008 observationsof the BPA integrated Wind Fleet during heavy load hours as def i nedby NERCand maximum regional average temperature from Seatac, Portland, and Spokane airports. October 29, 2009 NW Wind Integration Forum 13
Wind Generation vs. Temperature October 29, 2009 NW Wind Integration Forum 14
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 WECC: Variable Generation Subcommittee (VGS) Planning Work Group Northwest: PNW Resource Adequacy Forum/NW Wind Integration Forum October 29, 2009 NW Wind Integration Forum 15
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 October 29, 2009 NW Wind Integration Forum 16
Counting Wind toward Capacity Adequacy in the NW 10000 January 2009 Cold Snap BPA Balancing Authority Area Load & Total Wind Generation Jan. 5-25, 2009 9000 8000 7000 6000 MW 5000 4000 3000 BPA TOTAL WIND GENERATION 2000 BPA BALANCING AUTHORITY AREA LOAD 1000 0 1/5/09 1/6/09 1/7/09 1/8/09 1/9/09 1/10/09 1/11/09 1/12/09 1/13/09 1/14/09 1/15/09 1/16/09 1/17/09 1/18/09 1/19/09 1/20/09 1/21/09 1/22/09 1/23/09 1/24/09 1/25/09 Date/Time (5-min increments) October 29, 2009 NW Wind Integration Forum 17
Synthetic Wind Generation: Historic Cold Snaps October 29, 2009 NW Wind Integration Forum 18
Synthetic Wind Generation: Historic Cold Snaps October 29, 2009 NW Wind Integration Forum 19
Simulated Wind Generation: Historic Heat Waves October 29, 2009 NW Wind Integration Forum 20
Simulated Wind Generation: Historic Heat Waves October 29, 2009 NW Wind Integration Forum 21
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. Regional Load (MW) Duration Curves with and without Wind Adjustment 15,000 20,000 25,000 30,000 Minimum Difference = 35.7 MW at Observed Load of 31,962.4 MW Load Less Wind Duration Observed Load Duration Duration curve based on all observed hours from 2006 through 2008, regional load provided by Council, wind fleet adjustment based on observed capacity factors multiplied by current wind fleet nameplate. 0% 20% 40% 60% 80% 100% Percent of Hours Greater Than Load October 29, 2009 NW Wind Integration Forum 22
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. Difference Between Duration Curves (MW) 0 500 1000 1500 2000 Difference of Regional Load Duration Compared to Load Less Wind Duration Maximum Difference at the Lowest Observed Loads ELCC Focus Minumum Difference at Highest Observed Loads 0% 20% 40% 60% 80% 100% Duration Percentile Corresponding to Difference October 29, 2009 NW Wind Integration Forum 23
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. Difference (amw) 0 500 1000 1500 2000 Difference Between Six Peak Load Hour ObservedLoadandObservedLoadLessWind 0% 20% 40% 60% 80% 100% Percentage of Observations Less Than Difference October 29, 2009 NW Wind Integration Forum 24
18-hour wind capacity 2006 First Day 18hr Mean Load (amw) 18hr Mean Load Less Wind (amw) Difference (amw) % of Integrated Fleet Nameplate Jan 2006 1/16/2006 26260.09 25471.7 788.39 34.52% Feb 2006 2/16/2006 28775.7 28097.36 678.34 29.70% Mar 2006 3/8/2006 26556.67 25366.26 1190.41 52.12% Apr 2006 4/17/2006 22856.1 22194.6 661.5 28.96% May 2006 5/16/2006 24012.67 23953.73 58.94 2.58% Jun 2006 6/26/2006 26325.45 26045.51 279.94 12.26% Jul 2006 7/23/2006 27300.8 26920.43 380.37 16.65% Aug 2006 8/7/2006 24653.81 23934.57 719.24 31.49% Sep 2006 9/5/2006 23707.89 23402.34 305.55 13.38% Oct 2006 10/30/2006 26282.43 26114.24 168.19 7.36% Nov 2006 11/27/2006 30132.9 29882.64 250.26 10.96% Dec 2006 12/18/2006 29122.29 29120.18 2.11 0.09% October 29, 2009 NW Wind Integration Forum 25
18-hour wind capacity 2007 First Day 18hr Mean Load (amw) 18hr Mean Load Less Wind (amw) Difference (amw) % of Integrated Fleet Nameplate Jan 2007 1/15/2007 30014.62 30001.96 12.66 0.55% Feb 2007 1/31/2007 28100.33 28072.56 27.77 1.22% Mar 2007 2/27/2007 26696.8 25667.81 1028.99 45.05% Apr 2007 4/2/2007 23559.33 23089.03 470.3 20.59% May 2007 5/30/2007 23417.07 23392.29 24.78 1.08% Jun 2007 6/19/2007 23667.9 23336.97 330.93 14.49% Jul 2007 7/10/2007 26801.67 26639.63 162.04 7.09% Aug 2007 8/13/2007 24816.52 24733.04 83.48 3.65% Sep 2007 9/10/2007 22875.17 22729.48 145.69 6.38% Oct 2007 10/31/2007 24168.59 23924.87 243.72 10.67% Nov 2007 11/26/2007 27626.28 27150.03 476.25 20.85% Dec 2007 12/10/2007 28796.63 28521.3 275.33 12.05% October 29, 2009 NW Wind Integration Forum 26
18-hour wind capacity 2008 First Day 18hr Mean Load (amw) 18hr Mean Load Less Wind (amw) Difference (amw) % of Integrated Fleet Nameplate Jan 2008 1/22/2008 30891.69 30822.25 69.44 3.04% Feb 2008 2/4/2008 27867.22 26529.09 1338.13 58.59% Mar 2008 3/26/2008 25613.51 24654.68 958.83 41.98% Apr 2008 3/31/2008 25289.78 24821.24 468.54 20.51% May 2008 5/17/2008 23016.08 22142.59 873.49 38.24% Jun 2008 6/30/2008 26012.58 25591.03 421.55 18.46% Jul 2008 7/7/2008 25511.94 25088.61 423.33 18.53% Aug 2008 8/13/2008 26222.16 26016.39 205.77 9.01% Sep 2008 9/15/2008 22821.76 22705.31 116.45 5.10% Oct 2008 10/22/2008 22961.12 22564.17 396.95 17.38% Nov 2008 11/24/2008 24885.25 24809.17 76.08 3.33% Dec 2008 12/15/2008 32175.08 31638.4 536.68 23.50% October 29, 2009 NW Wind Integration Forum 27
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% October 29, 2009 NW Wind Integration Forum 28
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 October 29, 2009 NW Wind Integration Forum 29