International Workshop on Wind Energy Development Cairo, Egypt. ERCOT Wind Experience

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1 International Workshop on Wind Energy Development Cairo, Egypt ERCOT Wind Experience March 22, 21 Joel Mickey Direcr of Grid Operations Electric Reliability Council of Texas

2 ERCOT 2 2

3 ERCOT at a Glance Serves 22 million cusmers - 8% of Texas load 4,3 miles of highvoltage transmission lines generating units Record peak demand of 63,43 MW on 7/13/9 Leads the nation in wind generation 3 3

4 Wind Power Capacity of the U.S

5 ERCOT Wind Power Capacity

6 Renewables in Texas Texas State Energy Conservation Office (SECO) reports Texas has the largest renewable energy potential in the U.S. by a large margin. West Texas has the highest wind energy potential but relatively low load Lack of existing high voltage transmission lines 6 6

7 Congestion Generation and Load are separated by large distances Transmission system has limitations ERCOT restrains an N-1 system Generar Transformer Transmission Line 7 7

8 ERCOT Wind Transmission Expansion 8 8

9 Transition the Nodal Market 9 9

10 Transition from Zonal Nodal Market ERCOT Zonal ERCOT Nodal 1 1

11 Nodal Market Congestion Management - All congestion is local - Resource specific dispatch - Locational Marginal Price (LMPs) 4+ Nodes - Costs are directly assigned Improved price signals Improved dispatch efficiencies 11 11

12 Wind Issues Any energy schedule from a wind resource is a forecast with associated uncertainty that must be covered by reserves Schedule/forecast error Requires additional reserves Intra-interval variability Requires additional regulation Aggregate wind output changes, although somewhat predictably Typical diurnal pattern Large ramp events Both require sufficiently-flexible resources Wind generars do not currently provide primary frequency response Inertia Governor response event Other issues, such as low-voltage ride through, are not as relevant this discussion 8/2/29 12 PUCT Project W k h

13 Wind Generation Resource (WGR) Power Forecasting Provided by AWS Truewind Two forecasts are produced for each WGR The Wind Generation Resource Production Potential (WGRPP) is an 8% probability of exceedence forecast The Short-Term Wind Power Forecast (STWPF) is the most likely or % probability of exceedence forecast Aggregate Wind Power Forecasts: Red = STWPF, Green = WGRPP Each hour a new forecast is created for the next 48 hours Aggregate forecasts are also created and sent ERCOT 8/2/29 13 PUCT Project W k h

14 May 16, 29 Case (forecast delivered 3:1 PM CDT May 1) Large over estimate of the power production from midnight AM as a cold front approached and passed through the region Weather models overestimated the southerly wind speeds ahead of the front ERCOT Forecast and Observed Generation on /16 Observed Hour of the Day (CDT) Forecasted 8/2/29 14 PUCT Project W k h

15 Example Weather Model 1 1

16 Wind Generation Resource (WGR) Power Forecasting cont. Inputs in the forecasts: WGR site-specific MW and meteorological data Outage scheduler data Registration data Other (i.e. National or regional weather service data) MW Availability Scheduler Interface Demo ERCOT data designed come from Nodal systems Have needed develop work-around for Zonal: PRR 794 AWS provided MW availability scheduler 8/2/29 16 PUCT Project W k h

17 Wind Generation Resource (WGR) Power Forecasting cont. Wind Output/Curtailments vs. Day Ahead (16) Resource Plans for May 9 % of Hours with Output + Wind Curtailments >= Resource Plan MW (Target = 8%) 71.64% Note: QSEs must use AWST provided WGRPP forecast for Day-Ahead Resource Plans 8/2/29 17 PUCT Project W k h 17

18 Causes of the Sixty Largest ERCOT Wind Power Ramps January 1 April 2, 29 Down Ramps Up Ramps Coid Front - Up Ramp Low Level Jet - Up Ramp Pressure Gradient Change - Up Ramp Daytime Mixing - Up Ramp Dry Line - Up Ramp Pressure Gradient Change - Behind Cold Front - Down Ramp Pressure Gradient Change - High Pressure - Down Ramp Pressure Gradient Change - Other - Down Ramp Nocturnal Stabilization - Down Ramp Low Level Jet - Down Ramp Ramp events have different meteorological causes and thus the optimal parameters for tracking and predicting them are different 8/2/29 18 PUCT Project W k h

19 Wind vs Load (MW) Load Wind 19 19

20 Actual Wind Output as a Percentage of the Total Installed Wind Capacity at Peak 1% 9% 8% (Wind Output / Installed Wind Capacity)% 7% 6% % 4% 3% 2% 1% % 2

21 ERCOT Total Wind Vs Load ERCOT Total Wind Vs Load Ocber 28, & (1.11%) MW at 19:41: MW & (18.22%) MW at 3:6: 2 3 : 2: 4: 6: 8: 1: 12: 14: 16: 18: 2: 22: : Time Load Wind Linear (Wind) 3 21

22 Ramping 22 8/2/29 PUCT Project W k h

23 ERCOT Large Ramp Alert System (ELRAS) System awareness ol provided by AWS through a web interface Utilizes the same data that is being provided by ERCOT for the wind power forecasts Includes the following: An estimation of the probability of a defined ramp event (i.e. 1 MW up ramp in a hour) beginning in a particular interval Information regarding the weather event which is most likely cause the ramping event (i.e. a cold front) Additional attributes for each predicted ramp event including most likely start time, duration and maximum ramp rate Time variant graphics provide additional situational awareness Looks from the current time 6 hours in the future 8/2/29 23 PUCT Project W k h

24 ERCOT Large Ramp Alert System (ELRAS) cont. Example overview display Botm left graph shows that there is a 4% chance that there will be a systemwide WGR down ramp of 37 MW/1 Min starting between 18:4 and 19: Note: These displays are being developed as part of the project and may not be exactly the same as 24 what will finally be provided ERCOT 8/2/29 PUCT Project W k h

25 Intra-Interval Change s d 12 r io e P te 1 u in -M 8 e iv F f o6 r e b m4 u N 2 Distribution of Minute Deltas for ERCOT Load and Net ERCOT Load with Wind and Wind *3 for July 28 July 29 Excluding May Load Load Wind Load Wind * 3 GE A/S Study predicted REG requirement increase of 2-23% for 1 GW of wind Actual distribution for current wind generation appears have somewhat longer tails than GE predicted Additional wind generation will be more geographically dispersed < > 7 MW Courtesy IMM 8/2/29 2 PUCT Project W k h

26 Ancillary Service Methodology Regulation Reserve (reserves deployed by AGC) Procured amount is intended ensure that regulation reserves are sufficient cover 98.8% of the intervals Calculated based on previous 3 days and same month last year Accounts for the expected increase in installed Wind Generation for the upcoming month Provision increase regulation requirements if the last 3 day average CPS1 score falls below 1 8/2/29 26 PUCT Project W k h

27 How Wind resources increase challenges Maintaining adequate dynamic reactive capability respond voltage events. Conventional synchronous generating units utilize a fairly standardized Aumatic Voltage Regular technology provide voltage control aumatically Older (Inductive) wind units have provide reactive with external switching devices while new (asynchronous) wind units can provide reactive capability through internal power electronics

28 How Wind Resources Increase Challenges Low Voltage Ride-through. Technologies in wind generars have varying capabilities for remaining online through brief dips in transmission voltage. Such dips are rare, but can be wide-spread across the transmission network in the event of a severe (3 phase) transmission line fault. Without low voltage ride-through, many wind generars could trip simultaneously, increasing system generation lost for a single contingency

29 Summary of ERCOT Initiatives Commissioned an Ancillary Service study in conjunction with CREZ docket Supporting the Wind Operations Task Force and Renewable Technologies Work Group Exploring additional forecasting ols with AWS Truewind Developed a ramp forecast Improve operar situational awareness Developing a risk based reliability assessment ol Considers unit forced outages Considers wind & load forecast accuracy. Developing High Wind Generation Scenarios for the Operar Training Simular Expanding Voltage Security Assessment Tool moniring include West Texas Performing Low Voltage Ride-through dynamic fault analysis and steady state voltage support analysis

30 The Future Challenges of Wind Energy Questions?