Wind Working Group June 13. Wind Working Group Seasonality and direction of wind issues – Study of wind direction at Elkhorn indicated that splitting.

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Presentation transcript:

Wind Working Group June 13

Wind Working Group Seasonality and direction of wind issues – Study of wind direction at Elkhorn indicated that splitting wind into two basic directions improved the forecast – Light load versus heavy load MAE since April are 57/54 MW…respectively. We have wayyyy to much error at night. We are patching holes in the dike and not fixing the problem A more comprehensive approach is needed

Wind Working Group Seasonality… Average Power decreases from Spring to Summer Spring phenomena?

Wind Working Group Wind Direction…

Wind Working Group Direction…

Wind Working Group Direction…

Wind Working Group Average last four runs of model (or less if unavailable) – Provides the best forecast over single deterministic model run – 60 days updated every month Cutting the pie too small results in loss of statistical significance Addresses seasonality – Difference between model runs can be used to develop confidence interval Average last 4 model runs Carry forward average model forecast along with max and min wind speeds Two coefficient databases need to be developed; 1 st is a function of wind direction/time of day; 2 nd for hourly averaged forecast

Wind Working Group Divide data by three directions (NW,SE, All others) – Customize per site Golden Triangle may need four directions – Use model forecast wind (WRF-NAM) Divide data into eight 3 hour time blocks Hourly data would be best but there is not enough data (yet) to be statistically significant Addresses time of day/seasonality Split by model forecast 80m and 10m winds Convert wind speed to power and develop coefficients Directional Component 80m and 10m wind 3 Hour Time blocks ( ) Use Power curves to convert wind speed to power; actuals and data passed to Excel/Matlab to develop regression coefficients as a function of time of day and wind direction

Wind Working Group Second step is developing coefficients for the first and second hour for the hourly averaged forecast – We can either develop the coefficients as a function of time of day or present method of hour one and two Same procedure would be needed as other models are added Coefficients database will be updated every 30 days Whenever a forecast is generated, the coefficients database would be used with forecast data to obtain the actual forecast Same procedure would be accomplished for hour-ahead forecasts with the addition of “persistence” as a forecast F0,F1,10m,80m variables passed to Excel to develop regression coefficients for hourly averaged forecast This establishes the coefficients database. Time of day coefficients F 0 and F 1 coefficients

Wind Working Group