Results from the raw ensemble varied at each location, but showed the need for bias correction and ensemble calibration to improve both forecast accuracy and reliability scores. Raw ensemble wind forecasts at hub-height were generally under-dispersive with some locations also showing systematic biases.
Bias-correction and calibration of the ensemble forecast system was performed using the Component-based Post-processing System (COMPS). Calibrated forecasts at each location were produced by first removing the bias of each member by using historical observations. Calibration of the spread of the ensemble was necessary to ensure the forecasts were reliable. Reliable forecasts have the property that the forecasted probabilities accurately match the observed frequency of occurrence. Reliable forecasts are important to energy planners to optimize generation, distribution, and market trading.