Load forecast errors for ERCOT (top) and MISO (bottom) with data separated into three different load forecast classes
Figure 4. Load forecast errors for ERCOT (top) and MISO (bottom) with data separated into three different load forecast classes. All values are normalized by the mean load forecast. Low forecasts include all forecasts less than 90% of the mean forecast; medium forecasts are between 90 and 120% of the mean forecast; and high forecasts are greater than 120% of the mean forecast. Histogram bars show the relative frequency of the actual data while solid lines show the fitted logistic distributions.
Day-ahead load and wind power forecasts provide useful information for operational decision making, but they are imperfect and forecast errors must be offset with operational reserves and balancing of (real time) energy. Procurement of these reserves is of great operational and financial importance in integrating large-scale wind power. We present a probabilistic method to determine net load forecast uncertainty for day-ahead wind and load forecasts. Our analysis uses data from two different electric grids in the US with similar levels of installed wind capacity but with large differences in wind and load forecast accuracy, due to geographic characteristics. We demonstrate that the day-ahead capacity requirements can be computed based on forecasts of wind and load. For 95% day-ahead reliability, this required capacity ranges from 2100 to 5700 MW for ERCOT, and 1900 to 4500 MW for MISO (with 10 GW of installed wind capacity), depending on the wind and load forecast values. We also show that for each MW of additional wind power capacity for ERCOT, 0.16–0.30 MW of dispatchable capacity will be used to compensate for wind uncertainty based on day-ahead forecasts. For MISO (with its more accurate forecasts), the requirement is 0.07–0.13 MW of dispatchable capacity for each MW of additional wind capacity.