Abstract: Systems and methods improve the forecast of electricity consumption, and/or refining such predictions. Predictions may be refined by accounting for factors such as preliminary predictions, pricing and cost information associated with future supply of energy, the extent of anticipated changes in the predictions, the time of day and/or anticipated daylight for the period of time. Coefficient values are calculated for a forecast error model that takes into account factors related to electricity consumption using existing historical electrical grid data. Using the calculated values, the forecast error model may be applied to current electricity demand forecasts.

Abstract: Systems and methods improve the forecast of electricity consumption, and/or refining such predictions. Predictions may be refined by accounting for factors such as preliminary predictions, pricing and cost information associated with future supply of energy, the extent of anticipated changes in the predictions, the time of day and/or anticipated daylight for the period of time. Coefficient values are calculated for a forecast error model that takes into account factors related to electricity consumption using existing historical electrical grid data. Using the calculated values, the forecast error model may be applied to current electricity demand forecasts.