Multi-region load forecasting considering alternative meteorological predictions

Abstract

Electricity load forecasting is always a key instrument for the effective operation and planning of power systems. This paper presents our recent works on short-term electricity demand forecasting for an electric utility in Midwest US focusing on day-ahead operation and market. The target system covers a large geographical area, and several alternative meteorological forecasts are available from different commercial weather services.For a system with large geographical area, a single model for load forecasting of the entire area sometimes cannot guarantee satisfactory forecasting accuracy because of the load diversity. We therefore develop a multi-region load forecasting model, which can find the optimal region partition under diverse weather and load conditions and finally achieve more accurate forecasts for aggregated system demand. Furthermore, to effectively take advantage of the alternative meteorological predictions in the load forecasting system, combining forecasting using adaptive coefficients is applied to share the strength of the different temperature forecasts. The proposed forecasting system has been tested by using the real data from the system. A range of comparisons with different forecasting models have been conducted. The forecasting results demonstrate the superiority of the proposed methodology. Shu Fan (M'08-SM'09) received the B.S., M.S., and Ph.D. degrees in the