A temperature match based optimization method for daily load prediction considering DLC effect

Abstract

This paper presents a unique optimization method for short-term load forecasting. The new method is based on the optimal template temperature match between the future and past temperatures. The optimal error reduction technique is a new concept introduced in this paper. Two case studies show that for hourly load forecasting, this method can yield results as good as the rather complicated Box-Jenkins transfer function method, and better than the Box-Jenkins method. For peak load prediction, this method is comparable in accuracy to the neural network method with backpropagation, and can produce more accurate results than the multilinear regression method. The direct load control (DLC) effect on system load is also considered in this method.