Short term load forecasting using ANN technique

Abstract

Load forecasting is a very important tool for energy suppliers and other participants in electric energy generation, transmission, and distribution markets. Moreover, load forecasting plays a pivotal rule for the power system planning and operation. Load forecasting has great impacts on many power system applications including energy purchasing, energy generation, load switching, contract evaluation, and infrastructure development. Many mathematical methods were proposed for short and long term load forecasting. This paper presents an approach for short-term load forecasting using the artificial neural network technique. The proposed approach utilizes the historical hourly load data for accurate estimation of loads. The proposed load forecasting approach is applied to multiple data sets and the results obtained are compared to published results. The comparisons and subsequent discussions show the efficiency of the proposed method and its superiority over other load forecasting techniques.