Short-term load forecasting by artificial neural networks using individual and collective data of preceding years

This paper presents a short-term load forecasting technique for summer using an artificial neural network (ANN). The purpose of this study is to forecast accurately daily peak load for a target period using actual data from the same period of the previous several years as training data. This paper describes two methods. In one method, the actual data of each year for the several years earlier are used for each ANN. The other method uses the collective data of several years for the training of the ANN. With the proposed method, the mean absolute forecasting error was below 2%.