Two-Stage Artificial Neural Network Model for Short-Term Load Forecasting

Abstract

Abstract Short-term load forecast (STLF) is important to ensure stable, reliable and efficient power system operations. In this paper, we propose a two-stage artificial neural network (ANN) model for load forecasting application. The proposed system is currently being tested in the Taiwan Power Company (TPC) with potential for future adoption in their decision support systems. The accuracy of the proposed forecast model is tested using the historical data obtained from TPC; the results show that the proposed two-stage ANN model can outperform a previously proposed single stage ANN load forecast model.