Short- Term Electric Load Forecasting Using Neural Networks

Artificial neural network (ANN) techniques have been recently suggested for short-term electric load forecasting by a large number of researchers. This work studies the applicability of this kind of models. The work is performed for a real forecasting application. The proposed models are capable of forecasting the next 24-hour load profile, the next hour load and the next day peak load. The inputs to the ANN models are load profiles and weather information. The ANN load forecasting models are trained on historical data that obtained from a real HV/MV substation in south of Iran. Final results indicate average errors of developed models and prove that these models can be applied to the prediction of load in real case.