Application of artificial neural network for short term load forecasting

As accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional loads forecasting methods have been developed. In this paper we present the development of short term load forecaster using artificial neural network (ANN) models. Three approaches have been undertaken to forecast the load demand up to 24 hours ahead. The first model is a model that has 24 output nodes to forecast a sequence of 24 hourly loads at a time. The second ANN model forecasts the peak and valley load and the result is used to forecast the load profile, and finally a system with 24 separate ANNs in parallel, one for each hour of the days is used to forecast the load demand. These models are applied to the South Sulawesi Electricity System and the comparative summary of their performances are evaluated through simulation.