Neuro-short-term load forecast of the power system in Kuwait

Abstract This paper is concerned with short-term load forecast of the electrical power system in Kuwait. It applies artificial neural networks (ANN's) to predict the half hour total system load. The input pattern incorporates the temperature and humidity effects. Simulation results have indicated that the developed forecasting approach is flexible and efficient.