Short-term load forecasting investigations of Egyptian electrical network using ANNs

Load forecasting is the one of the most essential role of electric power systems as it absolutely shares the system opportunity. It is responsible for repairing the planning for future. Artificial Neural Network´s (ANNs) models have implemented to produce accurate results for short-term load forecasting with time lead being few minutes, hour, 24 hours of a day extending to a week. In this paper, load forecasting situation of Egyptian Power Utility has been investigated to define its problems and specify the most applicable method of load forecasting suitable for its load curve growth. Extensive studies have been done to improve the performance of the proposed ANN. The results are compared with the forecasted loads calculated with other techniques by the Egyptian Electrical Utility.