Optimal operation of electric hybrid WES/BS/DG system by neural network,” The international conference on electrical engineering

The performance of the Hybrid Wind Energy System/Battery storage/Diesel Generator can be improved through an application of advanced control method. This paper introduces an application of Artificial Neural Network on the operation control of the Wind/Battery/Diesel Hybrid Power Generation System to reduce the fuel consumption. It is generally agreed that using local information such as generated power from Wind Turbine Generator and state of charge for batteries are calculated by new software under known wind speed and load demand. The computer software, which proposed here and applied to carry out these calculations, is based on the minimization of the fuel consumption by diesel generator. Different Feed Forward Neural Network architectures are trained and tested with data containing a variety of operation patterns. The back propagation technique with sigmoid transfer function is used as the training algorithm. A simulation is carried out over one year using the hourly data of the load demand, wind speed at Zafarâna site, Egypt. The results show that the selected neural network architecture gives reasonably accurate operation of the system