Study the optimal operation of electric PV/B/D generation system by neural network

This paper introduces an application of artificial neural network on the operation control of the photovoltaic/Battery/Diesel hybrid power generation system. It is generally agreed that using local information such as generated power from PV solar cells array and state of battery charge are calculated by new software under known insolation 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, insolation and temperature at Elminia site, Egypt. The results show that the selected neural network architecture gives reasonably accurate operation of the system.