An efficient computing model for renewable energy systems

This paper presents an efficient computing model for wind speed prediction, which uses radial basis function (RBF) network. Wind energy is inexhaustible unlimited clean energy. In order to save conventional energy, wind power in the world has importance. By the reason of fluctuation and volatility of wind, wind speed prediction has the challenge in the stability of renewable energy system. The radial basis function (RBF) model is a 3 layer structure which contains input, hidden and output layer. The selection of parameter is important in this model. Here RBF network is used in the neural networks application. The objective of this paper is to compute predicted output (wind speed) based on RBFN algorithm. The results are obtained after the training and testing of network. Simulation result shows the performance of ANN for predicting wind speed in renewable energy systems.