Wind speed forecast is essential in wind energy conversion system and may fail to operate power plant at non optimal region if not properly forecasted. This paper focuses the short term wind speed forecasting using conventional statistical method and artificial neural networks such as back propagation network (BPN), generalized regression neural network (GRNN) and radial basis function networks (RBFN). The developed algorithms and networks are trained and tested for wind speed data which are measured at an interval of 15 minutes. In this paper we compared the performance of RBFN and other networks for effective wind speed forecasting. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.