Wind speed and power prediction using MK-PINN

Abstract

A multi-kernel pseudo inverse neural network (MKPINN) is proposed in this paper for efficient wind speed and power forecasting. The proposed model has been compared with Gaussian, wavelet, polynomial and sigmoid kernel. To get best output and learning methodology and stability pseudo inverse neural network is added, which substitutes the hidden layer with kernel function. This helps to achieve more accurate and faster response. Various case studies have been carried out from ten minutes to five hours interval in order to prove it accuracy.