Narx Based Short Term Wind Power Forecasting Model

Abstract

This paper contributes a short-term wind power forecasting through Artificial Neural Network with nonlinear autoregressive exogenous inputs (NARX) model. The meteorological parameters like wind speed, temperature, pressure, and air density are considered as input parameters collected from KL University area and the calculated generated power as output parameters of neural network to predict the wind power generation. Based on hybrid forecasting technique a code is developed in MATLAB at different hidden layers and delay times.