Wind Power Prediction Using Artificial Neural Network Model: A Case Study

Considering the high level of pollution that threatens our earth, energy from the wind represents a major alternative to fossil fuels, thanks to its high potential and large production. In order to benefit from this renewable energy, several methods of predicting the production of wind energy have been created and applied. In this article, a case study of wind energy forecasting for a Spanish wind installation in Sota Vento is realized. The employed methodology uses artificial neural networks based on a feed forward algorithm, a commonly applied method of artificial intelligence. The tool used is the NN-toolbox from MATLAB, and the model chosen is the Nonlinear autoregressive exogenous. After the model simulation in MATLAB, the results show that the determination coefficient R has a value close to 1 and the mean square error tends to 0. This confirms the average prediction of the model. For better performance, it is preferable to input more historical data and to combine ANNs with metaheuristic algorithms.