Improved wind power forecasting using a combined neuro-fuzzy and artificial neural network model

Abstract

The intermittent nature of the wind creates significant uncertainty in the operation of power systems with increased wind power penetration, Considerable efforts have been made for the accurate prediction of the wind power using either statistical or physical models. In this paper, a method based on Artificial Neural Network (ANN) is proposed in order to improve the predictions of an existing neuro-fuzzy wind power forecasting model taking into account the evaluation results from the use of this wind power forecasting tool, Thus, an improved wind power forecasting is achieved and a better estimation of the confidence interval of the proposed model is provided. © Springer-Verlag Berlin Heidelberg 2006.