Wind power forecasting using advanced neural networks models

In this paper, an advanced model, based on recurrent high order neural networks, is developed for the prediction of the power output profile of a wind park. This model outperforms simple methods like persistence, as well as classical methods in the literature. The architecture of a forecasting model is optimised automatically by a new algorithm, that substitutes the usually applied trial-and-error method. Finally, the online implementation of the developed model into an advanced control system for the optimal operation and management of a real autonomous wind-diesel power system, is presented.