Optimal management of various renewable energy sources by a new forecasting method

Hybrid power systems are increasingly considered in order to produce more electrical energy by renewable sources. Energy management of these plants is a challenge and in this paper we propose a new forecasting method for renewable sources an load demand to obtain an improved management. The novelty of this approach is that the proposed wavelet recurrent neural network, WRNN performs the prediction in the wavelet domain and in addiction it also performs the inverse wavelet transform giving as output the predicted renewables and loads. The case study is an hybrid plant assembled at the University of Catania.