Application of RNN to the Wind power forecasting problem

Under the pressure of environmental pollution and an energy crisis, the use of renewable energy sources is rapidly increasing as alternatives to conventional sources. Wind power prediction (WPP) models can provide useful information about the upcoming wind power generation profile. A Recurrent Neural Network (RNN) based method was proposed to predict wind power by learning the time relationship contained in the time series. Unlike feedforward neural networks or any other classical methods, the RNN is a variant of artificial neural networks, and its unique internal state that carries memory of past values makes an RNN able to form a directed graph along a sequence, and learn the temporal dynamic behavior for a time series.