Application of Recurrent Neural Network to Long-Term-Ahead Generating Power Forecasting for Wind Power Generator

In recent years, there have been problems such as environmental pollution resulting from consumption of fossil fuel, e.g., coal and oil. Thus, introduction of an alternative energy source such as wind energy is expected. Wind speed is not constant and wind power output is proportional to the cube of the wind speed. In order to predict the power output for wind power generators as accurate as possible, it requires the method of wind speed estimation. In this paper, a technique consider the wind speed of each month, and confirm the validity of neural network (NN) to predict wind speed by computer simulations. Since recurrent neural network (RNN) is known as good tool for time-series data forecasting, the authors propose an application of RNN for the wind speed prediction. The proposed method in this paper does not require complicated calculations and mathematical model