Wind speed forecasting using Multi-Layer Perceptron (MLP) neural network

The electricity production of wind farms is fluctuating because its dependency on the wind speed, so, improving of technical and economic integration of wind energy into the electricity supply system requires improving wind speed prediction accuracy. This paper deals with a neural network approach for Short term wind speed forecasting. Now a day, short-term wind speed forecasts have become gradually more important for the power system management or energy trading due to the large penetration of wind power technology and development of wind energy markets. In this new era, short-term wind speed forecasting is necessary for producers and consumers to become stable in the electricity market as in the electricity grid at any moment balance must be maintained between electricity consumption and generation. In this paper, a multi-layere perceptron (MLP) neural network, trained by the back propagation learning algorithm has been used for hourly forecasting of wind speed in the region of Khoram-Abad.

کلیدواژه ها:

Wind speed ، Multi-Layer Perceptron (MLP) ، neural network ، forecasting