Application of Artificial Neural Network for Wind Speed Prediction and Determination of Wind Power Generation Output

Wind power generation increases rapidly. The available wind energy depends on the wind speed, which is a random variable. For the wind-farm operator, this poses difficulty in the system scheduling and energy dispatching, as the schedule of the wind-power availability is not known in advance. In this research, we propose an intelligent technique for forecasting wind speed and power output of wind turbine from several hours up to 24 hours ahead. This technique is based on artificial neural network (ANN). The data was offered by the Japan Meteorological Agency. These data include the “multi-story meteorological data” and the “ground meteorological observation data” of Aomori area where is located in the north of Honshu, Japan. The Back-propagation (BP) neural network is then supplied with the data to establish the relationship between the inputs and the output. The model based on the neural network demonstrated a good agreement and produced the wind forecast with the accuracy of 90% and above.