Wind power prediction based on a convolutional neural network

Wind power has recently become one of the most important renewable energy sources due to its advantages including less pollution, flexible investment, short construction period and less land occupation. The uncertainty of the speed and direction of wind causes wind power prediction to be extremely difficult to wind power generation. The Convolutional Neural Network (CNN) has the advantage of big data processing. CNN addresses data in the form of a two-dimensional matrix and is widely applied in the field of image processing. This paper applies CNN to wind power prediction. With historical data of wind power from a wind farm as input, this paper sets and trains the CNN model in MATLAB. The results of the prediction prove the feasibility of CNN applied to regression prediction.