Analyzing the probabilistic distribution of the predicted wind speed

Wind power generation is characterized by its variability and uncertainty in the wind speed. Due to the irregular nature of wind power production, accurate prediction of wind speed is essential for its application in optimum power flow, transmission congestion, economic load dispatch and electricity market clearing prices. Wind speed of a wind farm is affected by conditions of the environment in which the wind farm is built, such as temperature, humidity, dew point, atmospheric pressure and wind direction. In this paper, five ANN techniques namely FFBP, CFBP, PNN, GRNN and KNN are considered to predict the wind speed. The feasibility of the proposed techniques is evaluated using the performance measures such as MSE, MAPE and linear regression and it is observed that GRNN is superior amongst the other methods that are used. Also, probability distribution of the predicted wind speed is found using Weibull probability distribution with various scale and shape factors. Keywords-Wind speed prediction; ANN; FFBP; CFBP; PNN; GRNN; KNN; Wind speed;Weibull probability distribution