In, it is mentioned that different types of conventional statistical approaches, such as auto regressive moving average (ARMA) models, auto regressive integrated moving average (ARIMA) models, and Kalman filter can be considered for wind speed forecasting. Besides, machine learning based techniques such as multilayer perceptron (MLP) neural networks and radial basis function (RBF) neural networks are also reported to estimate the wind speed uncertainty behavior ahead of time