Maximum Instantaneous Wind Speed Forecasting and Performance Evaluation by Using Numerical Weather Prediction and On-Site Measurement

Abstract

A maximum instantaneous wind speed forecast methodology based on the autoregressive with exogenous inputs (ARX) model is proposed, in which numerical weather prediction and on-site measurement are used as inputs and the model parameters are estimated using non-parametric regression with forgetting factors. The accuracy of prediction using a proposed dynamic model is then evaluated and compared to the conventional static model output statistics (MOS) model. It is found that the prediction accuracy is improved by utilizing numerical weather prediction with a higher horizontal resolution. Finally, the predictability of the maximum instantaneous wind speed higher than 15m/s is evaluated using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The optimal quantile level of the maximum instantaneous wind speed is derived using a cost function.