- 期刊
- OpenAccess
Wind Power Forecasting: A Review of Statistical Models-Wind Power Forecasting
並列摘要
Several wind power or wind speed forecasting methods have been reported in the literature over the past few years. A brief overview and comparison of all these techniques is the main focus of the present work. This paper provides insight on the foremost forecasting techniques, associated with wind power and speed, based on numeric weather prediction (NWP), statistical approaches, ARIMA models, artificial neural network (ANN), grey models, data mining models and hybrid techniques over different time-scales. The various wind power forecasting techniques have been categorized into following three major classes: (i) Physical models, (ii) Statistical models, and (iii) Hybrid models. It has been observed that forecasting accuracy of different models vary due to different types of terrain and wind turbulence at the different wind farms. Based on the assessment of wind power forecasting techniques, further direction for additional research and application is proposed.