A secondary decomposition based hybrid structure with meteorological analysis for deterministic and probabilistic wind speed forecasting
- 物理技术－已发表论文 
Abstract(#br)Accurate wind speed forecasting could ensure the reliability and controllability for the wind power system. In this paper, a new hybrid structure based on meteorological analysis is proposed for the wind speed vector (wind speed and direction) deterministic and probabilistic forecasting. Twelve kinds of secondary decomposition methods are employed to decrease the interference existing in the data. To improve the training efficiency and accelerate the sample selection process, active learning is employed. Four different wind speed datasets collected from Ontario Province, Canada, are utilized as case studies to evaluate the forecasting performance of the proposed structure. Experimental results show that the proposed structure based on meteorological analysis is suitable for wind speed vector forecasting and could obtain better forecasting performance. Furthermore, except accurate deterministic forecasts, the proposed structure also provides more probabilistic forecasting information.