可再生能源2017，Vol.35Issue(4)：515-521,7.
两种风速短临预报方法对比研究
Short-term wind speed forecasting study based on two methods
摘要
Abstract
There two groups of experinents of 10-seceond's magnitude and 15-minute's magnitude wind speed short-term forecasting have been done by using BP neural network method and least square regression method on 4 stations with different topography.The study found that both magnitude of 10-seceond and 15-minute forecasting experiments show:①The method of least square regression is better than BP neural network for 01# and 04# station with larger wind speed.The error is less and forecast satisfaction ratio is larger of least square regression method than that of BP neural network.②For 02# and 03# station with smaller wind speed,the forecast effect is similar between these two methods.In other words,there is no advantage of BP neural network method,which with complex algorithm,in very short-term wind speed forecasting,such as magnitude of 10-second or 15-minute forecasting.Therefore,the algorithm characteristics,the topography,geomorphologieal,climatic characteristics and period of validity should be full consideration,and the comparison test of forecasting should be performed before the method be selected.关键词
BP神经网络/最小二乘/短临预报/风速Key words
BP Neural Network/Least Square Regression Method/Short-term Forecasting/Wind Speed分类
能源科技引用本文复制引用
江滢,赵晓栋,郭鹏,叶冬..两种风速短临预报方法对比研究[J].可再生能源,2017,35(4):515-521,7.基金项目
国家自然科学基金项目(41205114). （41205114）
