A novel implementation of kNN classifier based on multi-tupled meteorological input data for wind power prediction

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• 作者：Mehmet Yesilbudak^a ; ^{myesilbudak@nevsehir.edu.tr} ; Seref Sagiroglu^b ; ^{ss@gazi.edu.tr} ; Ilhami Colak^c ; ^{ilhcol@gmail.com}
• 关键词：Wind power production ; Very short-term prediction ; Multidimensional meteorological data ; k-nearest neighbor classifier
• 刊名：Energy Conversion and Management
• 出版年：2017
• 出版时间：1 March 2017
• 年：2017
• 卷：135
• 期：Complete
• 页码：434-444
• 全文大小：4699 K
• 卷排序：135

文摘

An accurate wind power prediction model is proposed for very short-term horizon. The k-nearest neighbor classifier is implemented based on the multi-tupled inputs. The variation of wind power prediction errors is evaluated in various aspects. Our approach shows the superior prediction performance over the persistence method.