标题:The short-term load forecasting using the kernel recursive least-squares algorithm
作者:Liu, Chen ;Liu, Fasheng
通讯作者:Liu, C.
作者机构:[Liu, Chen ] School of Information Science and Engineering, Shandong University of Technology, Qingdao, 266510, China;[Liu, Fasheng ] School of Inform 更多
来源:Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010
出版年:2010
卷:7
页码:2673-2676
DOI:10.1109/BMEI.2010.5639855
摘要:This paper presents a new approach for short-term load forecasting problem based on the kernel recursive least-square algorithm (KRLS). The kernel recursive least-square algorithm is an online real-time kernel-based algorithm and also capable of efficiently solving in recursive manner nonlinear least-square predictive problems. In this paper we consider the loads as a time series, through training the KRLS, we give the one-step ahead load forecasting. The test result of short term load forecasting series shows that the precision of load forecasting is greatly improved by means of the new method. ©2010 IEEE.
收录类别:EI
资源类型:会议论文
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