标题:Parameter identification of load models using the CQDPSO algorithm
作者:Wang, Zhen Shu ;Bian, Shao Run ;Zhang, Da Hai ;Wang, Xiao Di ;Liu, Xiao Yu ;Yu, Kai
作者机构:[Wang, Zhen Shu ;Bian, Shao Run ;Zhang, Da Hai ;Liu, Xiao Yu ;Yu, Kai ] School of Electrical Engineering, Shandong University, Jinan250061, China;[Wan 更多
会议名称:2014 International Conference on Energy Research and Power Engineering, ERPE 2014
会议日期:17 May 2014 through 18 May 2014
来源:Advanced Materials Research
出版年:2014
卷:986-987
页码:1375-1378
DOI:10.4028/www.scientific.net/AMR.986-987.1375
关键词:CQDPSO; Load modeling; Parameter identification; PFR; Power system modeling
摘要:Load modeling has become a critical problem that is urgent to be solved in power system modeling. In this paper, CQDPSO algorithm, a hybrid optimization algorithm that combines quantum delta-potential-well-based particle swarm optimization (QDPSO) algorithm and chaotic optimization algorithm (COA), is proposed to identify parameters of the selected load model. Numerical results illustrate that the proposed method can improve the accuracy and reduce the computation complexity for load model parameter identifications. © (2014) Trans Tech Publications, Switzerland.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84905917349&doi=10.4028%2fwww.scientific.net%2fAMR.986-987.1375&partnerID=40&md5=6bc89c9a9f4aa5c3970a897befd16648
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