标题:An Improved PSO Algorithm for Flexible Load Dispatch
作者:Liu, Shiling; Hou, Meiyi; Zhu, Guofang; Cao, Guowei
作者机构:[Liu, Shiling; Hou, Meiyi; Zhu, Guofang] Shandong Univ, Sch Elect Engn, Jinan, Peoples R China.; [Cao, Guowei] State Grid Jiangsu Elect Power Co, St 更多
会议名称:IEEE PES Asia-Pacific Power and Energy Engineering Conference (IEEE PES APPEEC)
会议日期:DEC 07-10, 2014
来源:2014 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (IEEE PES APPEEC)
出版年:2014
卷:2015-March
期:March
DOI:10.1109/APPEEC.2014.7066108
关键词:Flexible Load Dispatch; Particle Swarm Optimization; Renewable Energy; Power generation
摘要:This paper presents an improved Particle Swarm Optimization algorithm (IPSO) for solving the flexible load dispatch problem (FLD) which relates to renewable energy power generation and three types of load composed of electric vehicle (EV), ice-storage central air conditioning and smart household appliance. The objective of the FLD problem is to utilize aggregators of the three types of load to deal with the unpredictability and intermittence of the renewable energy power generation. Facing premature convergence of PSO, the proposed method divides the search process into two stages. In the first stage, every particle selects one particle randomly to learn. The second stage is the conventional PSO algorithm. The total length the optimal particle flights for, the average velocity and the distance of every iteration are used to evaluate performance of PSO and IPSO. The results of a 12-unit system show that the IPSO is more stable and effective than PSO.
收录类别:CPCI-S;EI;SCOPUS
Scopus被引频次:1
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-s2.0-84983119782&doi=10.1109%2fAPPEEC.2014.7066108&partnerID=40&md5=698ab6b315578dec234b4b94d0a4f414
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