基于GA的电力系统多目标模糊无功优化

胡晨成; 于艾清; 柏扬; 王鲁杨

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DOI:10.3969/j.issn.1006-4729.2014.06.007

Journal of ShangHai University of Electric Power :2014,30(6):525-529

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基于GA的电力系统多目标模糊无功优化

胡晨成¹, 于艾清¹, 柏扬², 王鲁杨¹

(1.上海电力学院电气工程学院;2.国网上海市电力公司发展策划部)

Multi-Objective Fuzzy Reactive Power Optimization Based on GA

HU Chencheng¹, YU Aiqing¹, BAI Yang², WANG Luyang¹

(1.School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China;2.Development Planning Dept., State Grid Shanghai Municipal Electric Power Company, Shanghai 200122, China)

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Received:September 24, 2014

中文摘要: 针对传统无功优化的目标单一性,建立了以有功网络损耗和节点电压偏差均最小为目标的无功优化模型,采用模糊数学将不同量纲目标进行归一化,并转化为单目标模糊规划模型.鉴于多目标无功优化模型的复杂性,以及连续、离散控制变量并存,采用遗传算法搜索全局最优解.对某21节点系统进行了多目标无功优化分析,验证了该模型的可行性和优越性.

中文关键词: 无功优化遗传算法多目标优化

Abstract:Reactive power optimization model is established with an objective of minimizing active power loss and node voltage deviation. The objectives of different dimensions are normalized using fuzzy math. The multi-objective programming model is converted into a single objective fuzzy programming model. In viewof the optimization complexity and the coexistence of discrete variables and continuous variables,genetic algorithm is presented for finding global optimal solution. Finally,a multi-objective reactive power optimization analysis of a 21-bus system is made,proving the feasibility and validity of the model and algorithm.

keywords: reactive power optimization genetic algorithm multi-objective optimization

文章编号：20140607 中图分类号： 文献标志码：

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Author Name	Affiliation	E-mail
HU Chencheng	School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
YU Aiqing	School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China	yuaiqing@shiep.edu.cn
BAI Yang	Development Planning Dept., State Grid Shanghai Municipal Electric Power Company, Shanghai 200122, China
WANG Luyang	School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China