基于松弛域模型的电容器无功补偿优化配置

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摘要针对电容器补偿容量和补偿位置同时进行优化的典型组合优化问题,首次提出松弛域模型,并将该模型与粒子群优化算法结合得到新型粒子群优化算法。该算法由松弛域模型动态调整搜索方向和搜索范围,不断更新松弛域范围内的粒子位置,从而使整个粒子群不断向最优位置移动,最终达到电容器补偿容量和补偿位置优化的目的。通过IEEE14、IEEE30标准节点测试系统进行测试,并与二进制粒子群优化算法进行对比分析,该算法收敛速度更快、结果更优,验证了基于松弛域模型的电容器补偿容量和补偿位置优化方法的可行性和有效性。

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	罗庆跃
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关键词 ：松弛域模型, 补偿容量和补偿位置优化, 粒子群优化算法, 二进制粒子群优化算法

Abstract：Optimal capacitor capacity and location is an combinatorial optimization problem.This paper proposes the slack region model and combines it with the particle swarm optimization to realize the slack region particle swarm optimization (SRPSO) algorithm.This new algorithm utilizes the slack region model to adjust the search velocity and search range in order to update particles’ positions within the slack region so that the particle swarm can move toward the optimal position.The proposed method has been applied to IEEE14 and IEEE30 bus test system.Comparing to the results gained by the binary particle swarm optimization (BPSO) algorithm,the suggested one shows faster convergence rate and better results.The simulation results show the feasibility and effectiveness of the SRPSO for the capacitor capacity and location problem.

Key words： Slack region model optimal capacitor size and placement particle swarm optimization binary particle swarm optimization

收稿日期: 2014-12-28 出版日期: 2015-12-07

PACS:

TM532.3

作者简介: 罗庆跃男,1961年生,硕士,教授,硕士生导师,研究方向为电力系统运行与控制。刘白杨男,1987年生,硕士,助教,研究方向为电力系统无功优化。(通信作者)

引用本文:

罗庆跃,刘白杨,孙柳青,肖相纯,罗婷. 基于松弛域模型的电容器无功补偿优化配置[J]. 电工技术学报, 2015, 30(17): 79-84. Luo Qingyue,Liu Baiyang,Sun Liuqing,Xiao Xiangchun,Luo Ting. Optimal Capacitor Reactive Power Compensation Method Based on Slack Region Model. Transactions of China Electrotechnical Society, 2015, 30(17): 79-84.

链接本文:

https://dgjsxb.ces-transaction.com/CN/Y2015/V30/I17/79

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