基于混沌-遗传混合算法的多目标优化无功补偿研究
Research on Multi-Objective Optimal Reactive Power Compensation Based on Chaos-Genetic Hybrid Algorithm
林少佳 1林师远 1罗杰 1黄雄 1吴天杰 1陈锐忠 1周守辉 1张诚1
作者信息
- 1. 海南电网有限责任公司琼海供电局,海南琼海 571442
- 折叠
摘要
由于电力系统中存在感性负载和容性负载,导致电力系统存在电压波动.为提高电力系统无功补偿的准确性,提出了一种基于混沌-遗传混合算法的多目标优化无功补偿方法.首先,将混沌算法与遗传算法相结合,在初始阶段先利用遗传算法的全局搜索能力快速找到一组较好的初始解,随后使用混沌算法进行局部搜索和优化.其次,构建了一个多目标无功补偿优化模型.最后,基于IEEE 30节点进行了试验分析,试验结果表明,所提出的方法能有效地提高电力系统无功补偿的准确度,从而提高电力系统的运行可靠性.
Abstract
Voltage fluctuations in power systems arise due to the presence of inductive and capacitive loads.To address the accuracy of reactive power compensation,this paper proposes a multi-objective reactive power com-pensation method based on hybrid algorithms.Initially,a combination of chaos and genetic algorithms is used,where the genetic algorithm's global search capability finds a good set of initial solutions,followed by local search and optimization using the chaos algorithm.A multi-objective reactive power compensation optimization model is then constructed.Experimental analysis on an IEEE 30-node system demonstrates that the proposed method ef-fectively improves the accuracy of reactive power compensation,thereby enhancing the reliability of power system operations.
关键词
电力系统/电压波动/无功补偿/混沌算法/遗传算法Key words
power system/voltage fluctuations/reactive power compensation/chaos algorithm/genetic algorithm引用本文复制引用
基金项目
南方电网项目(070400KC23090013)
出版年
2024
NETL
NSTL
万方数据