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基于改进型蚁群算法实现配电网无功功率最佳补偿点分析
引用本文:王光增,华献宏,柴志华,张照锋,金东红,李灿灿,徐成浩.基于改进型蚁群算法实现配电网无功功率最佳补偿点分析[J].计算机测量与控制,2021,29(2):207-211.
作者姓名:王光增  华献宏  柴志华  张照锋  金东红  李灿灿  徐成浩
作者单位:国网浙江浦江县供电有限公司,浙江浦江322200;国网浙江浦江县供电有限公司,浙江浦江322200;国网浙江浦江县供电有限公司,浙江浦江322200;浦江光远电力建设有限公司,浙江浦江322200;浦江光远电力建设有限公司,浙江浦江322200;浦江光远电力建设有限公司,浙江浦江322200;浦江光远电力建设有限公司,浙江浦江322200
摘    要:针对配电网中由于谐波等因素影响,导致无功功率增加的问题,提出了新型的无功功率最佳补偿点查找方案;该方案构设出包括设备层、节点层、通信网络层、计算机管理层和远程管理中心的补偿点分析系统,能够以系统化的架构在本地或者远程对电力节点进行分析,并设计出一套谐波控制系统,能够通过在线、实时检测谐波发生点来选择功率补偿点;并在传统的蚁群算法中融合粒子群算法,解决了常规技术中难以实现全局最优解的技术弊端;通过200次的迭代计算,试验表明,该研究的方法在达到预定周期时,能够通过最佳化地更新全局位置搜索到局部的最优解,收敛速度快,收敛时间约为60s,通过对比试验,本研究的方案具有一定的技术进步性。

关 键 词:配电网  无功功率  补偿点  蚁群算法  粒子群算法
收稿时间:2020/4/14 0:00:00
修稿时间:2020/5/13 0:00:00

Analysis of optimal compensation point for reactive power in distribution network based on improved ant colony algorithm
Wang Guangzeng,Hua Xianhong,Chai Zhihua,Zhang Zhaofeng,Jin Donghong,Li Cancan,Xu Chenghao.Analysis of optimal compensation point for reactive power in distribution network based on improved ant colony algorithm[J].Computer Measurement & Control,2021,29(2):207-211.
Authors:Wang Guangzeng  Hua Xianhong  Chai Zhihua  Zhang Zhaofeng  Jin Donghong  Li Cancan  Xu Chenghao
Affiliation:(State Grid Zhejiang Pujiang County Power Supply Co.,Ltd.,Pujiang 322200,China;Pujiang Guangyuan Electric Power Construction Co.,Ltd.,Pujiang 322200,China)
Abstract:Aiming at the problem of the increase of reactive power due to the influence of harmonics and other factors in the distribution network, a new type of reactive power optimal compensation point search scheme is proposed. The scheme constructs a compensation point analysis system including equipment layer, node layer, communication network layer, computer management layer and remote management center. It can analyze power nodes locally or remotely with a systematic architecture and design a set The harmonic control system can select the power compensation point through online and real-time detection of the harmonic generation point. And the particle swarm optimization algorithm is integrated in the traditional ant colony algorithm, which solves the technical shortcomings that it is difficult to achieve the global optimal solution in the conventional technology. Through 200 iteration calculations, the experiment shows that the method of this study can find the local optimal solution by optimally updating the global position when the predetermined period is reached. The project of this research has certain technological advancement.
Keywords:Distribution network  reactive power  compensation point  ant colony algorithm  particle swarm algorithm
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