[1]龚雪娇,郝东光,朱瑞金.基于改进NSDE算法的有源配电网多目标无功优化[J].电力电容器与无功补偿,2020,41(5):54-59,66.[doi:10.14044/j.1674-1757.pcrpc.2020.05.010]
 GONG Xuejiao,HAO Dongguang,ZHU Ruijin.Multi?objective Reactive Power Optimization of Reactive Distribution Network Based on the Improved NSDE Algorithm[J].Power Capacitors & Reactive Power Compensation,2020,41(5):54-59,66.[doi:10.14044/j.1674-1757.pcrpc.2020.05.010]
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基于改进NSDE算法的有源配电网多目标无功优化()
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《电力电容器与无功补偿》[ISSN:1674-1757/CN:61-1468/TM]

卷:
41卷
期数:
2020年第5期
页码:
54-59,66
栏目:
无功补偿与滤波
出版日期:
2020-10-30

文章信息/Info

Title:
Multi?objective Reactive Power Optimization of Reactive Distribution Network Based on the Improved NSDE Algorithm
作者:
龚雪娇1郝东光2朱瑞金1
1. 西藏农牧学院电气工程学院,西藏林芝860000; 2. 国网西藏电力有限公司培训中心,西藏林芝860000
Author(s):
GONG Xuejiao1HAO Dongguang2ZHU Ruijin1
1. School of Electrical Engineering,Tibet Agriculture & Animal Husbandry University, Tibet Nyingchi 860000,China;2. State Grid Tibet Electric Power Company Limited Training Center, Tibet Nyingchi 860000,China
关键词:
无功优化配电网分布式电源(DG)多目标优化差分进化
Keywords:
reactive power optimizationdistribution networkdistributed generation(DG)multi?objective optimizationdifferentialevolution
DOI:
10.14044/j.1674-1757.pcrpc.2020.05.010
文献标志码:
A
摘要:
针对同时降低系统有功网损和改善电压水平的含分布式电源(DG)配电网多目标无功优化 问题,提出一种改进非支配排序差分进化算法(I-NSDE)。在传统非支配排序差分进化算法 (NSDE)的基础上,引入反向学习初始化种群和自适应调整控制参数策略,以增加Pareto 最优解的 多样性和提高算法的全局收敛能力。以IEEE 33 节点配电系统为算例进行仿真分析,结果表明应 用所提算法能获得一组分布均匀的Pareto 最优解,同时具有较好的全局收敛性,可为电网运行人员 提供多样化的无功优化方案。
Abstract:
In view of multi?objective reactive power optimization issue of distribution network containing distributed power supply in both reducing active power network loss of system and simultaneously improving voltage level,a kind of non?dominated sorting differential evolution algorithm(I-NSDE)is proposed. Based on the non?dominated sorting differential evolution algorithm(NSDE),opposition based learning and self?adaption of control parameters is introduced to enhance the diversity and the global convergence of algorithm.TheIEEE33nodesystemdistributionsystemistakenascalculationexampleforsimulationanalysis. It is shown by the result that the proposed algorithm can maintain the diversity of Pareto?optimal solutions and,at the same time,has better global convergence,which can provide various reactive power optimization proposals for network operators.

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备注/Memo

备注/Memo:
收稿日期:2020?03?09
基金项目:西藏自治区自然科学基金(XZ2019ZRG-52(Z))。
作者简介: 龚雪娇(1988—),女,讲师,研究方向为农业电气化、自 动化技术。 郝东光(1967—),男,高级工程师,从事智能电网工作。 朱瑞金(1986—),男,讲师,研究方向为农业电气化、自 动化技术。
更新日期/Last Update: 2020-10-30