Research on a Two-stage Optimization Algorithm for Multi-objective Reactive Power Optimization of Distribution Network

被引:0
|
作者
Gao, Fei [1 ]
Zhang, Yu [1 ]
Li, Jianfang [1 ]
Feng, Xueping [1 ]
Song, Xiaohui [1 ]
机构
[1] CEPRI, Beijing, Peoples R China
关键词
multi-objective; reactive power optimization; two stage; preferred area; improved dominance relation;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper proposes a two-stage optimization algorithm for multi-objective reactive power optimization of distribution network. In the first stage, an approximate Pareto solution set is obtained using traditional multi-objective optimi-zation algorithm. Then the preferred area for searching is calculated with the preference information of Decision Maker (DM) and the approximate Pareto solutions. In the second stage, an improved dominance relation is proposed to guide the particles of multi objective particle swarm optimization(MOPSO) to focus on a deep searching in preferred area, with a high calculation efficiency. The case in IEEE 33-node system verifies that compared with the traditional multi-objective reactive power optimization, the method proposed in this paper has a large improvement in generation distance(GD), spacing(SP), error ration(ER) and reduce the optimization time.
引用
收藏
页码:626 / 631
页数:6
相关论文
共 50 条
  • [1] Multi-objective reactive power and voltage optimization for distribution network
    Zheng, Weimin
    Xu, Yu
    Zhou, Yuyong
    Sun, Ke
    Chen, Xiaogang
    Wang, Gang
    Zhang, Luliang
    Chen, Jiajia
    [J]. 2018 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON), 2018, : 2216 - 2221
  • [2] A two-stage multi-objective evolutionary algorithm for large-scale multi-objective optimization
    Liu, Wei
    Chen, Li
    Hao, Xingxing
    Xie, Fei
    Nan, Haiyang
    Zhai, Honghao
    Yang, Jiyao
    [J]. 2022 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2022,
  • [3] A simple two-stage evolutionary algorithm for constrained multi-objective optimization
    Ming, Fei
    Gong, Wenyin
    Zhen, Huixiang
    Li, Shuijia
    Wang, Ling
    Liao, Zuowen
    [J]. KNOWLEDGE-BASED SYSTEMS, 2021, 228
  • [4] Multi-Objective Reactive Power Optimization of Distribution Network with Distributed Generation
    Zhao, Hui
    Luan, Zhaowen
    Guo, Sixin
    Han, Chunpeng
    [J]. 2016 ASIA CONFERENCE ON POWER AND ELECTRICAL ENGINEERING (ACPEE 2016), 2016, 55
  • [5] Two-stage multi-objective robust optimization of voltage/var for unbalanced active distribution network
    Fu, Yang
    Wu, Jie
    Su, Xiangjing
    Tian, Shuxin
    Mi, Yang
    Li, Haiyu
    Geng, Fuhai
    [J]. Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2024, 44 (05): : 79 - 87
  • [6] Multi-objective Oriented Search Algorithm for Multi-objective Reactive Power Optimization
    Zhang, Xuexia
    Chen, Weirong
    [J]. EMERGING INTELLIGENT COMPUTING TECHNOLOGY AND APPLICATIONS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE, 2009, 5755 : 232 - 241
  • [7] Reactive power optimization for distribution network system with wind power based on improved multi-objective particle swarm optimization algorithm
    Kuang, Honghai
    Su, Fuqing
    Chang, Yurui
    Kai, Wang
    He, Zhiyi
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2022, 213
  • [8] Multi-Objective Optimization for Distribution Network Reconfiguration With Reactive Power Optimization of New Energy and EVs
    Wu, Renbo
    Liu, Shuqin
    [J]. IEEE ACCESS, 2023, 11 : 10664 - 10674
  • [9] Research On Multi-Objective Reactive Power Optimization Based on Modified Particle Swarm Optimization Algorithm
    Wu, Jianhua
    Li, Nan
    He, Lihong
    Yin, Bin
    Guo, Jianhua
    Liu, Yaqiong
    [J]. 2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5, 2010, : 477 - 480
  • [10] Multimodal and multi-objective optimization algorithm based on two-stage search framework
    Zhang, Jia-Xing
    Chu, Xiao-Kai
    Yang, Feng
    Qu, Jun-Feng
    Wang, Shen-Wen
    [J]. APPLIED INTELLIGENCE, 2022, 52 (11) : 12470 - 12496