An Adaptive Particle Swarm Optimization Algorithm for Reactive Power Optimization in Power System

被引：3
|
作者：
Wu, Enqi [1 ]
Huang, Yue [2 ]
Li, Dan [3 ]
机构：
[1] North China Elect Power Univ, Sch Elect & Elect Engn, Baoding 071003, Peoples R China
[2] Shenyang Ligong Univ, Sch Informat Sci & Engn, Shenyang 110168, Peoples R China
[3] Northeast China Grid Co Ltd, Shenyang 110181, Peoples R China
来源：
2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2010年
关键词：
particle swarm optimization; adaptive mutation; reactive power optimization; DISPATCH;
D O I：
10.1109/WCICA.2010.5553988
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An adaptive particle swarm optimization(APSO) algorithm is presented to solve the problem that the standard particle swarm optimization(PSO) algorithm is easy to fall into a locally optimized point, where inertia weight is nonlinearly adjusted by using population diversity information. Velocity mutation factor and position interchange factor are both introduced. The APSO algorithm thus improves its solvability for global optimization to avoid effectively the precocious convergence. The new algorithm is applied to reactive power optimization of the standard IEEE-30-bus power system as instances, and the simulation results show the effectiveness and feasibility of APSO algorithm for the reactive power optimization. It is proved to be efficient and practical during the reactive power optimization.
引用
收藏
页码：3132 / 3137
页数：6
相关论文
共 50 条
  • [41] An improved particle swarm optimization algorithm for optimal reactive power dispatch
    Zhao, B
    Guo, CX
    Cao, YJ
    2005 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS, 1-3, 2005, : 272 - 279
  • [42] Cloud particle swarm algorithm improvement and application in reactive power optimization
    Su, Hongsheng
    Su, H. (shsen@163.com), 1600, Universitas Ahmad Dahlan (11): : 468 - 475
  • [43] Reactive power optimization of power system based on adaptive immune algorithm
    Lin, Ji-Keng
    Li, Hong-Lu
    Luo, Shan-Shan
    Zheng, Wei-Hong
    Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology, 2007, 40 (01): : 110 - 115
  • [44] Reactive Power Optimization of Electric Power System Incorporating Wind Power Based on Parallel Immune Particle Swarm Optimization
    Wang Tianhong
    Yuan Guili
    Zhu Lei
    Yu Tong
    26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC), 2014, : 1064 - 1068
  • [45] 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
    ELECTRIC POWER SYSTEMS RESEARCH, 2022, 213
  • [46] Reactive Power and Voltage Control Based on Improved Particle Swarm Optimization in Power System
    Wu, Xiuhua
    Piao, Zailin
    Liu, Yongliang
    Luo, Haiyan
    2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2010, : 5291 - 5295
  • [47] Reactive Power Optimization Based on Improved Particle Swarm Optimization Algorithm Considering Voltage Quality
    Zhu, Yingping
    Cai, Zexiang
    Zhang, Yongjun
    Song, Yongchao
    Yang, Yinguo
    MANUFACTURING SCIENCE AND TECHNOLOGY, PTS 1-8, 2012, 383-390 : 4721 - +
  • [48] Application of improved particle swarm optimization algorithm to multi-objective reactive power optimization
    Li, Xinbin
    Zhu, Qingjun
    Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, 2010, 25 (07): : 137 - 143
  • [49] Multi-Objective Reactive Power Optimization Based on Chaos Particle Swarm Optimization Algorithm
    He Xiao
    Pang Xia
    Zhu Da-rui
    Liu Chong-xin
    2013 2ND INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION AND MEASUREMENT, SENSOR NETWORK AND AUTOMATION (IMSNA), 2013, : 1014 - 1017
  • [50] Hybrid Fuzzy Particle Swarm Optimization Approach for Reactive Power Optimization
    Bhattacharyya, B.
    Goswami, S. K.
    Bansal, R. C.
    JOURNAL OF ELECTRICAL SYSTEMS, 2009, 5 (03)
12345