Self-adaptive evolutionary programming and its application to multi-objective optimal load flow. Part Two: Self-adaptive evolutionary programming solution of multi-objective optimal load flow

被引:0
|
作者
Shi, Libao [1 ]
Xu, Guoyu [1 ]
机构
[1] Chongqing Univ, Chongqing, China
关键词
Computer simulation - Electric load flow - Mathematical models - Nonlinear programming - Numerical analysis;
D O I
暂无
中图分类号
学科分类号
摘要
Multi-objective optimal load flow is an extremely complicated non-linear planning problem. The paper presents a new algorithm for the solution of multi-objective optimal load flow problem. Some related technical problems, such as optimized model, genetic operation etc. are investigated. The proposed method is applied to an IEEE-30 bus system. The numerical results of the simulation demonstrate that this method can bring about some good results on dealing with constraints flexibly, reducing the computational requirements and preventing the search from being in local optimum or converging with difficulty near the global optimum.
引用
收藏
页码:33 / 36
相关论文
共 50 条
  • [1] Self-adaptive evolutionary programming and its application to multi-objective optimal load flow: Part two self-adaptive evolutionary programming solution of multi-objective optimal load flow: Part two self-adaptive evolutionary programming solution of multi-objective optimal load flow
    Shi, Libao
    Xu, Guovu
    Dianli Xitong Zidonghue/Automation of Electric Power Systems, 2000, 24 (08): : 35 - 36
  • [2] Self-adaptive evolutionary programming and its application to multi-objective optimal operation of power systems
    Shi, LB
    Xu, GY
    ELECTRIC POWER SYSTEMS RESEARCH, 2001, 57 (03) : 181 - 187
  • [3] Self-adaptive evolutionary programming algorithm of multi-objective fuzzy optimal operation
    Shi, L.B.
    Xu, G.Y.
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2001, 21 (03): : 53 - 57
  • [4] Self-Adaptive Mechanism for Multi-objective Evolutionary Algorithms
    Zeng, Fanchao
    Low, Malcolm Yoke Hean
    Decraene, James
    Zhou, Suiping
    Cai, Wentong
    INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS (IMECS 2010), VOLS I-III, 2010, : 7 - 12
  • [5] Multi-objective Optimisation by Self-adaptive Evolutionary Algorithm
    Oliver, John M.
    Kipouros, Timoleon
    Savill, A. Mark
    EVOLVE - A BRIDGE BETWEEN PROBABILITY, SET ORIENTED NUMERICS AND EVOLUTIONARY COMPUTATION VII, 2017, 662 : 111 - 134
  • [6] A self-adaptive evolutionary algorithm for multi-objective optimization
    Cao, Ruifen
    Li, Guoli
    Wu, Yican
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE, 2007, 4682 : 553 - 564
  • [7] Self-Adaptive Multi-Objective Evolutionary Algorithm for Molecular Design
    Kannas, Christos C.
    Pattichis, Constantinos S.
    2017 IEEE 30TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 2017, : 162 - 166
  • [8] Self-Adaptive Multi-objective Differential Evolutionary Algorithm based on Decomposition
    Chen, Lingyu
    Wang, Beizhan
    Liu, Weigiang
    Wang, Jiajun
    2016 11TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE), 2016, : 610 - 616
  • [9] Multi-objective evolutionary algorithm based on self-adaptive differential evolution
    Bi, Xiao-Jun
    Xiao, Jing
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2011, 17 (12): : 2660 - 2665
  • [10] A Self-Adaptive Evolutionary Multi-Task Based Constrained Multi-Objective Evolutionary Algorithm
    Qiao, Kangjia
    Liang, Jing
    Yu, Kunjie
    Wang, Minghui
    Qu, Boyang
    Yue, Caitong
    Guo, Yinan
    IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, 2023, 7 (04): : 1098 - 1112