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基于适应度空间距离评估选取的多目标粒子群算法在电网无功优化中的应用
引用本文:娄素华,吴耀武,熊信银.基于适应度空间距离评估选取的多目标粒子群算法在电网无功优化中的应用[J].电网技术,2007,31(19):41-46.
作者姓名:娄素华  吴耀武  熊信银
作者单位:电力安全与高效湖北省重点实验室(华中科技大学),湖北省,武汉市,430074
摘    要:提出了一种基于适应度空间距离评估选取最优解的多目标粒子群算法。该方法避免了目前多目标优化求解方法中权重选择的难题,保证了寻优方向的多向性,可以获得多目标优化问题的Pareto解集。将该算法应用于网损最小、静态电压稳定裕度最大为目标的多目标无功优化问题,算例表明在有效性和最优性等方面均有良好表现。

关 键 词:多目标  无功优化  适应度空间距离  评估向量选取  多目标粒子群算法
文章编号:1000-3673(2007)19-0041-06
修稿时间:2007-08-10

Application of Multi-Objective Particle Swarm Optimization Algorithm in Power System Reactive Power Optimization Based on Evaluation of Distance in Fitness Space
LOU Su-hua,WU Yao-wu,XIONG Xin-yin.Application of Multi-Objective Particle Swarm Optimization Algorithm in Power System Reactive Power Optimization Based on Evaluation of Distance in Fitness Space[J].Power System Technology,2007,31(19):41-46.
Authors:LOU Su-hua  WU Yao-wu  XIONG Xin-yin
Affiliation:Electric Power Security and High Efficiency Laboratory (Huazhong University of Science and Technology
Abstract:A multi-objective reactive power optimization algorithm, which chooses solution by means of evaluating distance of fitness space, is proposed. Using this algorithm, the puzzle of weight selection in the solution of current multi-objective optimization algorithms can be avoided and the multidirectional in the searching process can be ensured, thus the Pareto optimal solution set of multi-objective optimization problem can be achieved. Applying the proposed algorithm to multi-objective reactive power optimization and taking minimized network loss and maximized static voltage stability margin as objective function, the results show that the computation complexity is reduced, the convergence precision is improved.
Keywords:multi-objective  reactive power optimization  distance of fitness space  vector evaluated  multi-objective particle swarm optimization (MOPSO) algorithm
本文献已被 CNKI 维普 万方数据 等数据库收录!
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