Vector evaluated adaptive immune particle swarm optimization algorithm for multi-objective reactive power optimization

Juan Li, Lin Yang, Jinlong Liu, Delong Yang, Chen Zhang
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引用次数: 6

Abstract

To solve the power system multi-objective reactive power optimization problem better, the shortcomings of the current multi-objective reactive power optimization were analyzed. The vector evaluated adaptive immune particle swarm optimization (VEAIPSO) algorithm based on evaluation vector is applied to multi-objective reactive power optimization in this paper which provides an effective method for solving the problem. Some conventional running models of reactive power optimization were analyzed. The improvement of the system static voltage stability margin was used as the one of the optimized objectives, and the minimum Jacobian matrix eigenvalue of the convergence trend was used as a voltage static stability scale. The multi-objective reactive power optimization model was established, its objective function contains reducing network power loss, improving the load node voltage level and increasing the static voltage stability margin. The operation simulation in this paper was done by simulation software MATLAB.
矢量评估自适应免疫粒子群算法用于多目标无功优化
为了更好地解决电力系统多目标无功优化问题,分析了当前多目标无功优化存在的不足。将基于评价向量的矢量评价自适应免疫粒子群优化(VEAIPSO)算法应用于多目标无功优化,为解决多目标无功优化问题提供了一种有效的方法。分析了几种常用的无功优化运行模型。以提高系统静态电压稳定裕度为优化目标之一,以收敛趋势的最小雅可比矩阵特征值为电压静态稳定尺度。建立了多目标无功优化模型,其目标函数包括降低电网损耗、提高负荷节点电压水平和增加静态电压稳定裕度。本文的运行仿真是通过仿真软件MATLAB进行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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