基于遗传算法的电力系统分段优化

A. Gavrilova, A. Khalyasmaa
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引用次数: 0

摘要

本文提出了利用遗传算法在考虑短路电流和损耗的情况下搜索电网最优配置的算法。所提出的方法可以有效地找到电网的最佳配置,迭代次数相对较少(明显少于对所有选项进行完全搜索)。分析了种群大小对计算模式电流和短路电流的运行次数的影响。测试方案采用IEEE标准方案,共设14个节点20个支路和118个节点186个支路。建模在MATLAB软件环境下进行,采用Matpower 6.0模式计算程序包进行建模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Power System Sectionalizing Optimization Using Genetic Algorithm
This paper proposes the algorithm for searching the optimal configuration of the power network, taking into account short-circuit currents and losses, using the genetic algorithm. The proposed method allows finding the optimal configuration of the power network effectively, for a relatively small number of iterations (significantly less than with a full search of all options). The influence of the population size on the number of runs to calculate the mode and short-circuit currents is analyzed. Standard IEEE schemes were used as test schemes, with 14 nodes, 20 branches and 118 nodes, 186 branches. The modeling was performed in the MATLAB software environment and the package of procedures for calculating the Matpower 6.0 mode.
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