加权减载的多目标遗传算法

M. T. Hagh, Sarah Galvani
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引用次数: 18

摘要

应急条件下的减载是缓解输电线路过载的有效方法。在这种情况下,考虑到负荷的重要性,使总减载最小化具有重要意义。这个问题需要同时优化两个或多个相互冲突的目标,例如最小化总减载,最小化输电线路过载和最小化电压违例。这些目标是相互冲突的,因为其中一个目标的改善会导致另一个目标的恶化。采用改进的非支配排序遗传算法(NSGA-II)作为一种有效的优化工具,求解突发条件下的最小加权减载问题。探讨了输电线路过载与减载量的关系。以IEEE 14总线测试系统为例,对测试结果进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multi objective genetic algorithm for weighted load shedding
Load shedding during contingency conditions is an efficient solution to alleviate transmission lines over loadings. Minimization of total load shedding considering loads importance has great significance in these situations. This problem requires simultaneous optimization of two or more conflicting objectives, such as minimization of the total load shedding, minimization of transmission lines over loadings and voltage violations minimization. The objectives are in conflict since the improvement of one of them leads to the deterioration of another. A modified version of Non-Dominated Sorting Genetic Algorithm (NSGA-II) is used as an effective optimization tools for solving the minimum weighted load shedding problem during contingency conditions. Also relation between transmission lines overloading and amount of load shedding is surveyed. IEEE 14 bus test system is used as a study case and results are discussed.
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