Non Dominated Sorting Dragonfly Algorithm For Multi-Objectives Optimal Power Flow

Sundaram B. Pandya, H. Jariwala
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引用次数: 1

Abstract

This paper shows the single and multi-objective edition of the newly projected Dragonfly Algorithm (DA) known as Non-Dominated Sorting Dragonfly Algorithm (NSDA) for the solution of multi-objectives optimal power flow problem. This projected NSDA algorithm is working in such a manner that, it primary finds all non-dominated Pareto optimal results at last end iteration number. Then crowding distance approach and fuzzy decision making technique are applied for finding the best compromise solutions among all the Pareto fronts in the dominated regions of multi-objective search spaces. The results are validated through the IEEE 30-bus test system and compared with the other latest optimization algorithms.
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多目标最优潮流的非支配排序蜻蜓算法
本文给出了求解多目标最优潮流问题的非支配排序蜻蜓算法(NSDA)的单目标和多目标版本。该投影NSDA算法的工作方式是,在最后一个迭代次数结束时,它主要找到所有非支配的Pareto最优结果。然后利用拥挤距离法和模糊决策技术,在多目标搜索空间的优势区域中寻找所有Pareto前沿的最佳妥协解。通过IEEE 30总线测试系统验证了结果,并与其他最新优化算法进行了比较。
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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