Non dominated sorting based multi objective GSA for solving optimal power flow problems

A. Bhowmik, A. Chakraborty
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引用次数: 0

Abstract

This paper presents the solution of different optimal power flow (OPF) problems using non dominated sorting based multi objective gravitational search algorithm (NSMOGSA). OPF problem is formulated as a non-linear constrained optimization problem where different objectives and various constraints have been considered into the formulation. To show the effectiveness of the proposed algorithm, it has been tested on a standard IEEE 30-bus system with two different individual objectives that reflect active power loss minimization and fuel cost minimization with valve point loading effect. The performance of NSMOGSA is compared with the results found by other meta-heuristic techniques reported in the recent literature. Numerical results demonstrate the tangible superiority of the proposed method in achieving the optimum OPF solution.
基于非支配排序的多目标GSA求解最优潮流问题
提出了基于非支配排序的多目标引力搜索算法(NSMOGSA)求解各种最优潮流问题的方法。将OPF问题表述为一个考虑了不同目标和约束条件的非线性约束优化问题。为了证明该算法的有效性,在一个标准的IEEE 30总线系统上进行了测试,该系统具有两个不同的独立目标,反映了具有阀点负载效应的有功功率损耗最小化和燃料成本最小化。将NSMOGSA的性能与最近文献中报道的其他元启发式技术的结果进行了比较。数值结果表明,该方法在求解最优OPF问题上具有明显的优越性。
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