A multiobjctive Solution of Gravitational Search Algorithm for Benchmark Functions and Placement of SVC
In this paper، a multi-objective version of Gravitational search algorithm (GSA) is proposed which is based on optimal Pareto concepts for solving the multi objective problems. To show the effectiveness of the proposed algorithm، it is tested on different benchmark functions and an engineering problem known as placement of Static Var Compensators (SVC) for VAr planning in a large-scale power system. Taking advantages of the SVCs depends greatly on how these devices are placed in the power system، namely on their location and size. The VAr planning problem is formulated as a multi-objective optimization problem، which represent minimizing voltage deviation، losses and the cost of installation resulting in the maximum system VAr margin. The results obtained show the effectiveness of the proposed algorithm.
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