Abstract

In this paper, Enhanced Gravitational Search (EGS) algorithm is proposed to solve the reactive power problem. Gravitational search algorithm (GSA) results are improved by using artificial bee colony algorithm (ABC). In GSA, solutions are fascinated towards each other by applying gravitational forces, which depending on the masses assigned to the solutions, to each other. The heaviest mass will move slower than other masses and pull others. Due to nature of gravitation, GSA may pass global minimum if some solutions stuck to local minimum. ABC updates the positions of the best solutions that have obtained from GSA, preventing the GSA from sticking to the local minimum by its strong penetrating capability. The proposed algorithm improves the performance of GSA in greater level. In order to evaluate the performance of the proposed EGS algorithm, it has been tested on IEEE 57,118 bus systems and compared to other standard algorithms.

Highlights

  • Various mathematical techniques have been adopted to solve this optimal reactive power dispatch problem

  • Gravitational search algorithm (GSA) performance is improved by using artificial bee colony algorithm (ABC)

  • At first Enhanced Gravitational Search (EGS) algorithm has been tested in standard IEEE-57 bus power system

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Summary

Introduction

Various mathematical techniques have been adopted to solve this optimal reactive power dispatch problem. These include the gradient method [1, 2], Newton method [3] and linear programming [4,5,6,7].The gradient and Newton methods suffer from the difficulty in handling inequality constraints. In this paper, Enhanced Gravitational Search (EGS) algorithm is proposed to solve the reactive power problem. ABC updates the positions of the best solutions that have obtained from GSA, preventing the GSA from sticking to the local minimum by its strong penetrating capability Both the exploration & exploitation ability of the proposed EGS algorithm has been enhanced. The performance of Enhanced Gravitational Search (EGS) algorithm has been evaluated in standard IEEE 57,118 bus test systems and the results analysis shows that our proposed approach outperforms all approaches investigated in this paper

Objective
Gravitational Search Algorithm
Artificial Bee Colony Algorithm
Simulation Results
Conclusion
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