Amplified black hole algorithm for real power loss reduction

This work presents Amplified Black Hole Algorithm (ABHA) for solving optimal reactive power problem. In the projected approach ABHA, Gravitational Search Algorithm (GSA) is merged with Black Hole Algorithm (BHA). Power loss reduction is the key objective in the proposed work. The gravitational force...

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Bibliographic Details
Main Author: L. Kanagasabai
Format: Article
Language:English
Published: Ayandegan Institute of Higher Education, 2020-06-01
Series:International Journal of Research in Industrial Engineering
Subjects:
Online Access:http://www.riejournal.com/article_104074_0a8da23d68f6f313d436e3d1f47e48ba.pdf
Description
Summary:This work presents Amplified Black Hole Algorithm (ABHA) for solving optimal reactive power problem. In the projected approach ABHA, Gravitational Search Algorithm (GSA) is merged with Black Hole Algorithm (BHA). Power loss reduction is the key objective in the proposed work. The gravitational force between stars and the progression of stars to the black hole is attuned while explore the solution space. Assumption made that heavy objects are stars in a gravitational system, which become black holes and the exploitation of GSA is enhanced. During the progression of the projected algorithm, the radius of the black hole diminishes and more objects are included, which assist to stop early convergence. To improve the exploration and exploitation, stars gravity information has been utilized. During the progression of the projected algorithm, the radius of the black hole diminishes, and more objects are included, which assist to stop early convergence. Some of the most excellent objects turn out to be the black hole, affect other objects by their sturdy gravity. The other objects are alienated into two groups: Heavy agents and light agents. Proposed ABHA has been tested in standard IEEE 14, 30, 57, 118, 300 bus test systems and simulation results show the projected algorithm reduced the real power loss comprehensively.
ISSN:2783-1337
2717-2937