Open AccessHybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm for Solving Optimal Reactive Power Dispatch Problem
Author(s) -
K. Lenin
Publication year - 2021
Publication title -
journal of applied science, engineering, technology, and education
Language(s) - English
Resource type - Journals
ISSN - 2685-0591
DOI - 10.35877/454ri.asci31106
Subject(s) - particle swarm optimization , meta optimization , algorithm , mathematical optimization , genetic algorithm , metaheuristic , multi swarm optimization , minification , computer science , mathematics
In this work Hybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm (HGPSOS) has been done for solving the power dispatch problem. Genetic particle swarm optimization problem has been hybridized with Symbiotic organisms search (SOS) algorithm to solve the problem. Genetic particle swarm optimization algorithm is formed by combining the Particle swarm optimization algorithm (PSO) with genetic algorithm (GA). Symbiotic organisms search algorithm is based on the actions between two different organisms in the ecosystem- mutualism, commensalism and parasitism. Exploration process has been instigated capriciously and every organism specifies a solution with fitness value. Projected HGPSOS algorithm improves the quality of the search. Proposed HGPSOS algorithm is tested in IEEE 30, bus test system- power loss minimization, voltage deviation minimization and voltage stability enhancement has been attained.