Open AccessFactual power loss reduction by dynamic membrane evolutionary algorithm
Author(s) -
Lenin Kanagabasai
Publication year - 2021
Publication title -
international journal of advances in applied sciences
Language(s) - English
Resource type - Journals
eISSN - 2722-2594
pISSN - 2252-8814
DOI - 10.11591/ijaas.v10.i2.pp99-106
Subject(s) - particle swarm optimization , membrane , algorithm , evolutionary algorithm , reduction (mathematics) , gaussian , differential evolution , mathematical optimization , ac power , membrane computing , power (physics) , mathematics , computer science , control theory (sociology) , artificial intelligence , physics , chemistry , biochemistry , geometry , control (management) , quantum mechanics
This paper presents Dynamic Membrane Evolutionary Algorithm (DMEA) has been applied to solve optimal reactive power problem.Proposed methodology merges the fusion and division rules of P systems with active membranes and with adaptive differential evolution (ADE), particle swarm optimization (PSO) exploration stratagem. All elementary membranes are amalgamated into one membrane in the computing procedure. Furthermore, integrated membrane are alienated into the elementary membranes 1, 2,_ m. In particle swarm optimization (PSO) , (acceleration constants) are vital parameters to augment the explorationability of PSO in the period ofthe optimization procedure.In this work, Gaussian probability distribution isinitiated to engenderthe accelerating coefficients of PSO.Proposed Dynamic Membrane Evolutionary Algorithm (DMEA) 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.