Factual power loss reduction by dynamic membrane evolutionary algorithm

Abstract

This paper presents a dynamic membrane evolutionary algorithm (DMEA) that has been applied to solve optimal reactive power problems. The 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, the integrated membrane is alienated into the elementary membranes 1, 2, _, m. In particle swarm optimization (PSO) C₁ and C₂ (acceleration constants) are vital parameters to augment the exploration ability of PSO in the period of the optimization procedure. In this work, Gaussian probability distribution is initiated to engender the accelerating coefficients of PSO. The proposed DMEA has been tested in standard IEEE 14, 30, 57, 118, and 300 bus test systems and simulation results show the projected algorithm reduced the real power loss comprehensively.