A REDUCTION OF REAL POWER LOSS BY ENRICHED GENETIC ALGORITHM

In this paper Enriched Genetic Algorithm (EGA) is proposed to solve the optimal reactive power problem. In order to overcome the drawbacks of standard genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, some improved mechanisms based on non-linear ranking selection, competition and selection among several crossover offspring and adaptive change of mutation scaling are adopted in the genetic algorithm, and dynamical parameters are adopted in PSO. The new population is produced through three approaches to improve the global optimization performance. Proposed algorithm has been tested in standard IEEE 57 bus test system and simulation results reveal the better performance of the proposed algorithm in reducing the real power loss.