Dependability Evaluations of Parallel Differential Evolutionary Particle Swarm Optimization for Voltage and Reactive Power Control

Abstract

Various evolutionary computation techniques have been applied to voltage and reactive power control. High penetration of renewable energies and deregulation of power systems require to shorten an interval of the control. One of the practical solutions for this problem is applications of parallel and distributed computing with dependability, which is an ability to keep sustainable control against various faults. This paper presents dependability evaluations of parallel differential evolutionary particle swarm optimization (DEEPSO) for voltage and reactive power control. Simulation results with IEEE118 bus systems indicate high dependability of the method, compared with parallel PSO and parallel differential evolution.