Improved Swarm Evolutionary-Programming Technique for Voltage Control in Power System

Abstract

Voltage decay is an important issue in the power system community. This can lead to a current increase, leading to temperature rise along the transmission line. Temperature rise can possibly cause an insulation failure, which can affect system stability. To avoid this phenomenon, compensation process can be employed with the installation of compensation devices. The required optimal sizing and location of the devices can be achieved using optimization technique. Evolutionary Programming (EP) technique can be one of the choices. However, the traditional EP technique may suffer inaccuracy and non-optimally. This study aims to develop an integrated computational intelligence technique termed as Swarm Evolutionary Programming (SEP) for voltage control study in power system. SEP proposes the combination of traditional EP and particle swarm optimization (PSO) technique, to improve the inaccuracy experienced in the traditional EP algorithm. The proposed technique has been validated on a chosen power system model; while comparative studies were conducted with respect to other techniques so as reveal its merits. Validation on the IEEE 24-Bus Reliability Test System (RTS) exhibits the superiority of the proposed SEP over the traditional EP in terms of voltage profile and loss minimization.