Title: Mutation-based PSO techniques for optimal location and parameter settings of STATCOM under generator contingency

Authors: Jayachitra Selvaraj; Amin Salih Mohammed

Addresses: Department of Computer Engineering, College of Engineering and Computer Science, Lebanese French University, Erbil, Iraq ' Department of Computer Engineering, College of Engineering and Computer Science, Lebanese French University, Erbil, Iraq

Abstract: This article addresses the efficient contribution of particle swarm optimisation (PSO) and its variants such as constrained factor-PSO (CF-PSO), Cauchy mutation-CFPSO (CM-CFPSO) and Gaussian mutation-CFPSO (GM-CFPSO) algorithm to choose suitable placement and rating of static synchronous compensator (STATCOM) based on novel index called unification index (UI). Minimisation of real and reactive power loss, voltage deviation reduction and augmentation of voltage stability are considered for this research work. UI is computed with respect to normal and generator contingency condition. Based on the index value, the ranking of severe lines is made. The purpose of embedding PSO with mutation is to expand the search space particularly to avoid being trapped in local optima. IEEE 30 bus system is chosen to assess the potency of the propound method using MATLAB working platform against generator bus contingency with and without STATCOM. This proposed approach yields promising result and their performances were presented and compared with other methodologies.

Keywords: generator contingency; mutation; particle swarm optimisation; PSO; static synchronous compensator; STATCOM; unification index.

DOI: 10.1504/IJISC.2020.104827

International Journal of Intelligence and Sustainable Computing, 2020 Vol.1 No.1, pp.53 - 68

Received: 07 Dec 2018
Accepted: 20 Feb 2019
Published online: 03 Feb 2020 *