Implementation of particle swarm optimization (PSO) algorithm for tuning of power system stabilizers in multimachine electric power systems

Humberto Verdejo, Victor Pino, Wolfgang Kliemann, Cristhian Becker, José Delpiano

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). The application of artificial intelligence-based techniques has covered a wide range of applications related to electric power systems (EPS). Particularly, a metaheuristic technique known as Particle Swarm Optimization (PSO) has been chosen for the tuning of parameters for Power System Stabilizers (PSS) with success for relatively small systems. This article proposes a tuning methodology for PSSs based on the use of PSO that works for systems with ten or even more machines. Our new methodology was implemented using the source language of the commercial simulation software DigSilent PowerFactory. Therefore, it can be translated into current practice directly. Our methodology was applied to different test systems showing the effectiveness and potential of the proposed technique.
Original languageAmerican English
JournalEnergies
Volume13
Issue number8
DOIs
StatePublished - 1 Apr 2020

Keywords

  • Multimachine system
  • Particle swarm optimization
  • Power system
  • Power system stabilizer

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