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.
Bibliographical noteFunding Information:
Funding: This research was funded by FONDECYT grant number 1180685, CONICYT grant FB0008, University of Santiago USA 1899 - Vridei 091913VF-PAP.
Acknowledgments: This research was financed by Fondecyt Project 1180685 of the Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) of the Government of Chile. J.D. acknowledges thankfully the funding from the Advanced Center of Electrical and Electronic Engineering AC3E (CONICYT Basal FB0008) and from Fondo de Ayuda a la Investigacion (FAI), Universidad de los Andes.
© 2020 by the authors. 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/).
- Multimachine system
- Particle swarm optimization
- Power system
- Power system stabilizer