Keywords
Particle swarm optimization
OTS
Tuning
How to Cite
Abstract
A real-time training simulator for power system operators is an extremely important tool for familiarizing operators with the electrical and dynamic behavior of power systems based on mathematical models of their constituent elements in response to various disturbances. This research involves the development of a computer tool for tuning the parameters of dynamic models of generating units using genetic algorithms and particle swarm optimization. Tuning is performed for the models of a thermal and a hydroelectric power plant, and the efficiency of each technique is compared based on the root mean square error (RMSE) performance metric and simulation times. Based on the results obtained from the tuning techniques, it is observed that genetic algorithms achieve a lower value for the performance metric, while particle swarm optimization offers less accuracy but requires shorter simulation times.
References
V. Kola, A. Bose y P. Anderson, “Power Plant Models for Operator Training Simulators,” en IEEE Transactions on Power Systems, 1989, pp. 559-565.
J. Camarillo, A. Saavedra y C. Ramos, "Recomendaciones para Seleccionar Índices para la Validación de Modelos," TecnoLógicas, vol. 1, pp. 109-122, octubre 2013.
A. Arias y A. Zapata, "Evaluación de metodologías de sintonización para controladores PI en microrredes eléctricas," Tesis de pregrado, Universidad de La Salle, 2020.
B. Acevedo, J. Fonseca y J. Gómez, “Desarrollo de una herramienta en MATLAB para Sintonización de Controladores PID utilizando algoritmos genéticos basado en técnicas de optimización multiobjetivo,” SENA, vol. 1, pp. 81-102.
S. Sivanandam y S. Deepa, Introduction to Genetic Algorithms. Berlin: Springer, 2008.
M. Gestal, D. Rivero, J. Rabuñal, J. Dorado y A. Pazos, “Algoritmos Genéticos. Introducción a los Algoritmos Genéticos y la Programación Genética,” Universidad da Coruña: Servizo de Publicacións, España, 2010.
R. Lluiyac, "Sintonización de un controlador PID usando Particle Swarm Optimization para el AGC de un Sistema Eléctrico Multiárea," Tesis de Máster, Universidad de Sevilla, 2014.
A. Engelbrecht, Computational Intelligence: An Introduction. Chichester: John Wiley & Sons Inc, 2007.
M. Clerc, Particle Swarm Optimization. Londres: Wiley-ITSE, 2005.
A. Harb, L. Mili, A. Nayfeh y C. Chin, “On the Effect of the Machine Saturation on SSR in Power System,” en Electric Machines and Power Systems, 2000, pp. 1019-1035.
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Copyright (c) 2024 W. Alguera, W. Berríos, V. Ibarra, J. Vargas, J. Martínez (Autor/a)