ISBN
Formato digital
979-13-87837-54-9
Fecha de publicación
06-10-2025
Licencia
D. R. © Copyright 2025. Alma Y. Alanis, Jorge Galvez, Omar Avalos, Eduardo Méndez-Palos, Jorge D. Rios, Adriana Peña Perez-Negron & Gabriel Martínez Soltero
Todos los contenidos de esta obra se comparten bajo la licencia Creative Commons Atri-bución/Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0). Esto implica que no está autorizado el uso comercial de la obra original ni de las eventuales obras derivadas, las cuales deberán distribuirse bajo la misma licencia que rige la obra original. No obstante, se permite a terceros compartir el contenido siempre y cuando se reconozca debidamente la autoría y la publicación original en esta editorial.
Primitivo Díaz
Universidad de Guadalajara
0000-0002-2571-1525
Adrián González
Universidad de Guadalajara
0000-0001-9989-8241
Fernando A. Fausto
Universidad de Guadalajara
0000-0001-8400-4540
Orlando Salas
Universidad de Guadalajara
Acerca de
Efficient operation of power generation systems has become a significant issue in the research community, driven by the increasing demand for sustainable energy solutions and mitigating the environmental impact. Dynamic Economic Dispatch (DED) is a well-known optimization problem in power system operation. To accurately model DED, it is crucial to account for valve-point loading effects and ramp-rate limits. These factors make DED a non-linear, non-convex, and non-smooth problem, which is challenging to solve using traditional optimization techniques. In contrast, the Selfish Herd Optimizer (SHO) is a novel algorithm capable of finding optimal solutions to complex problems. In this work the SHO algorithm is used to optimize the DED problem, to evaluate the effectiveness of the proposed approach, the SHO algorithm was applied to three distinct power generation systems. The results obtained demonstrate the competitive performance of the SHO algorithm.
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