Abstract
The Hydro–thermal Power Scheduling Problem is a dynamic multiobjective optimization problem which arises in the context of power generation systems. In this problem, a certain number of hydroelectric and thermal generating units must satisfy the total power demand in a combined effort. The planning horizon is divided into subintervals, each with its own load demands. Thus, the problem consists in allocating an optimal amount of power to each generating unit at each time subinterval in such a way that the fuel cost and pollutant emission are simultaneously minimized, and all the operational constraints are satisfied. In this chapter we propose a Multiobjective Particle Swarm Optimization algorithm enhanced with the crowding distance to deal with the Hydro–thermal Power Scheduling Problem. As far as we know, this is the first time that a swarm–intelligence–based algorithm is used to solve this problem. The computational experiment shows the potential of the proposed metaheuristic for the problem approached.
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Acknowledgements
The first author would like to thank the Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONAHCYT) of Mexico for supporting this research through its postdoctoral program.
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Castillo-García, N., Cruz–Reyes, L., Carlos Hernández Marín, J., Hernández-Hernández, P. (2024). Multiobjective Particle Swarm Optimization for the Hydro–Thermal Power Scheduling Problem. In: Castillo, O., Melin, P. (eds) New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics. Studies in Computational Intelligence, vol 1149. Springer, Cham. https://doi.org/10.1007/978-3-031-55684-5_12
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DOI: https://doi.org/10.1007/978-3-031-55684-5_12
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