Abstract
This paper presents new solution approaches capable of finding optimal solutions for the Hydrothermal Scheduling Problem (HSP) in power generation planning. The problem has been proven to be NP-hard and no exact methods have been able to tackle it, for problem sizes of practical relevance. We explore three approaches. The first method is an iterative algorithm that has been successfully used previously to solve the thermal commitment problem. The two other methods are “Local Branching” and a hybridization of “Particle Swarm Optimization” with a general purpose solver. Computational experiments show that the iterative piecewise linear approximation method outperforms more elaborated approaches, indicating that recourse to matheuristics for solving this problem is not necessary.
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Acknowledgments
Financial support for this work was provided by the Portuguese Foundation for Science and Technology (under Project PTDC/EGEGES/099120/2008) through the “Programa Operacional Temático Factores de Competitividade (COMPETE)” of the “Quadro Comunitário de Apoio III”, partially funded by FEDER. The authors would like to thank Prof. Andrea Lodi for providing with the Local Branching code used in this work.
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Rahman, D.F., Viana, A., Pedroso, J.P. (2014). A MILP-Based Approach for Hydrothermal Scheduling. In: Helber, S., et al. Operations Research Proceedings 2012. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-00795-3_23
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DOI: https://doi.org/10.1007/978-3-319-00795-3_23
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