Metaheuristic Approaches for Hydropower System Scheduling

This paper deals with the short-term scheduling problem of hydropower systems. The objective is to meet the daily energy demand in an economic and safe way. The individuality of the generating units and the nonlinearity of their efficiency curves are taken into account. The mathematical model is for...

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Main Authors: Ieda G. Hidalgo, Regiane S. de Barros, Jéssica P. T. Fernandes, João Paulo F. Estrócio, Paulo B. Correia
Format: Article
Language:English
Published: Wiley 2015-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2015/701851
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author Ieda G. Hidalgo
Regiane S. de Barros
Jéssica P. T. Fernandes
João Paulo F. Estrócio
Paulo B. Correia
author_facet Ieda G. Hidalgo
Regiane S. de Barros
Jéssica P. T. Fernandes
João Paulo F. Estrócio
Paulo B. Correia
author_sort Ieda G. Hidalgo
collection DOAJ
description This paper deals with the short-term scheduling problem of hydropower systems. The objective is to meet the daily energy demand in an economic and safe way. The individuality of the generating units and the nonlinearity of their efficiency curves are taken into account. The mathematical model is formulated as a dynamic, mixed integer, nonlinear, nonconvex, combinatorial, and multiobjective optimization problem. We propose two solution methods using metaheuristic approaches. They combine Genetic Algorithm with Strength Pareto Evolutionary Algorithm and Ant Colony Optimization. Both approaches are divided into two phases. In the first one, to maximize the plant’s net generation, the problem is solved for each hour of the day (static dispatch). In the second phase, to minimize the units’ switching on-off, the day is considered as a whole (dynamic dispatch). The proposed methodology is applied to two Brazilian hydroelectric plants, in cascade, that belong to the national interconnected system. The nondominated solutions from both approaches are presented. All of them meet demand respecting the physical, electrical, and hydraulic constraints.
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institution Kabale University
issn 1110-757X
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language English
publishDate 2015-01-01
publisher Wiley
record_format Article
series Journal of Applied Mathematics
spelling doaj-art-908004b2891b413299acb5ccf48ee4662025-02-03T05:45:22ZengWileyJournal of Applied Mathematics1110-757X1687-00422015-01-01201510.1155/2015/701851701851Metaheuristic Approaches for Hydropower System SchedulingIeda G. Hidalgo0Regiane S. de Barros1Jéssica P. T. Fernandes2João Paulo F. Estrócio3Paulo B. Correia4Faculty of Technology, State University of Campinas (Unicamp), 13.484-332 Limeira, SP, BrazilFaculty of Mechanical Engineering, State University of Campinas (Unicamp), 13.083-860 Campinas, SP, BrazilFaculty of Mechanical Engineering, State University of Campinas (Unicamp), 13.083-860 Campinas, SP, BrazilCia Energética de São Paulo (CESP), 04.447-011 São Paulo, SP, BrazilFaculty of Mechanical Engineering, State University of Campinas (Unicamp), 13.083-860 Campinas, SP, BrazilThis paper deals with the short-term scheduling problem of hydropower systems. The objective is to meet the daily energy demand in an economic and safe way. The individuality of the generating units and the nonlinearity of their efficiency curves are taken into account. The mathematical model is formulated as a dynamic, mixed integer, nonlinear, nonconvex, combinatorial, and multiobjective optimization problem. We propose two solution methods using metaheuristic approaches. They combine Genetic Algorithm with Strength Pareto Evolutionary Algorithm and Ant Colony Optimization. Both approaches are divided into two phases. In the first one, to maximize the plant’s net generation, the problem is solved for each hour of the day (static dispatch). In the second phase, to minimize the units’ switching on-off, the day is considered as a whole (dynamic dispatch). The proposed methodology is applied to two Brazilian hydroelectric plants, in cascade, that belong to the national interconnected system. The nondominated solutions from both approaches are presented. All of them meet demand respecting the physical, electrical, and hydraulic constraints.http://dx.doi.org/10.1155/2015/701851
spellingShingle Ieda G. Hidalgo
Regiane S. de Barros
Jéssica P. T. Fernandes
João Paulo F. Estrócio
Paulo B. Correia
Metaheuristic Approaches for Hydropower System Scheduling
Journal of Applied Mathematics
title Metaheuristic Approaches for Hydropower System Scheduling
title_full Metaheuristic Approaches for Hydropower System Scheduling
title_fullStr Metaheuristic Approaches for Hydropower System Scheduling
title_full_unstemmed Metaheuristic Approaches for Hydropower System Scheduling
title_short Metaheuristic Approaches for Hydropower System Scheduling
title_sort metaheuristic approaches for hydropower system scheduling
url http://dx.doi.org/10.1155/2015/701851
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