Application of evolutionary multiobjective algorithms for solving the problem of energy dispatch in hydroelectric power plants

Carolina G. Marcelino*, Leonel M. Carvalho, Paulo E.M. Almeida, Elizabeth F. Wanner, Vladimiro Miranda

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication


The Brazilian population increase and the purchase power growth have resulted in a widespread use of electric home appliances. Consequently, the demand for electricity has been growing steadily in an average of 5% a year. In this country, electric demand is supplied predominantly by hydro power. Many of the power plants installed do not operate efficiently from water consumption point of view. Energy Dispatch is defined as the allocation of operational values to each turbine inside a power plant to meet some criteria defined by the power plant owner. In this context, an optimal scheduling criterion could be the provision of the greatest amount of electricity with the lowest possible water consumption, i.e. maximization of water use efficiency. Some power plant operators rely on “Normal Mode of Operation” (NMO) as Energy Dispatch criterion. This criterion consists in equally dividing power demand between available turbines regardless whether the allocation represents an efficient good operation point for each turbine. This work proposes a multiobjective approach to solve electric dispatch problem in which the objective functions considered are maximization of hydroelectric productivity function and minimization of the distance between NMO and “Optimized Control Mode” (OCM). Two well-known Multiobjective Evolutionary Algorithms are used to solve this problem. Practical results have shown water savings in the order of million m3/s. In addition, statistical inference has revealed that SPEA2 algorithm is more robust than NSGA-II algorithm to solve this problem.

Original languageEnglish
Title of host publicationEvolutionary multi-criterion optimization
Subtitle of host publication8th International Conference, EMO 2015, Guimarães, Portugal, March 29 --April 1, 2015. Proceedings, Part II
EditorsAntónio Gaspar-Cunha, Carlos Henggeler Antunes, Carlos Coello Coello
Place of PublicationCham (CH)
Number of pages15
ISBN (Electronic)978-3-31915891-4
Publication statusPublished - 2015
Event8th International Conference on Evolutionary Multi-Criterion Optimization - Guimarães, Portugal
Duration: 29 Mar 20151 Apr 2015

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference8th International Conference on Evolutionary Multi-Criterion Optimization
Abbreviated titleEMO 2015


  • energy efficiency
  • multiobjective optimization
  • SPEA2


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