An evolutionary approach to improve efficiency for solving the electric dispatch problem

Carolina G. Marcelino*, Elizabeth F. Wanner, Paulo E.M. Almeida

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

The consumption of electric energy for general supply of a country is increasing over the years. In Brazil, energy demand grows, on average, 5% per year and the power source is predominantly hydroelectric. Many of the power plants installed in Brazil do not operate efficiently, from the water consumption point of view. The normal mode of operation (NMO) equally divides power demand between existing generation units of a power plant, regardless if this individual demand represents or not a good operation point for each unit. The unit dispatch problem is defined as the attribution of operational values to each unit inside a power plant, given some criteria to be met. In this context, an optimal solution for the dispatch problem means production of electricity with minimal water consumption. This work proposes a multi-objective approach to solve the 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). The proposed approach is applied to a large hydroelectric plant operating in Brazil. Results indicate that it is possible to identify operating points near NMO that present productivity efficiency, saving in one month about 14.6 million m3 of water. Moreover, higher productivity can be achieved with smaller differences between NMO and OCM in lower power demands. Finally, it is worth to mention that the simplicity and the nature of the proposed approach indicate that it can be easily applied to studies of similar power plants, and thus can potentially be used to provide further economy on water consumption to larger extents of the hydroelectric production.

Original languageEnglish
Title of host publication2014 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) Proceedings
Place of PublicationPiscataway, NJ (US)
PublisherIEEE
Pages163-170
Number of pages8
ISBN (Electronic)978-1-4799-4510-8
DOIs
Publication statusPublished - 15 Jan 2015
Event2014 IEEE Symposium on Computational Intelligence for Engineering Solutions - Orlando, FL, United States
Duration: 9 Dec 201412 Dec 2014

Symposium

Symposium2014 IEEE Symposium on Computational Intelligence for Engineering Solutions
Abbreviated titleCIES 2014
CountryUnited States
CityOrlando, FL
Period9/12/1412/12/14

Keywords

  • multi-objective Optimization
  • NSGA-II
  • sustainability
  • water consumption

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