Evolutionary approach for solving economic dispatch in power system

B. N.S. Rahimullah, E. Ramlan, T. K.A. Rahman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

The problem or economic dispatch has been forwarded and solved by numerous methods. This paper provides alternative methods to solve the problem. In this paper, evolutionary programming (EP) is used as one of the techniques to solve the problem of economic dispatch in power system. Log-normal Gaussian mutation or commonly known as metaEP, is used as the essential operator of generating the sufficient power in order to fulfill demand at a minimum cost. The proposed EP method provides a solution consisting suitable power generated of each generator and meeting the demand with minimum total cost. The study also investigates the differences of using standard EP against metaEP to solve the same problem. The comparisons between the both methods and GA solution to solve the problems are also highlighted in this paper. The study findings show that both EP methods perform better compared to GA in solving the economic dispatch problem. However, metaEP seems to be more robust in solving problems in a bigger search space compared to the original EP. The study conducted for the comparison is based on the solution and performance of each algorithm in solving the problem.

Original languageEnglish
Title of host publicationNational Power Engineering Conference, PECon 2003 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages32-36
Number of pages5
ISBN (Electronic)0780382080, 9780780382084
DOIs
Publication statusPublished (in print/issue) - 1 Jan 2003
EventNational Power Engineering Conference, PECon 2003 - Bangi, Malaysia
Duration: 15 Dec 200316 Dec 2003

Conference

ConferenceNational Power Engineering Conference, PECon 2003
Country/TerritoryMalaysia
CityBangi
Period15/12/0316/12/03

Keywords

  • Cost function
  • Equations
  • Genetic algorithms
  • Genetic mutations
  • Genetic programming
  • Power generation
  • Power generation economics
  • Power system economics
  • Power systems
  • Propagation losses

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