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 contribution

8 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.

LanguageEnglish
Title of host publicationNational Power Engineering Conference, PECon 2003 - Proceedings
Pages32-36
Number of pages5
ISBN (Electronic)0780382080, 9780780382084
DOIs
Publication statusPublished - 1 Jan 2003
EventNational Power Engineering Conference, PECon 2003 - Bangi, Malaysia
Duration: 15 Dec 200316 Dec 2003

Conference

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

Fingerprint

Evolutionary algorithms
Economics
Costs

Keywords

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

Cite this

Rahimullah, B. N. S., Ramlan, E., & Rahman, T. K. A. (2003). Evolutionary approach for solving economic dispatch in power system. In National Power Engineering Conference, PECon 2003 - Proceedings (pp. 32-36). [1437412] https://doi.org/10.1109/PECON.2003.1437412
Rahimullah, B. N.S. ; Ramlan, E. ; Rahman, T. K.A. / Evolutionary approach for solving economic dispatch in power system. National Power Engineering Conference, PECon 2003 - Proceedings. 2003. pp. 32-36
@inproceedings{ba6e339b2e4b47098605f6524fa04120,
title = "Evolutionary approach for solving economic dispatch in power system",
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.",
keywords = "Cost function, Equations, Genetic algorithms, Genetic mutations, Genetic programming, Power generation, Power generation economics, Power system economics, Power systems, Propagation losses",
author = "Rahimullah, {B. N.S.} and E. Ramlan and Rahman, {T. K.A.}",
year = "2003",
month = "1",
day = "1",
doi = "10.1109/PECON.2003.1437412",
language = "English",
pages = "32--36",
booktitle = "National Power Engineering Conference, PECon 2003 - Proceedings",

}

Rahimullah, BNS, Ramlan, E & Rahman, TKA 2003, Evolutionary approach for solving economic dispatch in power system. in National Power Engineering Conference, PECon 2003 - Proceedings., 1437412, pp. 32-36, National Power Engineering Conference, PECon 2003, Bangi, Malaysia, 15/12/03. https://doi.org/10.1109/PECON.2003.1437412

Evolutionary approach for solving economic dispatch in power system. / Rahimullah, B. N.S.; Ramlan, E.; Rahman, T. K.A.

National Power Engineering Conference, PECon 2003 - Proceedings. 2003. p. 32-36 1437412.

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

TY - GEN

T1 - Evolutionary approach for solving economic dispatch in power system

AU - Rahimullah, B. N.S.

AU - Ramlan, E.

AU - Rahman, T. K.A.

PY - 2003/1/1

Y1 - 2003/1/1

N2 - 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.

AB - 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.

KW - Cost function

KW - Equations

KW - Genetic algorithms

KW - Genetic mutations

KW - Genetic programming

KW - Power generation

KW - Power generation economics

KW - Power system economics

KW - Power systems

KW - Propagation losses

UR - http://www.scopus.com/inward/record.url?scp=30944466102&partnerID=8YFLogxK

U2 - 10.1109/PECON.2003.1437412

DO - 10.1109/PECON.2003.1437412

M3 - Conference contribution

SP - 32

EP - 36

BT - National Power Engineering Conference, PECon 2003 - Proceedings

ER -

Rahimullah BNS, Ramlan E, Rahman TKA. Evolutionary approach for solving economic dispatch in power system. In National Power Engineering Conference, PECon 2003 - Proceedings. 2003. p. 32-36. 1437412 https://doi.org/10.1109/PECON.2003.1437412