Knowledge-based genetic algorithm for unit commitment

C.J. Aldridge, S. McKee, J.R. McDonald, S.J. Galloway, K.P. Dahal, M.E. Bradley, J.F. Macqueen

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

A genetic algorithm (GA) augmented with knowledge-based methods has been developed for solving the unit commitment economic dispatch problem. The GA evolves a population of binary strings which represent commitment schedules. The initial population of schedules is chosen using a method based on elicited scheduling knowledge. A fast rule-based dispatch method is then used to evaluate candidate solutions. The knowledge-based genetic algorithm is applied to a test system of ten thermal units over 24-hour time intervals, including minimum on/off times and ramp rates, and achieves lower cost solutions than Lagrangian relaxation in comparable computational time.
LanguageEnglish
Pages146-152
Number of pages7
JournalIEE Proceedings Generation Transmission and Distribution
Volume148
Issue number2
DOIs
Publication statusPublished - 31 Mar 2001

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Genetic algorithms
Scheduling
Economics
Costs
Hot Temperature

Keywords

  • algorithms
  • computer systems
  • genetics
  • genetic algorithm

Cite this

Aldridge, C.J. ; McKee, S. ; McDonald, J.R. ; Galloway, S.J. ; Dahal, K.P. ; Bradley, M.E. ; Macqueen, J.F. / Knowledge-based genetic algorithm for unit commitment. In: IEE Proceedings Generation Transmission and Distribution. 2001 ; Vol. 148, No. 2. pp. 146-152.
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Knowledge-based genetic algorithm for unit commitment. / Aldridge, C.J.; McKee, S.; McDonald, J.R.; Galloway, S.J.; Dahal, K.P.; Bradley, M.E.; Macqueen, J.F.

In: IEE Proceedings Generation Transmission and Distribution, Vol. 148, No. 2, 31.03.2001, p. 146-152.

Research output: Contribution to journalArticle

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