Optimal standing reserve utilisation using genetic algorithms

F Li, X Zhang, R W Dunn

Research output: Contribution to conferencePaper

9 Citations (Scopus)

Abstract

This paper proposes a genetic algorithm (GA) based economic contracting strategy for standing reserve in a typical standing reserve market. The aim of the contracting procedure is to identify the standing reserve tenders to be contracted and the correct-contract order among the tender options received and scheduled reserve alternatives, to meet the reserve requirement at the lowest possible cost. The contract ordering is a simple problem when all options are rendering for a fixed period of time, however, it becomes troublesome with the presence of flexible contracts, i.e. with standing reserve only available for a partial service window. The proposed GA contracting strategy aims to address the complexity caused by flexible contracts. The results for a system with 16 fixed and flexible tender options are presented and compared with those of mixed integer linear programming (MILP) methods
Original languageEnglish
Pages553-558 vol.2
Publication statusPublished - 2001
EventPower Engineering Society Winter Meeting, 2001. IEEE -
Duration: 1 Jan 2001 → …

Conference

ConferencePower Engineering Society Winter Meeting, 2001. IEEE
Period1/01/01 → …

Fingerprint

Genetic algorithm
Contracting
Economics
Reserve requirements
Mixed integer linear programming
Costs

Keywords

  • flexible contracts
  • electricity supply industry
  • genetic algorithms
  • contract ordering
  • power system economics
  • partial service window
  • optimal standing reserve utilisation
  • contracts
  • tender options
  • economic contracting strategy

Cite this

Li, F., Zhang, X., & Dunn, R. W. (2001). Optimal standing reserve utilisation using genetic algorithms. 553-558 vol.2. Paper presented at Power Engineering Society Winter Meeting, 2001. IEEE, .

Optimal standing reserve utilisation using genetic algorithms. / Li, F; Zhang, X; Dunn, R W.

2001. 553-558 vol.2 Paper presented at Power Engineering Society Winter Meeting, 2001. IEEE, .

Research output: Contribution to conferencePaper

Li, F, Zhang, X & Dunn, RW 2001, 'Optimal standing reserve utilisation using genetic algorithms', Paper presented at Power Engineering Society Winter Meeting, 2001. IEEE, 1/01/01 pp. 553-558 vol.2.
Li F, Zhang X, Dunn RW. Optimal standing reserve utilisation using genetic algorithms. 2001. Paper presented at Power Engineering Society Winter Meeting, 2001. IEEE, .
Li, F ; Zhang, X ; Dunn, R W. / Optimal standing reserve utilisation using genetic algorithms. Paper presented at Power Engineering Society Winter Meeting, 2001. IEEE, .
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