Development of an optimal contracting strategy using genetic algorithms in the England and Wales standing reserve market

F Li, X Zhang, R W Dunn

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

This paper presents a genetic algorithm (GA)-based economic contracting strategy for optimal selection of tenders in the England and Wales standing reserve market. The aim of the contracting strategy is three fold-first, to identify potential tenders to be contracted, second, to determine the volume of electric power that each tender should supply, and thirdly how often they should provide the service. The third issue is easy to deal with using a contracting strategy where all tenders bid for a full service window (fixed tenders); however, it becomes troublesome if tenders are allowed to bid for a flexible, partial service window (flexible tenders). In this paper, a GA strategy with a special encoding scheme, order-based crossover and mutation operators (OBGA), has been developed to deal with flexible tenders within the tender selection process. The proposed method has been investigated using four test cases, with different tender flexibility and constraints. The test results clearly demonstrate that the OBGA performs as well as the conventional GA when all tenders bid for fixed contracts; however, OBGA gradually outperforms the conventional GA as the number of flexible tenders progressively increases.
Original languageEnglish
Pages (from-to)842-847
Number of pages6
JournalPower Systems, IEEE Transactions on
Volume18
Issue number2
Publication statusPublished - 2003

Keywords

  • tender flexibility
  • tender constraints
  • genetic algorithms
  • linear programming
  • order-based crossover and mutation operators
  • power system economics
  • UK
  • optimal contracting strategy
  • integer programming
  • National Grid
  • optimal tenders selection
  • power markets
  • contracts
  • economic contracting strategy
  • standing reserve market

Fingerprint Dive into the research topics of 'Development of an optimal contracting strategy using genetic algorithms in the England and Wales standing reserve market'. Together they form a unique fingerprint.

Cite this