Evaluation of two lagrangian dual optimization algorithms for large-scale unit commitment problems

Wen Fan, Yuan Liao, Jong Beom Lee, Yong Kab Kim

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Lagrangian relaxation is the most widely adopted method for solving unit commitment (UC) problems. It consists of two steps: dual optimization and primal feasible solution construction. The dual optimization step is crucial in determining the overall performance of the solution. This paper intends to evaluate two dual optimization methods - one based on subgradient (SG) and the other based on the cutting plane. Large-scale UC problems with hundreds of thousands of variables and constraints have been generated for evaluation purposes. It is found that the evaluated SG method yields very promising results.

Original languageEnglish
Pages (from-to)17-22
Number of pages6
JournalJournal of Electrical Engineering and Technology
Volume7
Issue number1
DOIs
StatePublished - Jan 2012

Keywords

  • Dual optimization
  • Lagrangian relaxation
  • Resource scheduling
  • Unit commitment

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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