Contingency-constrained unit commitment with post-contingency corrective recourse

Richard Li Yang Chen, Neng Fan, Ali Pinar, Jean Paul Watson

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

We consider the problem of minimizing costs in the generation unit commitment problem, a cornerstone in electric power system operations, while enforcing an (Formula presented.)–(Formula presented.)–(Formula presented.) reliability criterion. This reliability criterion is a generalization of the well-known (Formula presented.)–(Formula presented.) criterion and dictates that at least (Formula presented.) fraction of the total system demand (for (Formula presented.)) must be met following the failure of (Formula presented.) or fewer system components. We refer to this problem as the contingency-constrained unit commitment problem, or CCUC. We present a mixed-integer programming formulation of the CCUC that accounts for both transmission and generation element failures. We propose novel cutting plane algorithms that avoid the need to explicitly consider an exponential number of contingencies. Computational studies are performed on several IEEE test systems and a simplified model of the Western US interconnection network. These studies demonstrate the effectiveness of our proposed methods relative to current state-of-the-art.

Original languageEnglish (US)
JournalAnnals of Operations Research
DOIs
StateAccepted/In press - Dec 5 2014

Fingerprint

Contingency
Unit commitment
Commitment problem
Demand systems
Interconnection
Mixed integer programming
Electric power system
Costs
Cutting planes

Keywords

  • Benders decomposition
  • Bi-level programming
  • Contingency constraints
  • Integer programming
  • Unit commitment

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Decision Sciences(all)

Cite this

Contingency-constrained unit commitment with post-contingency corrective recourse. / Chen, Richard Li Yang; Fan, Neng; Pinar, Ali; Watson, Jean Paul.

In: Annals of Operations Research, 05.12.2014.

Research output: Contribution to journalArticle

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