Multi-Cuts Outer Approximation Method for Unit Commitment

Linfeng Yang, Jinbao Jian*, Zhaoyang Dong, Chunming Tang

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This letter introduces a deterministic global optimization methods for unit commitment (UC) problem based on outer approximation method (OAM). The proposed Multi-cuts OAM (MCs-OAM) decomposes the UC problem into a mixed integer linear programming (MILP) master problem and several nonlinear programming (NLP) subproblems, whereas only one NLP in classic OAM. After elaborately designing the terminating criterion for solving the bigger but tighter MILP master problems, MCs-OAM can obtained higher quality solutions with fewer main iterations and less total CPU times, although solving more NLPs consumes more CPU times than OAM. The numerical results on 42 test systems of up to 200 units show that the MCs-OAM is very promising for large scale UC problems because that it can obtain high-quality solutions in reasonable time. © 1969-2012 IEEE.
Original languageEnglish
Article number7508383
Pages (from-to)1587-1588
JournalIEEE Transactions on Power Systems
Volume32
Issue number2
DOIs
Publication statusPublished - 1 Mar 2017
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • Mixed integer linear programming
  • multiple cuts
  • outer approximation
  • unit commitment

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