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Annals of Operations Research

, Volume 210, Issue 1, pp 387–410 | Cite as

A decomposition approach to the two-stage stochastic unit commitment problem

  • Qipeng P. ZhengEmail author
  • Jianhui Wang
  • Panos M. Pardalos
  • Yongpei Guan
Article

Abstract

The unit commitment problem has been a very important problem in the power system operations, because it is aimed at reducing the power production cost by optimally scheduling the commitments of generation units. Meanwhile, it is a challenging problem because it involves a large amount of integer variables. With the increasing penetration of renewable energy sources in power systems, power system operations and control have been more affected by uncertainties than before. This paper discusses a stochastic unit commitment model which takes into account various uncertainties affecting thermal energy demand and two types of power generators, i.e., quick-start and non-quick-start generators. This problem is a stochastic mixed integer program with discrete decision variables in both first and second stages. In order to solve this difficult problem, a method based on Benders decomposition is applied. Numerical experiments show that the proposed algorithm can solve the stochastic unit commitment problem efficiently, especially those with large numbers of scenarios.

Keywords

Benders decomposition Energy Two-stage stochastic unit commitment Stochastic mixed integer programming Mixed integer subproblem 

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Qipeng P. Zheng
    • 1
    Email author
  • Jianhui Wang
    • 2
  • Panos M. Pardalos
    • 3
    • 4
  • Yongpei Guan
    • 3
  1. 1.Department of Industrial & Management Systems EngineeringWest Virginia UniversityMorgantownUSA
  2. 2.Decision and Information Sciences DivisionArgonne National LaboratoryArgonneUSA
  3. 3.Department of Industrial & Systems EngineeringUniversity of FloridaGainesvilleUSA
  4. 4.Laboratory of Algorithms and Technologies for Networks Analysis (LATNA)Higher School of Economics, National Research UniversityMoscowRussia

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