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Solving Hard Mixed-Integer Programs for Electricity Generation

  • Chapter
The Next Generation of Electric Power Unit Commitment Models

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 36))

Abstract

In this chapter, we describe the most recent advances in the solution of mixed-integer programming problems. The last ten years have seen enormous improvements in the solution of the most difficult mixed-integer programs. The trend towards integration of modeling and optimization now makes it possible to solve the hardest optimization problems arising from electricity generation, such as the unit commitment problem. We report results with a leading software package that was used successfully to solve unit commitment problems in two European utility companies.

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Author information

Authors and Affiliations

  1. Columbia University and Dash Optimization, Inc., USA

    Sebastian Ceria

Authors
  1. Sebastian Ceria
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Editor information

Editors and Affiliations

  1. The Johns Hopkins University, USA

    Benjamin F. Hobbs

  2. Rutgers University, USA

    Michael H. Rothkopf

  3. Federal Energy Regulatory Commission, USA

    Richard P. O’Neill

  4. Electric Power Research Institute, USA

    Hung-po Chao

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© 2002 Kluwer Academic Publishers

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Ceria, S. (2002). Solving Hard Mixed-Integer Programs for Electricity Generation. In: Hobbs, B.F., Rothkopf, M.H., O’Neill, R.P., Chao, Hp. (eds) The Next Generation of Electric Power Unit Commitment Models. International Series in Operations Research & Management Science, vol 36. Springer, Boston, MA. https://doi.org/10.1007/0-306-47663-0_9

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  • DOI: https://doi.org/10.1007/0-306-47663-0_9

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-7923-7334-6

  • Online ISBN: 978-0-306-47663-1

  • eBook Packages: Springer Book Archive

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