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Optimizing Large-Scale Linear Energy System Problems with Block Diagonal Structure by Using Parallel Interior-Point Methods

In: Operations Research Proceedings 2017

Author

Listed:
  • Thomas Breuer

    (Forschungszentrum Jülich GmbH)

  • Michael Bussieck

    (GAMS Software GmbH)

  • Karl-Kiên Cao

    (German Aerospace Center (DLR))

  • Felix Cebulla

    (German Aerospace Center (DLR))

  • Frederik Fiand

    (GAMS Software GmbH)

  • Hans Christian Gils

    (German Aerospace Center (DLR))

  • Ambros Gleixner

    (Zuse Institute Berlin/Technical University Berlin)

  • Dmitry Khabi

    (High Performance Computing Center Stuttgart (HLRS))

  • Thorsten Koch

    (Zuse Institute Berlin/Technical University Berlin)

  • Daniel Rehfeldt

    (Zuse Institute Berlin/Technical University Berlin)

  • Manuel Wetzel

    (German Aerospace Center (DLR))

Abstract

Current linear energy system models (ESM) acquiring to provide sufficient detail and reliability frequently bring along problems of both high intricacy and increasing scale. Unfortunately, the size and complexity of these problems often prove to be intractable even for commercial state-of-the-art linear programming solvers. This article describes an interdisciplinary approach to exploit the intrinsic structure of these large-scale linear problems to be able to solve them on massively parallel high-performance computers. A key aspect are extensions to the parallel interior-point solver PIPS-IPM originally developed for stochastic optimization problems. Furthermore, a newly developed GAMS interface to the solver as well as some GAMS language extensions to model block-structured problems will be described.

Suggested Citation

  • Thomas Breuer & Michael Bussieck & Karl-Kiên Cao & Felix Cebulla & Frederik Fiand & Hans Christian Gils & Ambros Gleixner & Dmitry Khabi & Thorsten Koch & Daniel Rehfeldt & Manuel Wetzel, 2018. "Optimizing Large-Scale Linear Energy System Problems with Block Diagonal Structure by Using Parallel Interior-Point Methods," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 641-647, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-89920-6_85
    DOI: 10.1007/978-3-319-89920-6_85
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    Cited by:

    1. Karl-Kiên Cao & Kai von Krbek & Manuel Wetzel & Felix Cebulla & Sebastian Schreck, 2019. "Classification and Evaluation of Concepts for Improving the Performance of Applied Energy System Optimization Models," Energies, MDPI, vol. 12(24), pages 1-51, December.

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