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A Lagrangian Decomposition Approach to Solve Large Scale Multi-Sector Energy System Optimization Problems

In: Operations Research Proceedings 2019

Author

Listed:
  • Andreas Bley

    (Universität Kassel)

  • Angela Pape

    (Fraunhofer IEE)

  • Frank Fischer

    (Universität Mainz)

Abstract

We consider the capacity and operations planning of a European energy supply system with a high share of renewable energy. Our model includes the energy sectors electricity, heat, and transportation and it considers numerous types of consumers and power generation, storage, and transformation technologies, which participate in these energy sectors. Given time series for the regional demands in each sector and the potential renewable production, the goal is to simultaneously optimize the strategic dimensioning and the hourly operation of all components in the system such that the overall costs are minimized. In this paper, we propose a Lagrangian solution approach that decomposes the model into many independent unit-commitment-type problems by relaxing several coupling constrains. This allows us to compute high quality lower bounds quickly and, in combination with some problem tailored heuristics, globally valid solutions with less computational effort.

Suggested Citation

  • Andreas Bley & Angela Pape & Frank Fischer, 2020. "A Lagrangian Decomposition Approach to Solve Large Scale Multi-Sector Energy System Optimization Problems," Operations Research Proceedings, in: Janis S. Neufeld & Udo Buscher & Rainer Lasch & Dominik Möst & Jörn Schönberger (ed.), Operations Research Proceedings 2019, pages 249-255, Springer.
    • Handle: RePEc:spr:oprchp:978-3-030-48439-2_30
    DOI: 10.1007/978-3-030-48439-2_30
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