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A Multi-objective Time Segmentation Approach for Power Generation and Transmission Models

In: Operations Research Proceedings 2015

Author

Listed:
  • Viktor Slednev

    (Institute for Industrial Production (IIP)
    Karlsruhe Institute of Technology (KIT))

  • Valentin Bertsch

    (Institute for Industrial Production (IIP)
    Karlsruhe Institute of Technology (KIT))

  • Wolf Fichtner

    (Institute for Industrial Production (IIP)
    Karlsruhe Institute of Technology (KIT))

Abstract

The complexity of large-scale power system models often necessitates the choice of a suitable temporal resolution. Nowadays, mainly simple heuristic approaches are used. An adequate decision support related to power generation and transmission optimisation in systems with a high RES share, however, requires preserving the complex intra-period and intra-regional links within and between the volatile electricity demand and supply profiles. Focussing on power systems operation, we are able to show that even an amount of less than 300 time segments may be sufficient for the modelling of a whole year, if chosen carefully.

Suggested Citation

  • Viktor Slednev & Valentin Bertsch & Wolf Fichtner, 2017. "A Multi-objective Time Segmentation Approach for Power Generation and Transmission Models," Operations Research Proceedings, in: Karl Franz Dörner & Ivana Ljubic & Georg Pflug & Gernot Tragler (ed.), Operations Research Proceedings 2015, pages 707-714, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-42902-1_95
    DOI: 10.1007/978-3-319-42902-1_95
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    Citations

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    Cited by:

    1. Slednev, Viktor & Bertsch, Valentin & Ruppert, Manuel & Fichtner, Wolf, 2017. "Highly resolved optimal renewable allocation planning in power systems under consideration of dynamic grid topology," MPRA Paper 79706, University Library of Munich, Germany.
    2. Henrik C. Bylling & Salvador Pineda & Trine K. Boomsma, 2020. "The impact of short-term variability and uncertainty on long-term power planning," Annals of Operations Research, Springer, vol. 284(1), pages 199-223, January.
    3. Finke, Jonas & Bertsch, Valentin, 2022. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," MPRA Paper 115504, University Library of Munich, Germany.
    4. Finke, Jonas & Bertsch, Valentin, 2023. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," Applied Energy, Elsevier, vol. 332(C).

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