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Mathematical Optimization and Algorithms for Offshore Wind Farm Design: An Overview

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  • Martina Fischetti

    (Vattenfall BA Wind)

  • David Pisinger

    (Technical University of Denmark)

Abstract

Wind energy is a fast evolving field that has attracted a lot of attention and investments in the last decades. Being an increasingly competitive market, it is very important to minimize establishment costs and increase production profits already at the design phase of new wind parks. This paper is based on many years of collaboration with Vattenfall, a leading wind energy developer and wind power operator, and aims at giving an overview of the experience of using Mathematical Optimization in the field. The paper illustrates some of the practical needs defined by energy companies, showing how optimization can help the designers to increase production and reduce costs in the design of offshore parks. In particular, the study gives an overview of the individual phases of designing an offshore wind farm, and some of the optimization problems involved. Finally it goes in depth with three of the most important optimization tasks: turbine location, electrical cable routing and foundation optimization. The paper is concluded with a discussion of future challenges.

Suggested Citation

  • Martina Fischetti & David Pisinger, 2019. "Mathematical Optimization and Algorithms for Offshore Wind Farm Design: An Overview," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 469-485, August.
  • Handle: RePEc:spr:binfse:v:61:y:2019:i:4:d:10.1007_s12599-018-0538-0
    DOI: 10.1007/s12599-018-0538-0
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    References listed on IDEAS

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    1. Joanna Bauer & Jens Lysgaard, 2015. "The offshore wind farm array cable layout problem: a planar open vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(3), pages 360-368, March.
    2. Martina Fischetti & Michele Monaci, 2016. "Proximity search heuristics for wind farm optimal layout," Journal of Heuristics, Springer, vol. 22(4), pages 459-474, August.
    3. Turner, S.D.O. & Romero, D.A. & Zhang, P.Y. & Amon, C.H. & Chan, T.C.Y., 2014. "A new mathematical programming approach to optimize wind farm layouts," Renewable Energy, Elsevier, vol. 63(C), pages 674-680.
    4. Kusiak, Andrew & Song, Zhe, 2010. "Design of wind farm layout for maximum wind energy capture," Renewable Energy, Elsevier, vol. 35(3), pages 685-694.
    5. Irawan, Chandra Ade & Ouelhadj, Djamila & Jones, Dylan & Stålhane, Magnus & Sperstad, Iver Bakken, 2017. "Optimisation of maintenance routing and scheduling for offshore wind farms," European Journal of Operational Research, Elsevier, vol. 256(1), pages 76-89.
    6. Topham, Eva & McMillan, David, 2017. "Sustainable decommissioning of an offshore wind farm," Renewable Energy, Elsevier, vol. 102(PB), pages 470-480.
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    Cited by:

    1. Martina Fischetti & Jesper Runge Kristoffersen & Thomas Hjort & Michele Monaci & David Pisinger, 2020. "Vattenfall Optimizes Offshore Wind Farm Design," Interfaces, INFORMS, vol. 50(1), pages 80-94, January.
    2. Fischetti, Martina & Fischetti, Matteo & Stoustrup, Jakob, 2023. "Safe distancing in the time of COVID-19," European Journal of Operational Research, Elsevier, vol. 304(1), pages 139-149.
    3. Martina Fischetti & Matteo Fischetti, 2023. "Integrated Layout and Cable Routing in Wind Farm Optimal Design," Management Science, INFORMS, vol. 69(4), pages 2147-2164, April.
    4. Cazzaro, Davide & Fischetti, Martina & Fischetti, Matteo, 2020. "Heuristic algorithms for the Wind Farm Cable Routing problem," Applied Energy, Elsevier, vol. 278(C).

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