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A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations

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  • Barlow, Euan
  • Tezcaner Öztürk, Diclehan
  • Revie, Matthew
  • Akartunalı, Kerem
  • Day, Alexander H.
  • Boulougouris, Evangelos

Abstract

With a typical investment in excess of £100 million for each project, the installation phase of offshore wind farms (OWFs) is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined framework, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities.

Suggested Citation

  • Barlow, Euan & Tezcaner Öztürk, Diclehan & Revie, Matthew & Akartunalı, Kerem & Day, Alexander H. & Boulougouris, Evangelos, 2018. "A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations," European Journal of Operational Research, Elsevier, vol. 264(3), pages 894-906.
    • Handle: RePEc:eee:ejores:v:264:y:2018:i:3:p:894-906
    DOI: 10.1016/j.ejor.2017.05.043
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    Cited by:

    1. Tjaberings, Jorick & Fazi, Stefano & Ursavas, Evrim, 2022. "Evaluating operational strategies for the installation of offshore wind turbine substructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    2. Chandra Ade Irawan & Graham Wall & Dylan Jones, 2019. "An optimisation model for scheduling the decommissioning of an offshore wind farm," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 513-548, June.
    3. Maria Giuffrida & Riccardo Mangiaracina & Umar Burki, 2021. "Cloud-Based Booking Platforms in Warehouse Operations," Sustainability, MDPI, vol. 13(20), pages 1-16, October.
    4. Amorosi, Lavinia & Fischetti, Martina & Paradiso, Rosario & Roberti, Roberto, 2024. "Optimization models for the installation planning of offshore wind farms," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1182-1196.
    5. Stålhane, Magnus & Halvorsen-Weare, Elin E. & Nonås, Lars Magne & Pantuso, Giovanni, 2019. "Optimizing vessel fleet size and mix to support maintenance operations at offshore wind farms," European Journal of Operational Research, Elsevier, vol. 276(2), pages 495-509.
    6. Stephan Oelker & Aljoscha Sander & Markus Kreutz & Abderrahim Ait-Alla & Michael Freitag, 2021. "Evaluation of the Impact of Weather-Related Limitations on the Installation of Offshore Wind Turbine Towers," Energies, MDPI, vol. 14(13), pages 1-12, June.
    7. Daniel Rippel & Fatemeh Abasian Foroushani & Michael Lütjen & Michael Freitag, 2021. "A Crew Scheduling Model to Incrementally Optimize Workforce Assignments for Offshore Wind Farm Constructions," Energies, MDPI, vol. 14(21), pages 1-21, October.
    8. Lerche, J. & Lorentzen, S. & Enevoldsen, P. & Neve, H.H., 2022. "The impact of COVID -19 on offshore wind project productivity – A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).

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