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A benders decomposition approach for solving the offshore wind farm installation planning at the North Sea

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  • Ursavas, Evrim

Abstract

Wind farm installation and particularly offshore wind farm installation is highly complex due to high dependency on weather and remarkably large components. Amongst others projects at North Sea face considerable interruptions due to severe weather conditions. The problem we refer to consists of determining the renting period of the offshore installation vessels and the scheduling of the operations for building the wind farm. Planners need to make these decisions under the uncertain wind states. A deterministic offshore wind turbine installation model is not suitable to capture the uncertainties which may leave the vessel resource unused or vessel being sent offshore in unfavorable conditions. Accordingly, this study proposes a model that considers disruptions arising from uncertain weather conditions which stand as the main challenge for such projects. As the compact formulation fails to provide solutions due to the large number of scenarios, an approach based on Benders decomposition is developed. The tool is applied to two major wind farm projects, “Bard 1” and “Borkum West” at the North Sea using real weather data over two years. The two-stage model leans to conservatively use the suitable conditions in advance to avoid huge waiting costs incurred under severe weather. Motivated by experts at Wagenborg and MPI Offshore, we extend our experiments to analyze cases where plants are build further away from the shore. The tool presented in this study is suitable for being used in the planning of wind farm projects providing competent solutions.

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  • Ursavas, Evrim, 2017. "A benders decomposition approach for solving the offshore wind farm installation planning at the North Sea," European Journal of Operational Research, Elsevier, vol. 258(2), pages 703-714.
    • Handle: RePEc:eee:ejores:v:258:y:2017:i:2:p:703-714
    DOI: 10.1016/j.ejor.2016.08.057
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    1. Santiago Cerisola & Álvaro Baíllo & José M. Fernández-López & Andrés Ramos & Ralf Gollmer, 2009. "Stochastic Power Generation Unit Commitment in Electricity Markets: A Novel Formulation and a Comparison of Solution Methods," Operations Research, INFORMS, vol. 57(1), pages 32-46, February.
    2. Jean-François Cordeau & Goran Stojković & François Soumis & Jacques Desrosiers, 2001. "Benders Decomposition for Simultaneous Aircraft Routing and Crew Scheduling," Transportation Science, INFORMS, vol. 35(4), pages 375-388, November.
    3. Stadtler, Hartmut & Sahling, Florian, 2013. "A lot-sizing and scheduling model for multi-stage flow lines with zero lead times," European Journal of Operational Research, Elsevier, vol. 225(3), pages 404-419.
    4. Trappey, Amy J.C. & Trappey, Charles V. & Liu, Penny H.Y. & Lin, Lee-Cheng & Ou, Jerry J.R., 2013. "A hierarchical cost learning model for developing wind energy infrastructures," International Journal of Production Economics, Elsevier, vol. 146(2), pages 386-391.
    5. Chen, Haoxun & Luh, Peter B., 2003. "An alternative framework to Lagrangian relaxation approach for job shop scheduling," European Journal of Operational Research, Elsevier, vol. 149(3), pages 499-512, September.
    6. Cheng-Hsiang Liu, 2016. "Mathematical programming formulations for single-machine scheduling problems while considering renewable energy uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 54(4), pages 1122-1133, February.
    7. Wang, S. & Huang, G.H., 2015. "A multi-level Taguchi-factorial two-stage stochastic programming approach for characterization of parameter uncertainties and their interactions: An application to water resources management," European Journal of Operational Research, Elsevier, vol. 240(2), pages 572-581.
    8. Alumur, Sibel A. & Nickel, Stefan & Saldanha-da-Gama, Francisco & Verter, Vedat, 2012. "Multi-period reverse logistics network design," European Journal of Operational Research, Elsevier, vol. 220(1), pages 67-78.
    9. Mao, Kun & Pan, Quan-ke & Pang, Xinfu & Chai, Tianyou, 2014. "A novel Lagrangian relaxation approach for a hybrid flowshop scheduling problem in the steelmaking-continuous casting process," European Journal of Operational Research, Elsevier, vol. 236(1), pages 51-60.
    10. Haugen, Kjetil K., 1996. "A Stochastic Dynamic Programming model for scheduling of offshore petroleum fields with resource uncertainty," European Journal of Operational Research, Elsevier, vol. 88(1), pages 88-100, January.
    11. Herroelen, Willy & Leus, Roel, 2005. "Project scheduling under uncertainty: Survey and research potentials," European Journal of Operational Research, Elsevier, vol. 165(2), pages 289-306, September.
    12. R. M’Hallah & T. Al-Khamis, 2015. "A Benders decomposition approach to the weighted number of tardy jobs scheduling problem on unrelated parallel machines with production costs," International Journal of Production Research, Taylor & Francis Journals, vol. 53(19), pages 5977-5987, October.
    13. Hanif Sherali & Ki-Hwan Bae & Mohamed Haouari, 2013. "A benders decomposition approach for an integrated airline schedule design and fleet assignment problem with flight retiming, schedule balance, and demand recapture," Annals of Operations Research, Springer, vol. 210(1), pages 213-244, November.
    14. Arnt-Gunnar Lium & Teodor Gabriel Crainic & Stein W. Wallace, 2009. "A Study of Demand Stochasticity in Service Network Design," Transportation Science, INFORMS, vol. 43(2), pages 144-157, May.
    15. Xydis, George, 2013. "A techno-economic and spatial analysis for the optimal planning of wind energy in Kythira island, Greece," International Journal of Production Economics, Elsevier, vol. 146(2), pages 440-452.
    16. Halvorsen-Weare, Elin E. & Fagerholt, Kjetil & Nonås, Lars Magne & Asbjørnslett, Bjørn Egil, 2012. "Optimal fleet composition and periodic routing of offshore supply vessels," European Journal of Operational Research, Elsevier, vol. 223(2), pages 508-517.
    17. Rentizelas, Athanasios A. & Tolis, Athanasios I. & Tatsiopoulos, Ilias P., 2012. "Investment planning in electricity production under CO2 price uncertainty," International Journal of Production Economics, Elsevier, vol. 140(2), pages 622-629.
    18. Pantuso, Giovanni & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A survey on maritime fleet size and mix problems," European Journal of Operational Research, Elsevier, vol. 235(2), pages 341-349.
    19. Bjørnar Aas & Øyvind Halskau Sr & Stein W Wallace, 2009. "The role of supply vessels in offshore logistics," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 11(3), pages 302-325, September.
    20. Arno Maatman & Caspar Schweigman & Arjan Ruijs & Maarten H. van Der Vlerk, 2002. "Modeling Farmers' Response to Uncertain Rainfall in Burkina Faso: A Stochastic Programming Approach," Operations Research, INFORMS, vol. 50(3), pages 399-414, June.
    21. Gyana R. Parija & Shabbir Ahmed & Alan J. King, 2004. "On Bridging the Gap Between Stochastic Integer Programming and MIP Solver Technologies," INFORMS Journal on Computing, INFORMS, vol. 16(1), pages 73-83, February.
    22. Li, Haitao & Womer, Norman K., 2015. "Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 246(1), pages 20-33.
    23. Ivan Contreras & Jean-François Cordeau & Gilbert Laporte, 2011. "Benders Decomposition for Large-Scale Uncapacitated Hub Location," Operations Research, INFORMS, vol. 59(6), pages 1477-1490, December.
    24. Sun, Xiaojing & Huang, Diangui & Wu, Guoqing, 2012. "The current state of offshore wind energy technology development," Energy, Elsevier, vol. 41(1), pages 298-312.
    25. Cardoso, Sónia R. & Barbosa-Póvoa, Ana Paula F.D. & Relvas, Susana, 2013. "Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 226(3), pages 436-451.
    26. Victor Santana-Viera & Jesus Jimenez & Tongdan Jin & Jose Espiritu, 2015. "Implementing factory demand response via onsite renewable energy: a design-of-experiment approach," International Journal of Production Research, Taylor & Francis Journals, vol. 53(23), pages 7034-7048, December.
    27. Kai Huang & Shabbir Ahmed, 2009. "The Value of Multistage Stochastic Programming in Capacity Planning Under Uncertainty," Operations Research, INFORMS, vol. 57(4), pages 893-904, August.
    28. Joyce W. Yen & John R. Birge, 2006. "A Stochastic Programming Approach to the Airline Crew Scheduling Problem," Transportation Science, INFORMS, vol. 40(1), pages 3-14, February.
    29. Bilgili, Mehmet & Yasar, Abdulkadir & Simsek, Erdogan, 2011. "Offshore wind power development in Europe and its comparison with onshore counterpart," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 905-915, February.
    30. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    31. Ricardo Saraiva de Camargo & Gilberto de Miranda & Henrique Pacca L. Luna, 2009. "Benders Decomposition for Hub Location Problems with Economies of Scale," Transportation Science, INFORMS, vol. 43(1), pages 86-97, February.
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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. Taylor, James W. & Jeon, Jooyoung, 2018. "Probabilistic forecasting of wave height for offshore wind turbine maintenance," European Journal of Operational Research, Elsevier, vol. 267(3), pages 877-890.
    3. 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.
    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. Rippel, Daniel & Jathe, Nicolas & Lütjen, Michael & Szczerbicka, Helena & Freitag, Michael, 2019. "Integrated domain model for operative offshore installation planning," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Digital Transformation in Maritime and City Logistics: Smart Solutions for Logistics. Proceedings of the Hamburg International Conference of Logistics, volume 28, pages 25-54, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    6. 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.
    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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