Abstract
In this article, an integer linear programming model for cost minimization of cable layouts in offshore wind farms is presented. All turbines must be connected to power substations by cables. Up to a given number, turbines may be connected along a joint cable in a series circuit, and cable branching at turbine locations is possible. No two cables are allowed to cross each other. As an improvement over previously available models, the model under study enables optimal adaptation of the cable routes to obstacles. Obstacles of two different kinds are considered. First, a set of regions in which cables cannot be laid is accepted as part of the input to the model. Second, the trajectory of one cable plays the role of an obstacle to all other cables. Both obstacle types are modeled by introducing optional connection points, which, contrary to the turbines, do not have to be visited by any cable. By introducing such optional connection points at selected positions, we arrive at a model with some resemblance with the Steiner tree problem. We demonstrate that, by virtue of the optional points, the suggested model is able to identify feasible solutions to problem instances where other models fail to do so. In other instances, the model yields more cost-effective cable layouts than previously studied models do. Computational experiments with realistic wind farm instances of up to 88 turbines prove that cabling cost reductions of about \(1\%\) are achievable by the model.







Similar content being viewed by others
References
Bauer, J., & Lysgaard, J. (2015). Offshore wind farm array cable layout problem. Journal of the Operational Research Society, 66(3), 360–368.
Cerveira, A., de Sousa, A., Pires, E. J. S., & Baptista, J. (2016). Optimal cable design of wind farms: The infrastructure and losses cost minimization case. IEEE Transactions on Power Systems, 31(6), 4319–4329.
DONG Energy Hornsea Project One (UK) Ltd. (2017). Hornsea project one. http://www.hornseaprojectone.co.uk. Accessed 10 June 2017.
Fischetti, M., & Pisinger, D. (2016). Inter-array cable routing optimization for big wind parks with obstacles. In Control Conference (ECC), 2016 European (pp. 617–622). IEEE.
Foley, A. M., Leahy, P. G., Marvuglia, A., & McKeogh, E. J. (2012). Current methods and advances in forecasting of wind power generation. Renewable Energy, 37(1):1–8. ISSN 09601481.
Gonzalez-Longatt, F. M., Wall, P., Regulski, P., & Terzija, V. (2012). Optimal electric network design for a large offshore wind farm based on a modified genetic algorithm approach. IEEE Systems Journal, 6(1), 164–172.
Greater Gabbard Offshore Winds Ltd. (2005). Greater gabbard offshore windfarm: Non-technical summary.http://sse.com/media/93004/NonTechnicalSummary.pdf. Accessed 27 June 2017.
GWEC. (2015). Global wind energy council: Global wind report 2013. http://www.gwec.org. Accessed 01 Dec 2015.
Hertz, A., Marcotte, O., Mdimagh, A., Carreau, M., & Welt, F. (2017). Design of a wind farm collection network when several cable types are available. Journal of the Operational Research Society, 68(1), 62–73.
Hou, P., Hu, W., Chen, C., & Chen, Z. (2016). Optimisation of offshore wind farm cable connection layout considering levelised production cost using dynamic minimum spanning tree algorithm. IET Renewable Power Generation, 10(2), 175–183.
Hwang, F. K., Richards, D. S., & Winter, P. (1992). The Steiner tree problem. Annals of discrete mathematics (Vol. 53). North Holland: Elsevier. ISBN 9780444890986.
Irawan, C.A., Ouelhadj, D., Jones, D., Stlhane, M., & Sperstad, I. B. (2017). Optimisation of maintenance routing and scheduling for offshore wind farms. European Journal of Operational Research, 256(1), 76–89. ISSN 0377-2217.
KIS-ORCA. (2017). Kingfisher awareness charts. http://www.kis-orca.eu. Accessed 10 Jan 2017.
Klein, A., Haugland, D., Bauer, J., & Mommer, M. (2015). An integer programming model for branching cable layouts in offshore wind farms. Advances in Intelligent Systems and Computing, 359, 27–36.
Lingling, H., Yang, F., & Xiaoming, G. (2009). Optimization of electrical connection scheme for large offshore wind farm with genetic algorithm. In International Conference on Sustainable Power Generation and Supply, 2009 (pp. 1–4).
London Array Limited. (2017). London array, the worlds largest offshore wind farm. http://www.londonarray.com. Accessed 10 June 2017.
Pillai, A. C., Chick, J., Johanning, L., Khorasanchi, M., & de Laleu, V. (2015). Offshore wind farm electrical cable layout optimization. Engineering Optimization, 47(12), 1689–1708.
Réthoré, P. -E., Fuglsang, P., Larsen, G. C., Buhl, T., Larsen, T. J., & Madsen., H. A. (2014). TOPFARM: Multi-fidelity optimization of wind farms. Wind Energy, 17(12):1797–1816. ISSN 10954244.
Wdzik, A., Siewierski, T., & Szypowski, M. (2016). A new method for simultaneous optimizing of wind farms network layout and cable cross-sections by MILP optimization. Applied Energy, 182, 525–538.
WindEurope. (2017). The European offshore wind industry: Key trends and statistics 2016. http://windeurope.org. Accessed 05 Jan 2017.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Klein, A., Haugland, D. Obstacle-aware optimization of offshore wind farm cable layouts. Ann Oper Res 272, 373–388 (2019). https://doi.org/10.1007/s10479-017-2581-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-017-2581-5