On the multi-objective optimization of wind farm cable layouts with regard to cost and robustness.

Christie, Lee A.; Sahin, Atakan; Ogunsemi, Akinola; Zăvoianu, Alexandru-Ciprian; McCall, John A.W.

Abstract

Offshore wind farms (OWFs) have emerged as a vital component in the transition to renewable energy, especially for countries like the United Kingdom with abundant shallow coastal waters suitable for wind energy exploitation. As net-zero emissions targets propel investments in renewables, OWFs present unique engineering challenges, particularly in the design of cost-effective and efficient infrastructural networks such as layout and electrical system optimization. Diverging from the previous approaches in electrical system optimization for OWFs, this paper introduces network robustness as a pivotal metric in design evaluations, differing from traditional reliability evaluation focused studies. By designing approximate solutions to the capacitated minimum spanning tree (CMST) using an approach grounded in a radial space partitioning strategy, the application of the Non-dominated Sorting Genetic Algorithm II (NSGA-II), and a bespoke domain-specific mutation operator, we present a multi-objective exploration of the cost-robustness trade-off. To demonstrate the effectiveness of our approach and its ability to offer decision makers valuable insight on cable layout designs, we apply it to a real world case study that considers the Anholt OWF. The obtained results indicate the ability of our approach to discover sets of high-quality solutions, underscoring its potential to enhance the strategic development of robust and economically viable OWF networks.

Citation

CHRISTIE, L.A., SAHIN, A., OGUNSEMI, A., ZĂVOIANU, A.-C. and MCCALL, J.A.W. 2024. On the multi-objective optimization of wind farm cable layouts with regard to cost and robustness. In Affenzeller, M., Winkler, S.M., Kononova, A.V. et al. (eds). Parallel problem solving from nature (PPSN XVIII): proceedings of the 18th Parallel problem solving from nature international conference 2024 (PPSN 2024), 14-18 September 2024, Hagenberg, Austria. Lecture notes in computer science, 15151. Cham: Springer [online], pages 367-382. Available from: https://doi.org/10.1007/978-3-031-70085-9_23

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 18th Parallel problem solving from nature international conference 2024 (PPSN 2024)
• Start Date: Sep 14, 2024
• End Date: Sep 18, 2024
• Acceptance Date: May 31, 2024
• Online Publication Date: Sep 7, 2024
• Publication Date: Dec 31, 2024
• Deposit Date: Jun 28, 2024
• Publicly Available Date: Sep 8, 2025
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Pages: 367-382
• Series Title: Lecture notes in computer science (LNCS)
• Series Number: 15151
• Series ISSN: 0302-9743; 1611-3349
• Book Title: Parallel problem solving from nature (PPSN XVIII): proceedings of the 18th Parallel problem solving from nature international conference 2024 (PPSN 2024), 14-18 September 2024, Hagenberg, Austria
• ISBN: 9783031700842
• DOI: https://doi.org/10.1007/978-3-031-70085-9_23
• Keywords: Topology optimization; Network robustness; Offshore wind farm; Inter-array cabling; Optimal trade-offs; Planarity constraints
• Public URL: https://rgu-repository.worktribe.com/output/2383488