Dr Lee Christie l.a.christie@rgu.ac.uk
Research Fellow
Dr Lee Christie l.a.christie@rgu.ac.uk
Research Fellow
Atakan Sahin
Akinola Ogunsemi
Dr Ciprian Zavoianu c.zavoianu@rgu.ac.uk
Research Programme Lead
Professor John McCall j.mccall@rgu.ac.uk
Director
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.
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. To be published in: 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. Cham: Springer [online], (accepted).
Conference Name | 18th Parallel problem solving from nature international conference 2024 (PPSN 2024) |
---|---|
Conference Location | Hagenberg, Austria |
Start Date | Sep 14, 2024 |
End Date | Sep 18, 2024 |
Acceptance Date | May 31, 2024 |
Deposit Date | Jun 28, 2024 |
Publisher | Springer |
Series Title | Lecture notes in computer science (LNCS) |
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 |
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 |
This file is under embargo due to copyright reasons.
Contact publications@rgu.ac.uk to request a copy for personal use.
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