Articles | Volume 11, issue 9
https://doi.org/10.5194/wes-11-3703-2026
https://doi.org/10.5194/wes-11-3703-2026
Research article
 | 
24 Sep 2026
Research article |  | 24 Sep 2026

Economic and design optimization of a 15 MW floating offshore wind platform using time series forecasting

Craig White, Victor Benifla, José Cândido, and Luís M. C. Gato

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Revised manuscript under review for WES
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Cited articles

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Bak, C., Zahle, F., Bitsche, R., Kim, T., Yde, A., Henriksen, L. C., Natarajan, A., and Hansen, M. H.: Description of the DTU 10 MW Reference Wind Turbine, DTU Wind Energy Report-I-0092, DTU Wind Energy, Roskilde, Denmark, https://gitlab.windenergy.dtu.dk/rwts/dtu-10mw-rwt (last access: 27 July 2026), 2013. 
Barter, G. E., Robertson, A., and Musial, W.: A systems engineering vision for floating offshore wind cost optimization, Renew. Energy Focus, 34, 1–16, https://doi.org/10.1016/j.ref.2020.03.002, 2020. 
Beiter, P., Musial, W., Duffy, P., Cooperman, A., Shields, M., Heimiller, D., and Optis, M.: The cost of floating offshore wind energy in California between 2019 and 2032, National Renewable Energy Laboratory, Golden, CO, USA, NREL/TP-5000-77384, https://doi.org/10.2172/1710181, 2020. 
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This paper looks to create sensible mass reductions to the new commercial-scale floating offshore wind platforms, which must reduce in cost if they are to be deployed at scale. A response–amplitude numerical model tested the floating wind system against environmental loads, whilst a genetic algorithm optimized the geometrical design. Then, a time series forecasting tool blends the models to predict future prices to accurately provide platform and energy costs.
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