What type of study is this?

This is a Quantitative Study study (also classified as: Experimental Study).

October 16, 2025Open Access

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

Key Points

A mass reduction of 9% was achieved by optimizing the design of the platform.
Under the SARIMAX scenario, optimal costs are predicted at 4404.56 €/t, 24.1% lower than average.
The levelized cost of energy for the optimized platform was reduced by 2.08%, enhancing economic viability.
Statistical and machine learning methods were employed for forecasting costs across various scenarios.

Abstract

Abstract. This work proposes a structural and economic optimisation framework applicable to floating semi-submersible platforms, demonstrated here for a 15-MW offshore wind design. A genetic algorithm was developed that can seek a multi-objective solution to minimise mass whilst respecting the constraints of loads acting upon the system. Statistical and machine learning methods are then employed to forecast near and far term costs of the platform under a range of scenarios. Finally, Levelized Cost of Energy is calculated to gauge the technical and economic viability. Results show that a mass reduction of 9 % is possible. With optimal costs predicted under the SARIMAX scenario of 4404.56 €/t, 24.1 % under the average. The optimised platform results in an LCoE reduction of 2.08 %.

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Cite This Study

White et al. (Wed,) studied this question.

synapsesocial.com/papers/68f0f51d8dd8ea469b1d70aa https://doi.org/https://doi.org/10.5194/wes-2025-197

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