Multidisciplinary design analysis and optimization of floating offshore wind turbine substructures : a review

Ojo, Adebayo and Collu, Maurizio and Coraddu, Andrea (2022) Multidisciplinary design analysis and optimization of floating offshore wind turbine substructures : a review. Ocean Engineering, 266 (Part 1). 112727. ISSN 0029-8018 (https://doi.org/10.1016/j.oceaneng.2022.112727)

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Abstract

The development of novel energy technologies to meet net zero carbon emission is essential in the provision of solutions to realize an increasing worldwide demand for renewable energy. Floating Offshore Wind Turbine (FOWT) is one of the emerging technologies to exploit the vast wind resources available in deep waters within the offshore wind sector. However, as a result of the complexity of a FOWT system, bringing FOWT technology up to speed requires a detailed understanding of the different disciplines within the system and the relationship between the FOWT system and the dynamics of the marine environment; hence, the need for Multidisciplinary Design Analysis and Optimization (MDAO) of the system. This paper reviews the MDAO of FOWT substructures / platforms proposed in the literature. This review covers an overview of floating offshore wind turbine substructures’ concepts, the design using geometric shape parameterization techniques and the analysis approaches (time and frequency domain) for response assessment of the FOWT system. It also provides a comprehensive review of MDAO frameworks for FOWT substructures. Regarding the optimization aspect, a review of some optimization algorithms used for floating offshore wind turbine substructure is provided, i.e., from the global search heuristic and meta-heuristics algorithms to the local search gradient-based optimization algorithms. This work further identifies the research gaps in MDAO for FOWT substructures. The main proposed future research areas to address these gaps are: increasing design space richness by adopting more advanced parametrization techniques to represent the platform geometry (and other characteristics), utilize surrogate/meta models to replace the most computationally expensive high-fidelity models needed for quick sensitivity studies before detailed analyses on selected models are conducted, and exploring the upscaling of the geometric design parameters of an optimal shape parameterized FOWT platforms derived from existing designs which can be coupled with new generation highly rated and heavier turbines.

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