In this paper, a site-specific optimization procedure aimed at finding the optimal substructures of a 10 MW Floating Offshore Wind Turbine (FOWT) is presented. An in-house developed Frequency Domain (FD) model is adopted for the simulation of the coupled system. Two Mediterranean sites have been chosen for the characterization of the metocean environments. 20-year databases have been used to obtain the joint distributions of wind speed, significant wave height and peak spectral period. The optimizations, performed adopting a Genetic Algorithm (GA), are aimed at reducing the costs of the floating substructure, controlling the maximum system response under both extreme and fatigue wind-wave loads. Results show that the optimized solution significantly reduces the system cost with an acceptable increase of the loads, opening interesting perspectives for the reduction of the Levelized Cost of Energy (LCOE) in sites characterized by mild sea states and low wind resource.

Site-specific optimizations of a 10 MW floating offshore wind turbine for the Mediterranean Sea / Ferri G.; Marino E.. - In: RENEWABLE ENERGY. - ISSN 0960-1481. - ELETTRONICO. - 202:(2023), pp. 921-941. [10.1016/j.renene.2022.11.116]

Site-specific optimizations of a 10 MW floating offshore wind turbine for the Mediterranean Sea

Ferri G.
;
Marino E.
2023

Abstract

In this paper, a site-specific optimization procedure aimed at finding the optimal substructures of a 10 MW Floating Offshore Wind Turbine (FOWT) is presented. An in-house developed Frequency Domain (FD) model is adopted for the simulation of the coupled system. Two Mediterranean sites have been chosen for the characterization of the metocean environments. 20-year databases have been used to obtain the joint distributions of wind speed, significant wave height and peak spectral period. The optimizations, performed adopting a Genetic Algorithm (GA), are aimed at reducing the costs of the floating substructure, controlling the maximum system response under both extreme and fatigue wind-wave loads. Results show that the optimized solution significantly reduces the system cost with an acceptable increase of the loads, opening interesting perspectives for the reduction of the Levelized Cost of Energy (LCOE) in sites characterized by mild sea states and low wind resource.
2023
202
921
941
Goal 7: Affordable and clean energy
Ferri G.; Marino E.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1345282
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