Tank Testing of Load Reduction Device for Floating Offshore Wind Moorings
Year: 2025
Type: conference-paper
Abstract: Floating Wind Energy farms are the next frontier is exploitation of offshore wind resources in open seas with high load factors. One of the challenges facing energy generation at these farms is the relatively high Levelized Cost of Electricity (LCOE). A typical wind farm is a complex installation with platform mounted turbine generators with multiple subsystems and strict requirements for station-keeping in face of wind and hydrodynamic loads. Mooring systems used for station keeping are subjected to high loads due to the environmental conditions. Hence, it is imperative to find cost-effective mooring solutions to lower the LCOE. Such solutions include the use of Mooring Optimization Technologies (MOTs) aimed at reducing the high peak and snatch loads in mooring lines and thus driving down the capital, operations and maintenance costs. In this paper, a wave tank testing campaign is described and analyzed. The objective of this testing campaign was to demonstrate the efficacy of an MOT for an open-source model wind platform in various water depths and sea states. The campaign produced high fidelity data that demonstrates that the selected MOT can achieve a peak load reduction of as much as 80% compared to a baseline without the MOT with large reductions in snatch load scenarios. Moreover, no significant impact on platform motion and nacelle acceleration for the open-source platform is observed, which implies the energy generation remains unaffected. These results, combined with simple construction and operation of the selected MOT, show great potential for certification and adoption of the technology for floating wind platforms.
Source: Offshore Technology Conference
DOI: 10.4043/35858-ms
Authors: T. Doyle, S. A. Hasan, D. Golden
Institution: University College Dublin
Language: English
Topic: Wave and Wind Energy Systems
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4409855818