| Citation |
Sperstad, I.B.,Stålhane, M., Dinwoodie, I., Endrerude, O.-E. V., Martin, R. and Warner, E. Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms, Ocean Engineering,145: 334-343, 2017. https://dx.doi.org/10.1016/j.oceaneng.2017.09.009. Cite this using DataCite |
| Author(s) |
Sperstad, I.B.,Stålhane, M., Dinwoodie, I., Endrerude, O.-E. V., Martin, R. and Warner, E. |
| Project partner(s) |
SINTEF, Norwegian University of Science and Technology, University of Strathclyde, University of Stavanger, Electricité de France, National Renewable Energy Laboratory |
| Publisher |
Ocean Engineering,145: 334-343 |
| DOI |
https://dx.doi.org/10.1016/j.oceaneng.2017.09.009 |
| Abstract |
Optimising the operation and maintenance (O&M) and logistics strategy of offshore wind farms implies the decision problem of selecting the vessel fleet for O&M. Different strategic decision support tools can be applied to this problem, but much uncertainty remains regarding both input data and modelling assumptions. This paper aims to investigate and ultimately reduce this uncertainty by comparing four simulation tools, one mathematical optimisation tool and one analytic spreadsheet-based tool applied to select the O&M access vessel fleet that minimizes the total O&M cost of a reference wind farm. The comparison shows that the tools generally agree on the optimal vessel fleet, but only partially agree on the relative ranking of the different vessel fleets in terms of total O&M cost. The robustness of the vessel fleet selection to various input data assumptions was tested, and the ranking was found to be particularly sensitive to the vessels’ limiting significant wave height for turbine access. This is also the parameter with the greatest discrepancy between the tools, implying that accurate quantification and modelling of this parameter is crucial. The ranking is moderately sensitive to turbine failure rates and vessel day rates but less sensitive to electricity price and vessel transit speed
Highlights- Six decision support tools are applied to rank vessel fleets for O&M at an offshore wind farm.
- Their vessel fleet rankings are compared and associated uncertainties in input analyzed.
- The rankings show sensitivity to which decision support tool is used.
- The rankings are particularly sensitive to the vessels’ wave height limits.
This work was partly funded via IDCORE, the Industrial Doctorate Centre for Offshore Renewable Energy, which trains research engineers whose work in conjunction with sponsoring companies aims to accelerate the deployment of offshore wind, wave and tidal-current technologies |
| Associated Project(s) |
ETI-MA2003: Industrial Doctorate Centre for Offshore Renewable Energy (IDCORE) |
| Associated Dataset(s) |
No associated datasets |
| Associated Publication(s) |
A model to map levelised cost of energy for wave energy projects An Integrated Data Management Approach for Offshore Wind Turbine Failure Root Cause Analysis An investigation of the effects of wind-induced inclination on floating wind turbine dynamics: heave plate excursion Application of an offshore wind farm layout optimization methodology at Middelgrunden wind farm Characterisation of current and turbulence in the FloWave Ocean Energy Research Facility Characterization of the tidal resource in Rathlin Sound Comparison of Offshore Wind Farm Layout Optimization Using a Genetic Algorithm and a Particle Swarm Optimizer Component reliability test approaches for marine renewable energy Constraints Implementation in the Application of Reinforcement Learning to the Reactive Control of a Point Absorber Control of a Realistic Wave Energy Converter Model Using Least-Squares Policy Iteration Cost Reduction to Encourage Commercialisation of Marine in the UK Cumulative impact assessment of tidal stream energy extraction in the Irish Sea Design diagrams for wavelength discrepancy in tank testing with inconsistently scaled intermediate water depth Development of a Condition Monitoring System for an Articulated Wave Energy Converter Dynamic mooring simulation with Code(-)Aster with application to a floating wind turbine ETI Insights Report - Wave Energy Environmental interactions of tidal lagoons: A comparison of industry perspectives Exploring Marine Energy Potential in the UK Using a Whole Systems Modelling Approach Hybrid, Multi-Megawatt HVDC Transformer Topology Comparison for Future Offshore Wind Farms Hydrodynamic analysis of a ducted, open centre tidal stream turbine using blade element momentum theory Offshore wind farm electrical cable layout optimization Offshore wind installation vessels - A comparative assessment for UK offshore rounds 1 and 2 Optimisation of Offshore Wind Farms Using a Genetic Algorithm Quantifying uncertainty in acoustic measurements of tidal flows using a “Virtual” Doppler Current Profiler Re-creation of site-specific multi-directional waves with non-collinear current Reactive control of a two-body point absorber using reinforcement learning Reactive control of a wave energy converter using artificial neural networks Reliability and O & M sensitivity analysis as a consequence of site specific characteristics for wave energy converters Reliability prediction for offshore renewable energy: Data driven insights Resource characterization of sites in the vicinity of an island near a landmass Review and application of Rainflow residue processing techniques for accurate fatigue damage estimation Sensitivity analysis of offshore wind farm operation and maintenance cost and availability Simulating Extreme Directional Wave Conditions Testing Marine Renewable Energy Devices in an Advanced Multi-Directional Combined Wave-Current Environment The Industrial Doctorate Centre for Offshore Renewable Energy(IDCORE) - Case Studies The SPAIR method: Isolating incident and reflected directional wave spectra in multidirectional wave basins The effects of wind-induced inclination on the dynamics ofsemi-submersible floating wind turbines in the time domain The power-capture of a nearshore, modular, flap-type wave energy converter in regular waves UK offshore wind cost optimisation: top head mass (Presentation to All Energy, 10th May 2017) |
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