Reducing the Levelised Cost of Energy (LCOE) is critical for the widespread adoption of floating offshore wind (FOW). Achieving this requires computational models that can accurately estimate LCOE by capturing the full life cycle of FOW farms, including manufacturing, installation, operation and maintenance, and end-of-life phases. These models must balance sufficient detail to represent each operational phase with computational efficiency to allow rapid evaluation of multiple scenarios. However, the installation phase is often oversimplified in existing LCOE models [1,2], typically represented by parametric cost equations. This limits the ability to capture the operational and logistical complexities of deploying FOW farms, which can significantly affect costs (particularly the capital cost) and project feasibility estimations.

An existing detailed optimisation-simulation-based model characterise the installation phase with high fidelity [3]. While providing valuable insights into vessel operations, task sequencing and weather dependencies, the high computational cost prevents direct integration into LCOE frameworks. This underscores the need for installation models that retain operational detail while remaining compatible with life-cycle cost assessments, enabling efficient evaluation of the full project lifecycle.

The present study addresses this gap by developing a Discrete Event Simulation (DES)-based installation model that is both comprehensive and computationally efficient, enabling its integration into LCOE models. The framework bridges the gap between detailed installation simulations and high-level LCOE models, maintaining fidelity in vessel operations, weather delays, component logistics and sequencing constraints, while reducing computational burden compared to full time-domain simulations.

The DES-based model represents sequential and interdependent operations in FOW installation. It captures key phases including anchoring, towing, hook-up and cable laying, while accounting for vessel availability, metocean conditions and operational weather limits. Each operation is treated as a discrete event, with timing and duration influenced by stochastic weather windows derived from site-specific metocean data. Vessel activities, including transit, standby and active installation periods, are explicitly simulated to estimate utilisation, fuel consumption and charter costs, providing a realistic view of installation logistics.

A case study will demonstrate how integrating this computationally efficient installation model into LCOE frameworks improves life-cycle cost estimates. It will examine the impact of installation strategies, vessel configurations and weather downtime on project economics. A sensitivity analysis will further explore the effects of different logistical scenarios, farm sizes and site conditions on installation duration and costs. By combining operational fidelity with efficiency, the proposed model offers a practical tool for early-stage project planning, techno-economic optimisation and uncertainty assessment, supporting LCOE reduction for FOW farms.

1. Martinez, A. (2022). Mapping of the levelised cost of energy for floating offshore wind in the European Atlantic. Renewable and Sustainable Energy Reviews.
2. Centeno-Telleria, M (2024). O&M-aware techno-economic assessment for floating offshore wind farms: A geospatial evaluation off the North Sea and the Iberian Peninsula. Applied Energy.
3. Halvorsen-Weare, E.E., Fonn, E., Johannessen, K., Kisialiou, Y., Nonås, L.M., Rialland A., & Thun, K. (2021). A computer tool for optimisation and simulation of marine operations for offshore wind farm installation. Journal of Physics: Conference Series, 2018, 012021.

As opposed to the bottom-fix wind turbine, the installation of Floating Offshore Wind Turbines (FOWTs) can benefit from its self-floating stability, making it possible to tow the assembled system (floater, tower, rotor-nacelle-assembly) from harbour to the installation site at once. This paper describes a methodology for simulating the towing of a fully assembled DeepCwind OC4 reference FOWT using OpenFAST. Although OpenFAST is an open-source software, the wave diffraction and radiation forces in the HydroDyn module are computed based on the output of an external boundary element method (BEM) solver. To that end, a comparative analysis is performed to compare the results of four BEM solvers: i) Capytaine, ii) HAMS, iii) Nemoh and iv) OrcaWave. The latter is a closed-source commercial software, whereas the others are open-source. Firstly, the zero-speed radiation coefficients and excitation forces computed by the four different BEM solvers are compared in the frequency-domain. A close agreement is found in the results from Capytaine and Nemoh, due to the inherently similar Green’s function evaluation in both codes to solve the boundary integral problem. Secondly, the resulting infinite added mass and impulse response functions (IRF) matrices are compared, which will serve as inputs for OpenFAST. In the time-domain, the response amplitude operators (RAOs) for heave and pitch motions are computed from the OpenFAST results and compared with the experimental data. The RAOs showed good agreement with the experimental data for lower encounter frequencies and lower towing speeds. Presently, Nemoh is the only open-source BEM solver capable of computing second-order wave loads. The impact of modeling the second-order wave forces is also analyzed in this paper, which is important to predict the towing resistance in waves. Overall, this study highlights the limitations, ease of use, computational time, and accuracy produced by the three open-source BEM solvers as inputs to simulate the towing of FOWTs in OpenFAST.

This study presents a computational fluid dynamics (CFD) investigation of vortex-induced motions (VIM) of the INO WINDMOOR floater [1] during towing operations. The simulations were performed at model scale for direct comparison with towing tests of INO WINDMOOR FOWT model previously conducted in SINTEF Ocean’s Ocean Basin [2]. Two towing configurations were examined: one single towing line and towing line with bridles.

The CFD setup includes a free surface and fully coupled six-degree-of-freedom (6DOF) body motion, solved using the overset mesh approach combined with the Improved Delayed Detached-Eddy Simulation (IDDES) turbulence model. The simulations successfully reproduced VIM responses in both configurations and showed encouraging qualitative agreement with experimental observations. In particular, the relative motion trends between the two towing setups were captured correctly, demonstrating the ability of CFD to distinguish which configuration induces larger motion in each DOF.

While some overprediction of amplitudes was observed for certain DOF, the results remain within reasonable bounds and highlight areas for further calibration. The very small free-surface waves observed at low Froude numbers suggest that simplified single-phase simulations may be sufficient for calm-water towing conditions. To explore this, sensitivity tests without the free surface have been initiated, and comparative results will be presented at the conference.

Overall, the study demonstrates the feasibility and potential of using CFD to reproduce VIM phenomena of a FOWT under towing operations. The findings provide valuable insights for future model development, validation, and towing configuration design for floating wind applications.

References
[1] Silva de Souza, C. E., Berthelsen, P. A., Eliassen, L., Bachynski, E., Engebretsen, E., & Haslum, H. (2022). Definition of the INO WINDMOOR 12 MW Base Case Floating Wind Turbine. SINTEF Ocean, Report No. OC2020 A-044 – Unrestricted.
[2] Yin, D., Indergård, R., Lie, H., & Braaten, H. (2024). Experimental Investigation of Towing of a Semi-submersible Floating Offshore Wind Turbine. Journal of Physics: Conference Series, vol. 2875, no. 012026, 2024