Verification of discrete-event-simulation-based O&M models for floating offshore wind

Abstract. Floating offshore wind offers access to deep-water wind resources but remains challenged by high and uncertain operation and maintenance (O&M) costs. Discrete-event simulation (DES) models are widely used to evaluate O&M strategies, yet variations in modeling assumptions often lead to inconsistent estimates and limit confidence in their use for decision support. This study applies a structured verification framework to examine how key assumptions influence O&M simulation outcomes using two DES-based models configured with a deep-water floating-wind reference case. While maintenance cost estimates remain broadly consistent across models, substantial differences arise in wind farm availability and in downtime-related revenue losses, which constitute a major share of total O&M costs. This discrepancy is driven primarily by how turbine operational states are represented during maintenance activities, including technician off-shift periods and tow-to-port operations. Quantifying the influence of these assumptions provides generalizable insight relevant to the wider O&M modeling community, where such choices are implemented inconsistently between different models. Building on the verified modeling foundation, several alternative O&M strategies including service operation vessel-based logistics, floating-to-floating major component replacement, and condition-based maintenance are evaluated, yielding total O&M cost reductions of up to 5 % in the examined case. The findings strengthen model transparency and reproducibility while demonstrating how verified simulation tools can support the assessment of emerging operational concepts in floating offshore wind.

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Publication Details

Journal
Wind energy science
Published
2026-08-25
DOI
https://doi.org/10.5194/wes-11-3031-2026
Primary Topic
Wave and Wind Energy Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Verification of discrete-event-simulation-based O&M models for floating offshore wind

Rob Hammond, L. H. Huang, Daniel Mulas Hernando, Simone Mancini
Wind energy science
Wave and Wind Energy Systems
article

Verification of discrete-event-simulation-based O&M models for floating offshore wind

Rob Hammond, L. H. Huang, Daniel Mulas Hernando, Simone Mancini
article en

Abstract

Abstract. Floating offshore wind offers access to deep-water wind resources but remains challenged by high and uncertain operation and maintenance (O&M) costs. Discrete-event simulation (DES) models are widely used to evaluate O&M strategies, yet variations in modeling assumptions often lead to inconsistent estimates and limit confidence in their use for decision support. This study applies a structured verification framework to examine how key assumptions influence O&M simulation outcomes using two DES-based models configured with a deep-water floating-wind reference case. While maintenance cost estimates remain broadly consistent across models, substantial differences arise in wind farm availability and in downtime-related revenue losses, which constitute a major share of total O&M costs. This discrepancy is driven primarily by how turbine operational states are represented during maintenance activities, including technician off-shift periods and tow-to-port operations. Quantifying the influence of these assumptions provides generalizable insight relevant to the wider O&M modeling community, where such choices are implemented inconsistently between different models. Building on the verified modeling foundation, several alternative O&M strategies including service operation vessel-based logistics, floating-to-floating major component replacement, and condition-based maintenance are evaluated, yielding total O&M cost reductions of up to 5 % in the examined case. The findings strengthen model transparency and reproducibility while demonstrating how verified simulation tools can support the assessment of emerging operational concepts in floating offshore wind.

Wind energy scienceVol. 11(8)
Netherlands Organisation for Applied Scientific Research (NL), Agence internationale de l'énergie (FR)
Strong, Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek
Affordable and clean energy
Openalex Percentile: Top 14%
Wave and Wind Energy Systems
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