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Optimal Design and Maintenance of Offshore Wind Farms
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Optimal Design and Maintenance of Offshore Wind Farms

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: 5 July 2026 | Viewed by 510

Editors

Dr. Frances Judge

E-Mail Website
Guest Editor
School of Engineering and Architecture, MaREI Centre, Sustainability Institute, University College Cork, Cork, Ireland
Interests: offshore renewable energy
Dr. Jimmy Murphy

E-Mail Website
Guest Editor
School of Engineering and Architecture, MaREI Centre, Sustainability Institute, University College Cork, Cork, Ireland
Interests: coastal engineering; offshore renewable energy
Dr. Michael O’Shea

E-Mail Website
Guest Editor
School of Engineering and Architecture, MaREI Centre, Sustainability Institute, University College Cork, Cork, Ireland
Interests: coastal engineering; structural health monitoring; wave slamming; physical modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Offshore wind farms represent a cornerstone of the global transition to renewable energy, harnessing vast ocean winds to generate clean power. However, their deployment in harsh marine environments poses significant challenges, including high installation costs, structural fatigue, and operational disruptions from component failures that are exacerbated by inclement weather.

This Special Issue aims to explore innovative strategies for optimising the design, construction, and long-term maintenance of offshore wind farms, fostering sustainable and cost-effective solutions. Its scope encompasses multidisciplinary approaches, from engineering and materials science to logistics and economic modelling.

Papers related (but not limited) to the following topics will be taken into consideration:

  • Advancements in predictive maintenance (e.g., AI-driven), sensors, and robotics.
  • Novel turbine designs for extreme conditions.
  • Floating platforms and hybrid energy systems.
  • Integration of digital twins for real-time optimisation.
  • Autonomous systems like drones, robotic crawlers, and uncrewed vessels for safer cost-effective inspections of blades, foundations, and subsea infrastructure.

We seek original research articles, comprehensive reviews, and case studies that provide empirical data, theoretical models, or practical insights into offshore wind optimisation. Submissions should emphasise interdisciplinary collaboration and real-world applicability.

Dr. Frances Judge
Dr. Jimmy Murphy
Dr. Michael O’Shea
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • predictive maintenance
  • sustainable O&M solutions
  • autonomous systems and vessels
  • robotics
  • sensors
  • logistics

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Published Papers (1 paper)

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Research

32 pages, 2355 KB  
Article
Wind Inflow-State Discretisation Effects on Wake Loss and Annual Energy Production in Offshore Wind Farms
by J. William Flynn and Michael O’Shea
J. Mar. Sci. Eng. 2026, 14(12), 1118; https://doi.org/10.3390/jmse14121118 - 17 Jun 2026
Viewed by 133
Abstract
This paper examines how inflow-state discretisation affects wake-loss and annual energy production (AEP) estimates for offshore wind farms. A reproducible workflow is presented for constructing weighted inflow-state ensembles from long-term offshore wind datasets using empirical wind-speed–direction occurrence frequencies. Hub-height wind speeds are reconstructed [...] Read more.
This paper examines how inflow-state discretisation affects wake-loss and annual energy production (AEP) estimates for offshore wind farms. A reproducible workflow is presented for constructing weighted inflow-state ensembles from long-term offshore wind datasets using empirical wind-speed–direction occurrence frequencies. Hub-height wind speeds are reconstructed from multi-level wind data using a time-varying power–law shear exponent, after which the wind climatology is discretised using configurable directional sectors and wind-speed bins. The methodology was evaluated using both a controlled synthetic wind dataset and offshore climatological datasets processed through the same inflow-state and wake-modelling workflow. The analysis quantified how directional resolution, wind-speed bin width, and sector-mean inflow representations affect predicted turbine power, wake loss, and AEP relative to empirical reference cases. For the synthetic dataset, replacing the within-sector wind-speed distribution with a single sector-mean wind speed produced an annual power difference of 12.58%, with seasonal differences ranging from 6.66% in JJA to 13.91% in DJF. Offshore wake-model calculations showed the same overall behaviour. Reducing the empirical inflow-state ensemble from 1593 to 416 retained states changed annual AEP by only 0.03% and wake loss by −0.03 percentage points, whereas the sector-mean inflow representation increased predicted AEP by 18.40% and wake loss by 5.13 percentage points relative to the empirical reference case. The results show that preserving the within-sector wind-speed distribution has a larger influence on predicted wake loss and AEP than moderate reductions in retained state count or directional resolution for the datasets and layouts considered here. Empirical inflow-state ensembles using 36 directional sectors together with 1 ms−1 or 2 ms−1 wind-speed bins remained within 0.03% of the higher-resolution annual AEP reference while reducing the number of retained inflow states by approximately 74%, with a corresponding reduction in the number of wake-model evaluations required. Full article
(This article belongs to the Special Issue Optimal Design and Maintenance of Offshore Wind Farms)
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