The effect of sea ice on offshore wind farm operation and maintenance
Bibliographic record
Abstract
Abstract The growth of offshore wind energy has led to installation in regions with challenging environmental conditions, such as high levels of sea ice, that can limit site accessibility, increase turbine downtime, and raise energy costs. This study examines the impact of sea ice on offshore wind farms, focusing on accessibility, availability, and operational costs. While ice-breaking vessels are widely used in shipping, their role in offshore wind operations remains largely unexplored. Some companies are investing in these vessels, but none have advanced beyond the construction phase. To address this gap, an O&M model is adapted to simulate sea ice conditions at three offshore wind farms: the Baltic Sea (Finland), the Bohai Sea (China), and Nova Scotia (Canada). These locations experience varying ice thickness, concentration and duration, with Nova Scotia facing four months of sea ice, while the Bohai Sea experiences only two. Case studies assess different classifications of ice-breaking vessels, ranging from those with no ice-breaking capability to Polar Class 1 vessels, that can break up to 3 metres of ice. Results indicate that in the Baltic Sea, an PC6-class ice-breaking vessel improves availability by 2.43% compared to a non-ice-breaking vessel, while the Bohai Sea sees a smaller 0.75% increase in availability due to an average lower amount of ice. However, wind farm availability plateaus once a sufficient ice-breaking capability is reached. Climate variability significantly influences outcomes, with the Canadian site experiencing up to 53 days on average per year where the site is inaccessible with no ice breaking vessels. A cost-benefit analysis evaluates the financial implications of ice-breaking vessels, finding that operational costs are significantly higher for the wind farm when no ice breaking vessels are used compared to the same wind farm utilising a ice vessel class of IB or higher. Findings provide a baseline for wind farm operators to assess the feasibility of incorporating ice-breaking strategies into maintenance planning, ultimately improving offshore wind farm performance in ice-prone regions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".