the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Dec 2024
Developing an atlas of rain-induced leading edge erosion for wind turbine blades in the Dutch North Sea
Abstract. To support the ongoing development of offshore wind energy in The Netherlands and to maintain the current assets, it is essential to provide wind farm operators accurate estimates of wind turbine blade erosion. Unfortunately, there is currently a shortage of information on wind turbine erosion risk, especially in offshore regions. In this work, we developed an atlas detailing rain-induced leading edge erosion for wind turbine blades in the Dutch North Sea, using weather simulations spanning a decade. These weather simulations were validated using recent offshore and onshore measurements and incorporated into a fatigue-based damage model, linking weather conditions to blades’ leading edge erosion. The results reveal that the erosive impact of rainfall on wind turbine blades varies across the Dutch North Sea. The estimated average incubation period, which indicates the leading edge protection system's lifespan, ranges from 8 to 9 years in the southwestern region, decreasing to 6 to 7 years in the northeastern area. This is due to both the higher average wind speeds and greater rainfall amounts occurring in the northeastern locations compared to the southwestern ones. This paper emphasizes that the northeastern regions of the Dutch North Sea, which are being examined for potential wind farm developments post-2030, will encounter higher erosion risks compared to those currently operating in southern locations, possibly requiring enhanced mitigation strategies.
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Status: open (until 27 Feb 2025)
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RC1: 'Comment on wes-2024-174', Anonymous Referee #1, 18 Feb 2025
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Summary for editor:
The main message of this study, emphasized both in the conclusion and the abstract, is that there is a higher risk of erosion-damage on planned Dutch off-shore wind farms in the North Eastern waters than in the South, because both rain amount and wind speeds are higher in the North East. As a scientific contribution, I find this message to be somewhat trivial, and one that could have been reached with much less effort than is presented in the paper. In general, the work reads rather like a project report, explaining what the authors have done rather than a scientific study that others can learn from. In addition, several of their statements are simply not correct. Despite some impressive material, I therefore suggest that the paper is reconsidered after major revisions or rejected, such that the authors have sufficient time to rethink their study. Â Â
Specific comments:
- In the introduction, the authors mention that “The literature review reveals a significant gap in knowledge regarding the large-scale mapping of rain erosion risks for wind turbine blades, particularly in the Dutch North Sea.” A large part of the Dutch North Sea is however covered in the erosion atlas based on the NORA3 simulations from Hannisdottir et al 2024b, which is cited in the previous paragraph. The authors also critique the Hannisdottir study based on the course resolution of reanalysis data, but in the end they do not utilize the high-resolution data that they themselves generate. There seems to be no need for this study, because the NORA3 reanalysis covers the Dutch North Sea, and such data could easily have underpinned the claimed main conclusion of the study. Further, the authors should very clearly state the literature regarding all rain erosion atlases to help the reader understand their contribution.Â
- Although not explicitly mentioned as an objective, I believe that the authors wish to formulate an alternative way of constructing a rain erosion atlas than what has been done before. By not acknowledging this objective, and by not comparing their detailed methods with already published methods, a reader cannot understand what the new methodology brings to the field. The authors should focus on the complementary aspects of a new methodology and what the difference between their results and already published data can teach the community regarding direction forwards for the development of erosion risk atlases. (They could also focus it on the pros and cons of the LES based approach in comparison with re-analysis or meso-scale simulations, which is currently not covered at sufficient depth in the study.)
- In the abstract, the authors claim to have validated their model runs using in-situ wind and rain observations. This would normally mean that the estimates of the models can be trusted within a certain error margin. However, the use of the word “validation” is here very questionable, because the estimates of the models are as much as several 100% different from the observations (see table 2). In the text, the authors claim that the models capture trends of the erosion related parameters effectively, but this is not generally correct (for example, regarding the accumulated rain amount, which show different relative behaviors for the three sites in observations and simulations). In summary, the authors do not validate the models. In the introduction, the authors mention that the LES simulations are performed to verify the meso-scale simulations. However, the meso-scale simulations show a better performance concerning wind modeling and the precipitation fields of the models are not compared in any meaningful way to justify the impression that the authors communicate regarding the LES model’s superiority. No side-by side rain and wind fields are shown to document the LES model’s strengths or weaknesses.
- Interestingly, the authors state that the LES based approach is better at capturing extreme events, without showing this important aspect in the paper! Instead, they only show results regarding rain-intensity in the high-resolution simulations (Figure 2), but here they omit to show the results from the meso-scale simulations. This omission is problematic, because it is important to show the comparison for the simulation that the atlas is based on. In general, neither approach is well evaluated, and it is hard to judge the pros and cons of their methods based on the presented results.
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- For erosion studies on wind turbines, a key parameter is the incubation period (IP), which is the life-time of the leading-edge-protection system. I find the low numbers in the last column in Table 2 here (and elsewhere) highly problematic, mainly because they are not discussed. The measurement data indicates that the IP at the offshore LEG site is little more than two years. The overall result of this study indicates that it would be significantly shorter in the planned wind farms in the North, which, in turn, would indicate that these wind farms’ O&M costs would be enormous. It is important to discuss what these low numbers mean in terms of cost-efficient operation of wind farms. Do they put a question mark on all the North Sea wind exploitation plans? Or is this low number simply a reflection of  the methods behind the IP estimation are incorrect?
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- The results in the Figures 3-5 are not very easy to understand, partly based on the absolute numbers used (with very many decimals). The authors should normalize the numbers such that deviations can be seen in per cent. Also, the results from both models should be shown.
- Another reason for recommending the rejection of this paper is that the authors fail to report a conflict of interest, although they are presenting results from a commercial tool in a core area of the company that produces this tool. One of the authors is hired by this company and the other seems to have strong links to it via project funding. Hence, there is an obvious conflict of interest, and by not acknowledging it, the presented research cannot be judged in a transparent way by readers. The results regarding the LES simulations are of high scientific interest, but we can only take these results seriously if we trust the presented work. To acknowledge their obvious conflict of interest is a first step towards creating such trust. Many authors mistake the existence of conflict of interests with scientific misconduct. However, it is only misconduct if the situation is not acknowledged (in a European context, this is elaborated here H2020 INTEGRITY - Conflict of interest in research: what is it and why it matters?).
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Minor comments:
Lines 150-153: The authors write However, it is essential to note that DSD measurements obtained from current sensors, such as disdrometers, remain quite uncertain (Letson and Pryor, 2023; Caboni et al., 2024; Asta Hannesdottir et al., 2024a). This is due to the fact that these sensors and their algorithms are typically optimized to accurately detect total precipitation amounts rather than the DSD itself. This is not correct. The disdrometers are made to detect droplets; Â not optimized for rain rates, which is a derived parameter from the instrument (see Johannsen et al 2020). Â Precipitation measurement from different types of disdrometers also vary (Angulo-Martinez et al 2018) .
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Johannsen LL, Zambon N, Strauss P, Dostal T, Neumann M, Zumr D, Cochrane TA, Blöschl G, Klik A. Comparison of three types of laser optical disdrometers under natural rainfall conditions. Hydrol Sci J. 2020 Jan 21;65(4):524-535. doi: 10.1080/02626667.2019.1709641.
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Angulo-MartĂnez, M., BeguerĂa, S., Latorre, B., and Fernández-Raga, M.: Comparison of precipitation measurements by OTT Parsivel2 and Thies LPM optical disdrometers, Hydrol. Earth Syst. Sci., 22, 2811–2837, https://doi.org/10.5194/hess-22-2811-2018, 2018.
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Figure 7: The legends should not block the data shown.
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Citation: https://doi.org/10.5194/wes-2024-174-RC1 - In the introduction, the authors mention that “The literature review reveals a significant gap in knowledge regarding the large-scale mapping of rain erosion risks for wind turbine blades, particularly in the Dutch North Sea.” A large part of the Dutch North Sea is however covered in the erosion atlas based on the NORA3 simulations from Hannisdottir et al 2024b, which is cited in the previous paragraph. The authors also critique the Hannisdottir study based on the course resolution of reanalysis data, but in the end they do not utilize the high-resolution data that they themselves generate. There seems to be no need for this study, because the NORA3 reanalysis covers the Dutch North Sea, and such data could easily have underpinned the claimed main conclusion of the study. Further, the authors should very clearly state the literature regarding all rain erosion atlases to help the reader understand their contribution.Â
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