2022
DOI: 10.3390/app12031762
|View full text |Cite
|
Sign up to set email alerts
|

SCADA-Compatible and Scaleable Visualization Tool for Corrosion Monitoring of Offshore Wind Turbine Structures

Abstract: The exploitation of offshore windfarms (WFs) goes hand in hand with large capital expenditures (CAPEX) and operational expenditures (OPEX), as these mechanical installations operate continuously for multiple decades in harsh, saline conditions. OPEX can account for up to 30% of the levelised cost of energy (LCoE) for a deployed offshore wind farm. To maintain the cost-competitiveness of deployed offshore WFs versus other renewable energy sources, their LCoE has to be kept in check, both by minimising the OPEX … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
8
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
7
2
1

Relationship

1
9

Authors

Journals

citations
Cited by 11 publications
(8 citation statements)
references
References 10 publications
0
8
0
Order By: Relevance
“…These models not only contribute to the sustainable development of the wind power industry but also help wind power plant managers and operators to optimize the performance and efficiency of wind turbines. Verhelst et al [138] developed corrosion measurement data visualization software that identifies standards for effective structural corrosion analysis as a scalable, SCADA-compatible, secure, and network-accessible tool, showing that SCADA-compatible visualization software tools are possible and can significantly reduce the technical and experiential requirements for O&M service personnel. However, since it is difficult to quantify the corrosion process theoretically, both the quantity and quality of data are extremely important, which also requires relevant organizations to raise risk awareness and collect adequate data in a timely manner.…”
Section: Decision Support Systemsmentioning
confidence: 99%
“…These models not only contribute to the sustainable development of the wind power industry but also help wind power plant managers and operators to optimize the performance and efficiency of wind turbines. Verhelst et al [138] developed corrosion measurement data visualization software that identifies standards for effective structural corrosion analysis as a scalable, SCADA-compatible, secure, and network-accessible tool, showing that SCADA-compatible visualization software tools are possible and can significantly reduce the technical and experiential requirements for O&M service personnel. However, since it is difficult to quantify the corrosion process theoretically, both the quantity and quality of data are extremely important, which also requires relevant organizations to raise risk awareness and collect adequate data in a timely manner.…”
Section: Decision Support Systemsmentioning
confidence: 99%
“…Indeed, uniform corrosion may reduce the steel wall of the wind turbine structure beyond its corrosion allowance, at which point the structure reaches the end of useful life. The thickness of the steel wall of the wind turbine structure can be continuously measured using ultrasound sensors mounted on the interior side of the wall [4,5] and corrosion information (including corrosion prognosis) can then be visualized for the onshore wind farm operator [6]. We remark that ultrasound is but one possible technique to monitor corrosion, see, e.g., [7], where electrochemical techniques are used instead of ultrasound.…”
Section: Introductionmentioning
confidence: 99%
“…To support a systematic corrosion assessment and management of OWTs, an integrated system/solution that is able to handle corrosion monitoring data and to transform and visualize the data into actionable information is therefore required for the offshore wind energy industry. However, to the authors' knowledge, as discussed in previous works [8,9], tools and solutions that can serve the aforementioned purpose are still very limited and not mature yet.…”
Section: Introductionmentioning
confidence: 99%