Seismic Performance of Multimegawatt Offshore Wind Turbines in Liquefiable Soil under Horizontal and Vertical Motions

Deterioration processes such as fatigue and corrosion are typically affecting offshore structures. To “control” this deterioration, inspection and maintenance activities are developed. Probabilistic methodologies represent an important tool to identify the suitable strategy to inspect and control the deterioration in structures such as offshore wind turbines (OWT). Besides these methods, the integration of condition monitoring information (CMI) can optimize the mitigation activities as an updating tool. In this paper, a framework for risk-based inspection and maintenance planning (RBI) is applied for OWT incorporating CMI, addressing this analysis to fatigue prone details in welded steel joints at jacket or tripod steel support structures for offshore wind turbines. The increase of turbulence in wind farms is taken into account by using a code-based turbulence model. Further, additional modes t integrate CMI in the RBI approach for optimal planning of inspection and maintenance. As part of the results, the life cycle reliabilities and inspection times are calculated, showing that earlier inspections are needed at in-wind farm sites. This is expected due to the wake turbulence increasing the wind load. With the integration of CMI by means Bayesian inference, a slightly change of first inspection times are coming up, influenced by the reduction of the uncertainty and harsher or milder external agents.

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Comparison of the dynamic responses of monopiles and gravity base foundations for offshore wind turbines in sand using centrifuge modelling

SOILS AND FOUNDATIONS ◽

10.1016/j.sandf.2020.10.009 ◽

2020 ◽

Author(s):

Marcos Massao Futai ◽

Stuart K. Haigh ◽

Gopal S.P. Madabhushi

Keyword(s):

Wind Turbines ◽

Dynamic Responses ◽

Offshore Wind ◽

Centrifuge Modelling ◽

Offshore Wind Turbines

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Improving the Strategy of Maintaining Offshore Wind Turbines through Petri Net Modelling

Applied Sciences ◽

10.3390/app11020574 ◽

2021 ◽

Vol 11 (2) ◽

pp. 574

Author(s):

Rundong Yan ◽

Sarah Dunnett

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Petri Net ◽

Offshore Wind ◽

Offshore Wind Turbine ◽

Maintenance Costs ◽

Offshore Wind Turbines ◽

Major Repair ◽

Wind Turbine System ◽

Periodic Maintenance

In order to improve the operation and maintenance (O&M) of offshore wind turbines, a new Petri net (PN)-based offshore wind turbine maintenance model is developed in this paper to simulate the O&M activities in an offshore wind farm. With the aid of the PN model developed, three new potential wind turbine maintenance strategies are studied. They are (1) carrying out periodic maintenance of the wind turbine components at different frequencies according to their specific reliability features; (2) conducting a full inspection of the entire wind turbine system following a major repair; and (3) equipping the wind turbine with a condition monitoring system (CMS) that has powerful fault detection capability. From the research results, it is found that periodic maintenance is essential, but in order to ensure that the turbine is operated economically, this maintenance needs to be carried out at an optimal frequency. Conducting a full inspection of the entire wind turbine system following a major repair enables efficient utilisation of the maintenance resources. If periodic maintenance is performed infrequently, this measure leads to less unexpected shutdowns, lower downtime, and lower maintenance costs. It has been shown that to install the wind turbine with a CMS is helpful to relieve the burden of periodic maintenance. Moreover, the higher the quality of the CMS, the more the downtime and maintenance costs can be reduced. However, the cost of the CMS needs to be considered, as a high cost may make the operation of the offshore wind turbine uneconomical.

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Offshore Wind Energy Resource Assessment across the Territory of Oman: A Spatial-Temporal Data Analysis

Sustainability ◽

10.3390/su13052862 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2862

Author(s):

Amer Al-Hinai ◽

Yassine Charabi ◽

Seyed H. Aghay Kaboli

Keyword(s):

Data Analysis ◽

Wind Energy ◽

Wind Turbines ◽

Energy Resource ◽

Wind Farms ◽

Offshore Wind ◽

Wind Data ◽

Offshore Wind Energy ◽

Offshore Wind Turbines ◽

Wind Potential

Despite the long shoreline of Oman, the wind energy industry is still confined to onshore due to the lack of knowledge about offshore wind potential. A spatial-temporal wind data analysis is performed in this research to find the locations in Oman’s territorial seas with the highest potential for offshore wind energy. Thus, wind data are statistically analyzed for assessing wind characteristics. Statistical analysis of wind data include the wind power density, and Weibull scale and shape factors. In addition, there is an estimation of the possible energy production and capacity factor by three commercial offshore wind turbines suitable for 80 up to a 110 m hub height. The findings show that offshore wind turbines can produce at least 1.34 times more energy than land-based and nearshore wind turbines. Additionally, offshore wind turbines generate more power in the Omani peak electricity demand during the summer. Thus, offshore wind turbines have great advantages over land-based wind turbines in Oman. Overall, this work provides guidance on the deployment and production of offshore wind energy in Oman. A thorough study using bankable wind data along with various logistical considerations would still be required to turn offshore wind potential into real wind farms in Oman.

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