Reliability optimization of wind farms considering redundancy and opportunistic maintenance strategy

2016 ◽  
Vol 112 ◽  
pp. 445-458 ◽  
Author(s):  
Karim Atashgar ◽  
Hadi Abdollahzadeh
Author(s):  
Chen Zhang ◽  
Wei Gao ◽  
Tao Yang ◽  
Sheng Guo ◽  
Honggang Ding

Corrective maintenance and preventive maintenance are two common maintenance strategies used in the wind farms, whose drawbacks are obvious and significant. Opportunistic maintenance strategy takes advantage of the dependencies existing among the wind turbine components and implement combined maintenance actions to reduce the huge downtime cost. The opportunistic maintenance strategy for wind turbines has made a great progress, as well as the strategy considering imperfect and condition-based maintenance. However, existing maintenance strategy researches are usually concerned with the maintenance itself and the effects of power generation are barely considered. Nowadays, a current research trend in manufacturing system is the integration of maintenance and production planning. In this paper, the effects of power generation on opportunistic maintenance strategy for wind turbines considering reliability are researched. The opportunistic maintenance reliability threshold is not constant and depends on the real-time power generation. Numerical examples are used to illustrate the economical advantages of this proposed strategy over traditional opportunistic maintenance strategy. Moreover, the optimal maintenance combination is also provided.


Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2036 ◽  
Author(s):  
Juan Izquierdo ◽  
Adolfo Crespo Márquez ◽  
Jone Uribetxebarria ◽  
Asier Erguido

The growth in the wind energy sector is demanding projects in which profitability must be ensured. To fulfil such aim, the levelized cost of energy should be reduced, and this can be done by enhancing the Operational Expenditure through excellence in Operations & Maintenance. There is a considerable amount of work in the literature that deals with several aspects regarding the maintenance of wind farms. Among the related works, several focus on describing the reliability of wind turbines and many set the spotlight on defining the optimal maintenance strategy. It is in this context where the presented work intends to contribute. In the paper a technical framework is proposed that considers the data and information requisites, integrated in a novel approach a clustering-based reliability model with a dynamic opportunistic maintenance policy. The technical framework is validated through a case study in which simulation mechanisms allow the implementation of a multi-objective optimization of the maintenance strategy for the lifecycle of a wind farm. The proposed approach is presented under a comprehensive perspective which enables the discovery an optimal trade-off among competing objectives in the Operations & Maintenance of wind energy projects.


2015 ◽  
Vol 30 (8) ◽  
pp. 2981-2997 ◽  
Author(s):  
M’hammed Sahnoun ◽  
David Baudry ◽  
Navonil Mustafee ◽  
Anne Louis ◽  
Philip Andi Smart ◽  
...  

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2650 ◽  
Author(s):  
Lubing Xie ◽  
Xiaoming Rui ◽  
Shuai Li ◽  
Xin Hu

Owing to the late development of offshore wind power in China, operational data and maintenance experience are relatively scarce. Due to the harsh environmental conditions, a reliability analysis based on limited sample fault data has been regarded as an effective way to investigate maintenance optimization for offshore wind farms. The chief aim of the present work is to develop an effective strategy to reduce the maintenance costs of offshore wind turbines in consideration of their accessibility. The three-parameter Weibull distribution method was applied to failure rate estimation based on limited data. Moreover, considering the impacts of weather conditions on the marine maintenance activities, the Markov method and dynamic time window were used to depict the weather conditions. The opportunistic maintenance strategy was introduced to cut down on the maintenance costs through optimization of the preventive maintenance age and opportunistic maintenance age. The simulation analysis we have performed showed that the maintenance costs of the opportunistic maintenance strategy were 10% lower than those of the preventive maintenance strategy, verifying the effectiveness of the proposed maintenance strategy.


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