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Open AccessArticle

Optimal Maintenance Management of Offshore Wind Farms

1
Ingenium Research Group, Universidad Castilla-La Mancha, 13071 Ciudad Real, Spain
2
CUNEF-Ingenium, Colegio Universitario de Estudios Financieros, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Frede Blaabjerg
Energies 2016, 9(1), 46; https://doi.org/10.3390/en9010046
Received: 30 October 2015 / Revised: 11 December 2015 / Accepted: 24 December 2015 / Published: 15 January 2016
(This article belongs to the Special Issue Wind Turbine 2015)
Nowadays offshore wind energy is the renewable energy source with the highest growth. Offshore wind farms are composed of large and complex wind turbines, requiring a high level of reliability, availability, maintainability and safety (RAMS). Firms are employing robust remote condition monitoring systems in order to improve RAMS, considering the difficulty to access the wind farm. The main objective of this research work is to optimise the maintenance management of wind farms through the fault probability of each wind turbine. The probability has been calculated by Fault Tree Analysis (FTA) employing the Binary Decision Diagram (BDD) in order to reduce the computational cost. The fault tree presented in this paper has been designed and validated based on qualitative data from the literature and expert from important European collaborative research projects. The basic events of the fault tree have been prioritized employing the criticality method in order to use resources efficiently. Exogenous variables, e.g., weather conditions, have been also considered in this research work. The results provided by the dynamic probability of failure and the importance measures have been employed to develop a scheduled maintenance that contributes to improve the decision making and, consequently, to reduce the maintenance costs. View Full-Text
Keywords: offshore; wind turbines; maintenance management; fault tree analysis; binary decision diagrams offshore; wind turbines; maintenance management; fault tree analysis; binary decision diagrams
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MDPI and ACS Style

Pliego Marugán, A.; García Márquez, F.P.; Pinar Pérez, J.M. Optimal Maintenance Management of Offshore Wind Farms. Energies 2016, 9, 46. https://doi.org/10.3390/en9010046

AMA Style

Pliego Marugán A, García Márquez FP, Pinar Pérez JM. Optimal Maintenance Management of Offshore Wind Farms. Energies. 2016; 9(1):46. https://doi.org/10.3390/en9010046

Chicago/Turabian Style

Pliego Marugán, Alberto; García Márquez, Fausto P.; Pinar Pérez, Jesús M. 2016. "Optimal Maintenance Management of Offshore Wind Farms" Energies 9, no. 1: 46. https://doi.org/10.3390/en9010046

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