Modelling and simulation of the operation and maintenance of offshore wind turbines

Fernando Santos, Ângelo P Teixeira and C Guedes Soares

Journal of Risk and Reliability, 2015, vol. 229, issue 5, 385-393

Abstract: The offshore environment limits the accessibility to the wind turbines and subjects them to faster degradation processes than in onshore. Thus, operation and maintenance is more challenging and costly and represents a considerable share of the cost of energy. It is therefore important to identify which factors most influence the turbines’ performance, namely, the availability, overall cost and revenues, so that actions can be taken to minimize their effect. This article addresses such issues by presenting a parametric study on how the variation of failure and repair models, vessels logistic times, weather windows and waiting times affect a wind turbine performance. Offshore failure models/data were not usually available on the public domain, being obtained herein from onshore ones using an empirical approach based on stress factors for mechanical systems. The baseline model results from the optimization of an operation and maintenance strategy based on corrective maintenance replacements and imperfect age-based preventive maintenance repairs. Generalized stochastic Petri nets with predicates coupled with Monte Carlo simulation are used for modelling and simulation. Results are discussed.

Keywords: Maintenance; modelling; simulation; Petri nets; offshore wind turbine; performance influencing factors (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X15589209 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:229:y:2015:i:5:p:385-393

DOI: 10.1177/1748006X15589209

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().