{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T03:40:10Z","timestamp":1776138010700,"version":"3.50.1"},"reference-count":30,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2015,6,8]],"date-time":"2015-06-08T00:00:00Z","timestamp":1433721600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability"],"published-print":{"date-parts":[[2015,10]]},"abstract":"<jats:p>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\u2019 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.<\/jats:p>","DOI":"10.1177\/1748006x15589209","type":"journal-article","created":{"date-parts":[[2015,6,8]],"date-time":"2015-06-08T22:00:47Z","timestamp":1433800847000},"page":"385-393","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":19,"title":["Modelling and simulation of the operation and maintenance of offshore wind turbines"],"prefix":"10.1177","volume":"229","author":[{"given":"Fernando","family":"Santos","sequence":"first","affiliation":[{"name":"Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior T\u00e9cnico, Universidade de Lisboa, Lisboa, Portugal"}]},{"given":"\u00c2ngelo P","family":"Teixeira","sequence":"additional","affiliation":[{"name":"Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior T\u00e9cnico, Universidade de Lisboa, Lisboa, Portugal"}]},{"given":"C Guedes","family":"Soares","sequence":"additional","affiliation":[{"name":"Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior T\u00e9cnico, Universidade de Lisboa, Lisboa, Portugal"}]}],"member":"179","published-online":{"date-parts":[[2015,6,8]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Global Wind Energy Council (GWEC). Global Wind REPORT annual market update 2013. GWEC Brussels April 2014."},{"key":"e_1_3_2_3_2","unstructured":"The European Wind Energy Association (EWEA). Wind in our Sails \u2013 the coming of Europe\u2019s offshore wind energy industry. EWEA Brussels November 2011."},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1049\/PBRN013E"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2010.07.007"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2014.11.045"},{"key":"e_1_3_2_7_2","volume-title":"Proceedings of IEEE Bucharest PowerTech conference","author":"Besnard F","unstructured":"Besnard F, Patriksson M, Stromberg AB, . An optimization framework for opportunistic maintenance of offshore wind power system. In: Proceedings of IEEE Bucharest PowerTech conference, Bucharest, 28 June\u20132 July 2009. 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London: Taylor & Francis Group, 2015, pp.1141\u20131146."},{"key":"e_1_3_2_12_2","first-page":"455","volume-title":"Risk and reliability in marine technology","author":"Signoret J-P","year":"1986","unstructured":"Signoret J-P. Availability of petroleum installations using Markov processes and Petri net modelling. In: Guedes Soares C (ed.) Risk and reliability in marine technology. Rotterdam: Balkema, 1986, pp.455\u2013472."},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1201\/b10572"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2008.06.002"},{"key":"e_1_3_2_15_2","unstructured":"Lindoe Offshore Renewables Center (LORC) foundation http:\/\/www.lorc.dk\/offshore-wind-farms-map\/alpha-ventus?os_c=Germany (2011 accessed 15 April 2013)."},{"key":"e_1_3_2_16_2","unstructured":"International Energy Agency (IEA). IEA wind 2011 annual report. IEA Boulder CO July 2012."},{"key":"e_1_3_2_17_2","unstructured":"Rademakers LW Braam H. O&M aspects of the 500 MW offshore wind farm at NL7 (80\u2009\u00d7\u20096 MW turbines) \u2013 baseline configuration. Report for DOWEC. Report no. 10080 rev 2 July 2002 https:\/\/www.ecn.nl\/fileadmin\/ecn\/units\/wind\/docs\/dowec\/10080_002.pdf"},{"key":"e_1_3_2_18_2","volume-title":"A guide to an offshore wind farm","author":"BVG Associates","unstructured":"BVG Associates. A guide to an offshore wind farm. London: The Crown Estate."},{"key":"e_1_3_2_19_2","first-page":"1329","volume-title":"Maritime technology and engineering","author":"Martins D","year":"2015","unstructured":"Martins D, Muraleedharan G, Guedes Soares C. Weather window analysis of a site off Portugal. In: Guedes Soares C, Santos TA (eds) Maritime technology and engineering. 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MSc Thesis KTH School of Electrical Engineering Stockholm 2006."},{"key":"e_1_3_2_25_2","unstructured":"Durstewitz M. Windenergie report Deutschland 2004\u20132005. Institut f\u00fcr Solare Energieversorgungstechnik (ISET) Kassel 2005."},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/5.24143"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0951-8320(96)00108-1"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2008.03.024"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1201\/b12726-62"},{"key":"e_1_3_2_30_2","volume-title":"32nd international conference on ocean, offshore and arctic engineering (OMAE 2013)","author":"Santos FP","unstructured":"Santos FP, Teixeira AP, Guedes Soares C. Maintenance planning of an offshore wind turbine using stochastic Petri nets with predicates. In: 32nd international conference on ocean, offshore and arctic engineering (OMAE 2013), Nantes, 9\u201314 June 2013, paper no. 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