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dc.contributor.authorDu, Mianes-ES
dc.contributor.authorYi, Junes-ES
dc.contributor.authorMazidi, Peymanes-ES
dc.contributor.authorCheng, Lines-ES
dc.contributor.authorGuo, Jianboes-ES
dc.date.accessioned2017-01-19T04:06:18Z
dc.date.available2017-01-19T04:06:18Z
dc.identifier.urihttp://hdl.handle.net/11531/16204
dc.description.abstractes-ES
dc.description.abstractFor offshore wind power generation, accessibility is one of the main factors that has great impact on operation and maintenance due to constraints on weather conditions for marine transportation. This paper presents a framework to explore the accessibility of an offshore site. At first, several maintenance types are defined and taken into account. Next, a data visualization procedure is introduced to provide an insight into the distribution of access periods over time. Then, a rigorous mathematical method based on finite state Markov chain is proposed to assess the accessibility of an offshore site from the maintenance perspective. A five-year weather data of a marine site is used to demonstrate the applicability and the outcomes of the proposed method. The main findings show that the proposed framework is effective in investigating the accessibility for different time scales and is able to catch the patterns of the distribution of the access periods. Moreover, based on the developed Markov chain, the average waiting time for a certain access period can be estimated. With more information on the maintenance of an offshore wind farm, the expected production loss due to time delay can be calculated.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.rightses_ES
dc.rights.uries_ES
dc.titleAn approach for evaluating the influence of accessibility on offshore wind power generationes_ES
dc.typeinfo:eu-repo/semantics/workingPaperes_ES
dc.description.versioninfo:eu-repo/semantics/draftes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordses-ES
dc.keywordsaccessibility; offshore; operation and maintenance; weather condition; Markov chain; data visualizationen-GB


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