Show simple item record

dc.contributor.authorLi, X
dc.contributor.authorOuelhadj, D
dc.contributor.authorSong, X
dc.contributor.authorJones, D
dc.contributor.authorWall, G
dc.contributor.authorHowell, KE
dc.contributor.authorIgwe, P
dc.contributor.authorMartin, S
dc.contributor.authorSong, D
dc.contributor.authorPertin, E
dc.date.accessioned2016-09-09T09:41:30Z
dc.date.available2016-09-09T09:41:30Z
dc.date.issued2016-12
dc.identifier.issn0960-1481
dc.identifier.issn1879-0682
dc.identifier.otherC
dc.identifier.urihttp://hdl.handle.net/10026.1/5426
dc.description.abstract

This paper presents a Decision Support System (DSS) for maintenance cost optimisation at an Offshore Wind Farm (OWF). The DSS is designed for use by multiple stakeholders in the OWF sector with the overall goal of informing maintenance strategy and hence reducing overall lifecycle maintenance costs at the OWF. Two optimisation models underpin the DSS. The first is a deterministic model that is intended for use by stakeholders with access to accurate failure rate data. The second is a stochastic model that is intended for use by stakeholders who have less certainty about failure rates. Solutions of both models are presented using a UK OWF that is in construction as an example. Conclusions as to the value of failure rate data are drawn by comparing the results of the two models. Sensitivity analysis is undertaken with respect to the turbine failure rate frequency and number of turbines at the site, with near linear trends observed for both factors. Finally, overall conclusions are drawn in the context of maintenance planning in the OWF sector.

dc.format.extent784-799
dc.languageen
dc.language.isoen
dc.publisherElsevier
dc.subjectOffshore wind
dc.subjectRenewable energy
dc.subjectOperations and maintenance (O&M)
dc.subjectDecision support
dc.subjectStochastic optimisation
dc.titleA decision support system for strategic maintenance planning in offshore wind farms
dc.typejournal-article
dc.typeArticle
plymouth.volume99
plymouth.publication-statusPublished
plymouth.journalRenewable Energy
dc.identifier.doi10.1016/j.renene.2016.07.037
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA17 Business and Management Studies
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Marine Institute
dcterms.dateAccepted2016-07-16
dc.rights.embargodate2017-7-31
dc.identifier.eissn1879-0682
dc.rights.embargoperiod12 months
rioxxterms.versionofrecord10.1016/j.renene.2016.07.037
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved
rioxxterms.licenseref.startdate2016-12
rioxxterms.typeJournal Article/Review


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record


All items in PEARL are protected by copyright law.
Author manuscripts deposited to comply with open access mandates are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author.
Theme by 
Atmire NV