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dc.contributor.authorWang, Pingfeng
dc.contributor.authorTamilselvan, Prasanna
dc.contributor.authorTwomey, Janet M.
dc.contributor.authorYoun, Byeng D.
dc.date.accessioned2013-07-26T13:45:47Z
dc.date.available2013-07-26T13:45:47Z
dc.date.issued2013-06
dc.identifier.citationWang, Pingfeng; Tamilselvan, Prasanna; Twomey, Janet M.; Youn, Byeng Dong. 2013. Prognosis-informed wind farm operation and maintenance for concurrent economic and environmental benefits. International Journal of Precision Engineering and Manufacturing, v.14:no.6:Special Issue:pp.1049-1056en_US
dc.identifier.issn2234-7593
dc.identifier.otherWOS:000320013300028
dc.identifier.urihttp://dx.doi.org/10.1007/s12541-013-0141-8
dc.identifier.urihttp://hdl.handle.net/10057/6068
dc.descriptionClick on the DOI link to access the article (may be free).en_US
dc.description.abstractAdvances in high-performance sensing and signal processing technology enable the development of failure-prognosis tools for wind turbines to detect, diagnose, and predict the systemwide effects of failure events. Although prognostics can provide valuable information for proactive actions in preventing system failures, the benefits have not been fully utilized for the operation and maintenance decision-making of wind turbines. This paper presents a generic failure prognosis informed decision-making tool for wind farm operation and maintenance while considering the predictive failure information of an individual turbine and its uncertainty. In the presented approach, the probabilistic damage growth model is used to characterize individual wind turbine performance degradation and failure prognostics, whereas the economic loss measured by monetary values and environmental performance measured by unified carbon credits are considered in the decision-making process. Based on customized wind farm information input, the developed decision-making methodology can be used to identify optimum and robust strategies for wind farm operation and maintenance in order to maximize economic and environmental benefits concurrently The efficacy of the proposed prognosis-informed maintenance strategy is compared with the condition-based maintenance strategy and demonstrated with a wind farm case study.en_US
dc.description.sponsorshipNational Science Foundation (CMMI-1200597), Kansas NSF EPSCoR program (NSF-0068316) and Wichita State University through the University Research Creative Project Awards (UCRA).en_US
dc.language.isoen_USen_US
dc.publisherThe Korean Society for Precision Engineering and Manufacturing (KSPE).en_US
dc.publisherSpringer
dc.relation.ispartofseriesInternational Journal of Precision Engineering and Manufacturing;v.14:no.6
dc.subjectEconomic and environmental impacten_US
dc.subjectPredictive maintenanceen_US
dc.subjectPrognosticsen_US
dc.subjectWind farm O&Men_US
dc.titlePrognosis-informed wind farm operation and maintenance for concurrent economic and environmental benefitsen_US
dc.typeArticleen_US
dc.rights.holderCopyright 2013 The Korean Society for Precision Engineering and Manufacturing (KSPE).


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