File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: A Novel Method for Optimal Life Cycle Management Scheme with Markov Model

TitleA Novel Method for Optimal Life Cycle Management Scheme with Markov Model
Authors
KeywordsLife cycle management
maintenance
Markov chain
optimal strategy
Issue Date2014
PublisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000581
Citation
The IEEE Power and Energy Society (PES) General Meeting, Washington, USA, 27-31 July 2014. In the IEEE Power and Energy Society General Meeting Proceedings, 2014 How to Cite?
AbstractMaintenance of equipment of a power system can enhance the health condition and result in the improvement of reliability of a power system. However, maintenance introduces additional cost into the total operating cost. A sophisticated maintenance strategy should be a tradeoff between maintenance costs and reliability enhancement. This paper addresses the optimal maintenance scheme for transmission equipment over their life cycles. The whole life cycle is divided into several intervals. The health states over all intervals are modeled as a Markov chain. The transformation probability between the states at interconnected intervals will be determined with different maintenance strategies. The model for optimal maintenance strategy considering minor maintenance costs, major maintenance costs, repair costs and equivalent load losses costs. Equivalent load losses are determined by Monte Carlo method based OPF algorithm associated with stochastic loads. To find solution within reasonable computing time, a space reduction approach is proposed based on the characteristics of the Markov chain. A test system is used to demonstrate the efficiency and accuracy of the method.
Persistent Identifierhttp://hdl.handle.net/10722/204102
ISBN

 

DC FieldValueLanguage
dc.contributor.authorWang, Cen_US
dc.contributor.authorHou, Yen_US
dc.date.accessioned2014-09-19T20:05:30Z-
dc.date.available2014-09-19T20:05:30Z-
dc.date.issued2014en_US
dc.identifier.citationThe IEEE Power and Energy Society (PES) General Meeting, Washington, USA, 27-31 July 2014. In the IEEE Power and Energy Society General Meeting Proceedings, 2014en_US
dc.identifier.isbn9781479964154-
dc.identifier.urihttp://hdl.handle.net/10722/204102-
dc.description.abstractMaintenance of equipment of a power system can enhance the health condition and result in the improvement of reliability of a power system. However, maintenance introduces additional cost into the total operating cost. A sophisticated maintenance strategy should be a tradeoff between maintenance costs and reliability enhancement. This paper addresses the optimal maintenance scheme for transmission equipment over their life cycles. The whole life cycle is divided into several intervals. The health states over all intervals are modeled as a Markov chain. The transformation probability between the states at interconnected intervals will be determined with different maintenance strategies. The model for optimal maintenance strategy considering minor maintenance costs, major maintenance costs, repair costs and equivalent load losses costs. Equivalent load losses are determined by Monte Carlo method based OPF algorithm associated with stochastic loads. To find solution within reasonable computing time, a space reduction approach is proposed based on the characteristics of the Markov chain. A test system is used to demonstrate the efficiency and accuracy of the method.-
dc.languageengen_US
dc.publisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000581-
dc.relation.ispartofIEEE Power and Energy Society General Meeting Proceedingsen_US
dc.subjectLife cycle management-
dc.subjectmaintenance-
dc.subjectMarkov chain-
dc.subjectoptimal strategy-
dc.titleA Novel Method for Optimal Life Cycle Management Scheme with Markov Modelen_US
dc.typeConference_Paperen_US
dc.identifier.emailHou, Y: yhhou@eee.hku.hken_US
dc.identifier.authorityHou, Y=rp00069en_US
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/PESGM.2014.6939421-
dc.identifier.scopuseid_2-s2.0-84930995246-
dc.identifier.hkuros239441en_US
dc.publisher.placeUnited States-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats