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Conference Paper: Dynamic maintenance strategies for multiple transformers with Markov models

TitleDynamic maintenance strategies for multiple transformers with Markov models
Authors
KeywordsBackward induction
Dynamic coordinated maintenance strategies
Markov decision processes
Issue Date2013
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1003148
Citation
The 5th IEEE PES Innovative Smart Grid Technologies Conference (ISGT 2014), Washington, DC., 19-22 February 2014. In Innovative Smart Grid Technologies (ISGT) Proceedings, 2014, p. 1-5 How to Cite?
AbstractIntelligent substations in smart grids can provide more information about operating states of transformers by advanced sensors and monitoring units. According to information, operators can identify health conditions of transformers more accurately to determine maintenance strategies more reasonably. Maintenance of transformers can enhance the health condition and improve the reliability of a power system. However, maintenance introduces additional costs into total operating costs. A sophisticated maintenance strategy should be a tradeoff between maintenance costs and reliability enhancement. Based on monitoring information, a dynamic coordinated maintenance strategy for multiple transformers is proposed in this paper. First, a Markov model of an individual transformer is built to demonstrate its deterioration processes. Based on deterioration processes of an individual transformer, deterioration processes of a system with multiple transformers are built. Besides internal deterioration processes of components, external conditions, e.g., weather conditions and availability of servicemen and auxiliary equipment, are also considered in the model. Then, an optimization model is built. A series of dynamic coordinated maintenance strategies can be provided by the proposed optimization model, which is solved by a backward induction algorithm. A test system is used to demonstrate efficiency and accuracy of the method proposed in this paper. © 2014 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/204104
ISBN

 

DC FieldValueLanguage
dc.contributor.authorWang, Cen_US
dc.contributor.authorZhou, Hen_US
dc.contributor.authorHou, Y-
dc.contributor.authorLiu, H-
dc.date.accessioned2014-09-19T20:05:31Z-
dc.date.available2014-09-19T20:05:31Z-
dc.date.issued2013en_US
dc.identifier.citationThe 5th IEEE PES Innovative Smart Grid Technologies Conference (ISGT 2014), Washington, DC., 19-22 February 2014. In Innovative Smart Grid Technologies (ISGT) Proceedings, 2014, p. 1-5en_US
dc.identifier.isbn978-1-4799-3653-3-
dc.identifier.urihttp://hdl.handle.net/10722/204104-
dc.description.abstractIntelligent substations in smart grids can provide more information about operating states of transformers by advanced sensors and monitoring units. According to information, operators can identify health conditions of transformers more accurately to determine maintenance strategies more reasonably. Maintenance of transformers can enhance the health condition and improve the reliability of a power system. However, maintenance introduces additional costs into total operating costs. A sophisticated maintenance strategy should be a tradeoff between maintenance costs and reliability enhancement. Based on monitoring information, a dynamic coordinated maintenance strategy for multiple transformers is proposed in this paper. First, a Markov model of an individual transformer is built to demonstrate its deterioration processes. Based on deterioration processes of an individual transformer, deterioration processes of a system with multiple transformers are built. Besides internal deterioration processes of components, external conditions, e.g., weather conditions and availability of servicemen and auxiliary equipment, are also considered in the model. Then, an optimization model is built. A series of dynamic coordinated maintenance strategies can be provided by the proposed optimization model, which is solved by a backward induction algorithm. A test system is used to demonstrate efficiency and accuracy of the method proposed in this paper. © 2014 IEEE.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1003148-
dc.relation.ispartofInnovative Smart Grid Technologies (ISGT) Proceedingsen_US
dc.rightsInnovative Smart Grid Technologies (ISGT) Proceedings. Copyright © IEEE.-
dc.rights©2013 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBackward induction-
dc.subjectDynamic coordinated maintenance strategies-
dc.subjectMarkov decision processes-
dc.titleDynamic maintenance strategies for multiple transformers with Markov modelsen_US
dc.typeConference_Paperen_US
dc.identifier.emailHou, Y: yhhou@hku.hken_US
dc.identifier.emailLiu, H: hmliu@eee.hku.hk-
dc.identifier.authorityHou, Y=rp00069en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ISGT.2014.6816480-
dc.identifier.scopuseid_2-s2.0-84901937460-
dc.identifier.hkuros239443en_US
dc.identifier.spage1-
dc.identifier.epage5-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 141006-

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