RCAM Based Maintenance Plan of the Power Transformers Using k-Means Clustering Algorithm

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dc.authoridKoksal, Aysun/0000-0002-8131-6802
dc.authoridAta, Oguz/0000-0003-4511-7694
dc.authoridozdemir, aydogan/0000-0003-1331-2647
dc.contributor.authorKoksal, Aysun
dc.contributor.authorOzdemir, Aydogan
dc.contributor.authorAta, Oguz
dc.date.accessioned2025-03-26T17:35:08Z
dc.date.available2025-03-26T17:35:08Z
dc.date.issued2017
dc.departmentİstanbul Esenyurt Üniversitesi
dc.description19th International Conference on Intelligent System Application to Power Systems (ISAP) -- SEP 17-20, 2017 -- San Antonio, TX
dc.description.abstractRCAM based maintenance planning of power transmission grid aims to optimize the planned outage of the assets that maximizes the system reliability without additional cost increases. A recent RCAM based transformer maintenance procedure is extended to the system level and a revised maintenance plan is proposed to achieve better reliability indices, total costs and longer life cycles. k-means clustering algorithm is used for criticality assessment and classification of the transformers with respect to two criticality criteria. The proposed classification is applied to the power transformers of Turkish National Power Transmission System and the results are discussed in terms of accuracy and the applicability.
dc.identifier.isbn978-1-5090-4000-1
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.14704/1046
dc.identifier.wosWOS:000426989800029
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherIeee
dc.relation.ispartof2017 19th International Conference on Intelligent System Application To Power Systems (Isap)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250326
dc.subjectReliability Centered Asset Management; criticality analysis; k-Means Clustering; power transformers
dc.titleRCAM Based Maintenance Plan of the Power Transformers Using k-Means Clustering Algorithm
dc.typeConference Object

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