{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/86762"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/86762","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"A Comparative Analysis on Transformer Failure Modeling Techniques","abstract":"M.S.","abstract_html":"M.S.","abstract_has_math":false,"creators":["Franklin, Jarrett; 0000-0001-7273-1601"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Zirnheld, Jennifer","Electrical Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-02-21T21:44:50Z","date_published":"2025-02-21T21:44:50Z","updated_at":"2026-07-27T19:05:37Z","subjects":["electrical engineering","statistics"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/86762","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zirnheld, Jennifer","Electrical Engineering"]},{"key":"dc:creator","label":"Author","values":["Franklin, Jarrett; 0000-0001-7273-1601"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-02-21T21:44:50Z","2020"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["electrical engineering","statistics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/86762"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["M.S.","Power transformers are a vital part of electrical power utility systems. Like most electrical utility equipment under high stress conditions, power transformers are prone to failures and degradation in performance. A transformer failure can be detrimental to the utility network and be costly to replace. Producing a reliable model to predict transformer end-of-life is a topic that has been researched in the energy systems field. The main deterrent in these efforts has been the lack of detailed transformer failure data due to intellectual property rights, trade secrets, and the absence of operational data. The purpose of this work is to analyze modeling methods that aim to predict the time of failure for transformers based solely on age. Doble's Transformer Failure Subcommittee provided age-based data of 38,587 transformers for analysis. This data pool consisted of 35,712 operational units and 2,875 failed units. Each unit is a transmission-system transformer whose voltage ratings fall between 10kV and 700kV. The variable analyzed was the age of the transformer when the failure occurred. The age-of-failure data was analyzed using the Graphical Hazard Plotting Method to determine if an increased sample size would increase the modeling method's viability. However, additional parameters besides age influence transformer lifetimes. Diversity in voltage ratings, geographical locations, loading conditions and design characteristics vary between transformers. To address these additional parameters that were excluded in the initial model, alternative modeling methods including Health Index and Thermal Aging Modeling are examined during literature review. These methods typically include multiple failure mechanisms and modes that can contribute to transformer failures. The concept of hybrid modeling methods is introduced, and a proposed modeling structure is recommended. The proposed model incorporates the different failure mechanisms and modes that pertain to power transformers. It also accounts for historical failures and multi-factorial analysis to influence the health index scale. The hybrid structure can produce a more holistic model to predict transformer end-of-life. This method could enable utility companies with insights into failure-based maintenance schemes, targeted transformer testing, and spare/redundancy planning.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A Comparative Analysis on Transformer Failure Modeling Techniques"]}]}],"canonical_facts":{"dc:contributor":["Zirnheld, Jennifer","Electrical Engineering"],"dc:creator":["Franklin, Jarrett; 0000-0001-7273-1601"],"dc:date":["2025-02-21T21:44:50Z","2020"],"dc:description":["M.S.","Power transformers are a vital part of electrical power utility systems. Like most electrical utility equipment under high stress conditions, power transformers are prone to failures and degradation in performance. A transformer failure can be detrimental to the utility network and be costly to replace. Producing a reliable model to predict transformer end-of-life is a topic that has been researched in the energy systems field. The main deterrent in these efforts has been the lack of detailed transformer failure data due to intellectual property rights, trade secrets, and the absence of operational data. The purpose of this work is to analyze modeling methods that aim to predict the time of failure for transformers based solely on age. Doble's Transformer Failure Subcommittee provided age-based data of 38,587 transformers for analysis. This data pool consisted of 35,712 operational units and 2,875 failed units. Each unit is a transmission-system transformer whose voltage ratings fall between 10kV and 700kV. The variable analyzed was the age of the transformer when the failure occurred. The age-of-failure data was analyzed using the Graphical Hazard Plotting Method to determine if an increased sample size would increase the modeling method's viability. However, additional parameters besides age influence transformer lifetimes. Diversity in voltage ratings, geographical locations, loading conditions and design characteristics vary between transformers. To address these additional parameters that were excluded in the initial model, alternative modeling methods including Health Index and Thermal Aging Modeling are examined during literature review. These methods typically include multiple failure mechanisms and modes that can contribute to transformer failures. The concept of hybrid modeling methods is introduced, and a proposed modeling structure is recommended. The proposed model incorporates the different failure mechanisms and modes that pertain to power transformers. It also accounts for historical failures and multi-factorial analysis to influence the health index scale. The hybrid structure can produce a more holistic model to predict transformer end-of-life. This method could enable utility companies with insights into failure-based maintenance schemes, targeted transformer testing, and spare/redundancy planning.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/86762"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["electrical engineering","statistics"],"dc:title":["A Comparative Analysis on Transformer Failure Modeling Techniques"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T19:05:37Z"}