Reliability analysis of smart electrical transmission system and reliability modeling through dynamic flowgraph methodology

dc.contributor.advisorLu, Lixuan
dc.contributor.authorRazzaq, Muhammad Rashid
dc.date.accessioned2012-09-21T19:07:37Z
dc.date.accessioned2022-03-29T16:40:43Z
dc.date.available2012-09-21T19:07:37Z
dc.date.available2022-03-29T16:40:43Z
dc.date.issued2011-04-01
dc.degree.disciplineElectrical and Computer Engineering
dc.degree.levelMaster of Applied Science (MASc)
dc.description.abstractReliability assessment methods allow the evaluation of the reliability of systems and provide important information on how to improve a system‟s life to reduce risk and hazards. With the advancement in technology, the existing methods were extended and new methods were adopted. The advancement from mechanical to numerical and analog to digital system in many applications, and deregulation of energy sector brought the need to further modify the reliability analysis methods. The scope of this research is to demonstrate the advancement of the Dynamic Flowgraph Methodology (DFM) to reliability modeling of Smart Electrical Transmission System. The reason behind this is the successful operation of electric power under a deregulated electricity market depends on transmission system reliability management. Besides this, analog electro-mechanical systems in existing power system are aging and becoming obsolete. This thesis also illustrates how the electrical transmission system can be renovated into smart electrical transmission system and evaluates the reliability measures.en
dc.description.sponsorshipUniversity of Ontario Institute of Technologyen
dc.identifier.urihttps://hdl.handle.net/10155/252
dc.language.isoenen
dc.subjectDynamic flowgraph methodologyen
dc.subjectSmart electrical transmission systemen
dc.subjectReliability modelingen
dc.titleReliability analysis of smart electrical transmission system and reliability modeling through dynamic flowgraph methodologyen
dc.typeThesisen
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Ontario Institute of Technology
thesis.degree.nameMaster of Applied Science (MASc)

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