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dc.creatorGrover, Mohinder Singh
dc.date.accessioned2017-08-16T21:35:34Z
dc.date.available2017-08-16T21:35:34Z
dc.date.issued1972-10
dc.date.submittedOctober 1972en_US
dc.identifier.urihttp://hdl.handle.net/10388/8018
dc.description.abstractAn acceptable level of customer reliability is a major factor in the design and operation of an efficient and economic distribution system, Quantitative reliability assessment provides a valuable tool for predicting the performance adequacy of the system. this thesis illustrates the application of simple probability techniques to the evaluation of the generally accepted reliability measures of outage frequency and duration at various system load points, component permanent, temporary maintenance and overload outage modes are considered in the reliability prediction. The results predicted by using and existing approximate method are compared with those obtained by using a Markov technique for a two state fluctuating failures environment covering normal and adverse weather periods. Simple equations are developed to represent the various load point failure modes and the results are comparable with those predicted by the Markov approach. A three state weather model is proposed which includes the effect of disaster adverse weather periods on system reliability. A technique which exists in the literature for forming an equivalent component is investigated and it is shown that such an approach is not valid when dependent effects exist in the system. A failure modes and effect analysis of a practical configuration This technique provides an insight into the inherent system failure processes and gives an indication of the action most likely to achieve the required improvement at minimum cost.en_US
dc.titleDISTRIBUTION SYSTEM RELIABILITY ASSESSMENTen_US
thesis.degree.departmentElectrical and Computer Engineeringen_US
thesis.degree.disciplineElectrical Engineeringen_US
thesis.degree.grantorUniversity of Saskatchewanen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Science (M.Sc.)en_US
dc.type.genreThesisen_US


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