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    Failure rate modeling due to aging and its impacts on distribution network reliability

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    Failure rate modeling and its impacts on Uganda's distribution network reliability (1.603Mb)
    Failure rate modeling and its impacts on Uganda's distribution network reliability (1.603Mb)
    Date
    2019-06
    Author
    Mangen, Stephen
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    Abstract
    This project report presents a mathematical model that help to determine the failure rate due to aging of a power distribution feeder and the impact of those failures on the distribution network reliability. Electrical distribution network is composed of feeders formed from many components that become aged with time. Individual component failure rate mathematical models were built considering component failure due to their time of service in the outage data received from UMEME limited. Components considered were distribution conductors, distribution poles and line insulators. Individual component failure rate were there after added to give the entire feeder failure rate. Five UMEME feeders A, B, C, D, and E were studied. Feeders A and B (base case) were relatively new aged 1- 2 years and were in their useful period of operation experiencing minimal numbers of outages. Feeders C, D, and E were old feeders that had been in service since 1970s, with poor performance history and experiencing more numbers of outages on the UMEME network. Data for selected feeders was collected from UMEME limited and there after used to determine the failure rate per year of the entire feeders A, B, C, D, and E. The failure rates per year and annual down times for each feeder were used to run single line simulations in Dig SILENT software 15.0. Reliability indices from the simulation and their respective failure rates per year for each feeder were compared. It was observed that feeders C, D, and E had continuous increase in failure rate and could always be out of service due to their high values of SAIFI, SAIDI, CAIDI, and low values of ASAI. This gave the impact of failure rate due to aging on distribution network reliability.
    URI
    http://hdl.handle.net/20.500.12281/6174
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