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    Statistical and probabilistic models for smart electricity distribution networks

    194382_Li 2013-.pdf (3.304Mb)
    Access Status
    Open access
    Authors
    Li, Yingliang
    Date
    2013
    Supervisor
    Prof. Peter J. Wolfs
    Prof. Syed Islam
    Dr Dilan Jayaweera
    Type
    Thesis
    Award
    PhD
    
    Metadata
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    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/1515
    Collection
    • Curtin Theses
    Abstract

    This thesis aims towards an improved statistical understanding of distribution feeders, an improved probabilistic understanding of loads and methods for network-wide assessment of SmartGrid technologies. An efficient multi variable statistical analysis method was presented to identify prototypical feeders, which relies upon a few key variables that are highly meaningful from an engineering perspective and readily available in most distribution companies. Hybrid models for residential consumer load were built for high and low demand days.

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