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    Smart Load Management of Plug-in Electric Vehicles in Distribution and Residential Networks with Charging Stations for Peak Shaving and Loss Minimisation Considering Voltage Regulation

    Access Status
    Fulltext not available
    Authors
    Masoum, A.
    Deilami, Sara
    Moses, Paul
    Masoum, Mohammad Sherkat
    Abu-Siada, Ahmed
    Date
    2011
    Type
    Journal Article
    
    Metadata
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    Citation
    Masoum, A. and Deilami, S. and Moses, P. and Masoum, M.S. and Abu-Siada, A. 2011. Smart Load Management of Plug-in Electric Vehicles in Distribution and Residential Networks with Charging Stations for Peak Shaving and Loss Minimisation Considering Voltage Regulation. IET Generation, Transmission and Distribution. 5 (8): pp. 877-888.
    Source Title
    IET Generation, Transmission and Distribution
    DOI
    10.1049/iet-gtd.2010.0574
    ISSN
    17518687
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/32195
    Collection
    • Curtin Research Publications
    Abstract

    New smart load management (SLM) approach for the coordination of multiple plug-in electric vehicle (PEV) chargers in distribution feeders is proposed. PEVs are growing in popularity as a low emission and efficient mode of transport against petroleum-based vehicles. PEV chargers represent sizeable and unpredictable loads, which can detrimentally impact the performance of distribution grids. Utilities are concerned about the potential overloads, stresses, voltage deviations and power losses that may occur in distribution systems from domestic PEV charging activity as well as from newly emerging charging stations. Therefore this study proposes a new SLM control strategy for coordinating PEV charging based on peak demand shaving, improving voltage profile and minimising power losses. Furthermore, the developed SLM approach takes into consideration the PEV owner preferred charging time zones based on a priority selection scheme. The impact of PEV charging stations and typical daily residential loading patterns are also considered. Simulation results are presented to demonstrate the significant performance improvement offered by SLM for a 1200 node test system topology consisting of several low-voltage residential networks populated with PEVs.

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