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    Optimal Operation of Distributed Energy Storage Systems to Improve Distribution Network Load and Generation Hosting Capability

    Access Status
    Fulltext not available
    Authors
    Jayasekara, N.
    Masoum, M.
    Wolfs, Peter
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Jayasekara, N. and Masoum, M. and Wolfs, P. 2015. Optimal Operation of Distributed Energy Storage Systems to Improve Distribution Network Load and Generation Hosting Capability. IEEE Transactions on Sustainable Energy. 7 (1): pp. 250-261.
    Source Title
    IEEE Transactions on Sustainable Energy
    DOI
    10.1109/TSTE.2015.2487360
    ISSN
    1949-3029
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/15363
    Collection
    • Curtin Research Publications
    Abstract

    This paper proposes a strategy for optimal integration of battery energy storage systems (BESSs) to improve the load and distributed generation (DG) hosting ability of the utility grid. An effective tool that determines the optimal capacity and day-ahead operation strategy for deployment of distribution network operator (DNO)-controlled BESSs is presented. It is a cost-based multiobjective optimization strategy that considers two primary factors: 1)distribution system cost; and 2) battery cycling cost. Quantitative analyses on the benefits and tradeoffs of BESS installations are carried out considering different service options. BESS is investigated for three main service options: 1) voltage regulation; 2) loss reduction; and 3) peak reduction. The performance and benefits of the optimized BESS to control one service option exclusively or multiple services simultaneously is compared. The analysis is further extended to study the effect of installation site on the size, management strategy, and the service option. Results show that optimal integration of BESSs can realize maximum operational and cost benefits while effectively elevating the load and DG hosting capability of the network. The approach is developed using MATLAB interior-point algorithm. Simulations are conducted for the medium voltage (MV) IEEE 33 bus system and a low voltage (LV) distribution network in Western Australia studied during the Perth Solar City Trial.

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