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    Optimal Resource Allocation for Reducing Distribution System Risk Induced by Hurricane

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    CIRED 2019 - 898.pdf (706.9Kb)
    Paper number
    898
    Conference name
    CIRED 2019
    Conference date
    3-6 June 2019
    Conference location
    Madrid, Spain
    Peer-reviewed
    Yes
    Metadata
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    Authors
    ZHANG, HANG, Guangzhou Power Supply Bureau Co.- Ltd., China
    GAN, LIN, Guangzhou Power Supply Bureau Co. Ltd., China
    MO, WENXIONG, Guangzhou Power Supply Bureau Co. Ltd., China
    WANG, HONGBIN, Guangzhou Power Supply Bureau Co. Ltd., China
    QIN, YU, Guangzhou Power Supply Bureau Co. Ltd., China
    LUO, LINHUAN, Guangzhou Power Supply Bureau Co. Ltd., China
    HE, JIAXING, Guangzhou Power Supply Bureau Co. Ltd., China
    YANG, ZEJUN, Tsinghua University, China
    Abstract
    Preventive measures to reduce the risk of large-scale blackouts caused by natural disasters are necessary. This paper focuses on the resource allocation problem in distribution systems before a coming hurricane. The probability evaluation model of critical load service failure is developed. Emergency resources such as crews, materials, and equipment are considered for allocation, which is essential for hurricane preparedness and post-disaster repairing in terms of critical loads. An evaluation method of outage risks is introduced with considering the intensity and path of the coming hurricane. Due to the uncertainties of system failures, the allocation optimization is formulated into a dynamic Mixed-Integer Nonlinear Programming(MINP). Numerical simulations are performed on the IEEE 33-node feeder with 3 dispatch centers under several scenarios to validate the proposed method. Simulation results show that the risk is largely decreased through the proposed allocation strategy.
    Publisher
    AIM
    Date
    2019-06-03
    Published in
    • CIRED 2019 Conference
    Permanent link to this record
    https://cired-repository.org/handle/20.500.12455/190
    http://dx.doi.org/10.34890/368
    ISSN
    2032-9644
    ISBN
    978-2-9602415-0-1

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