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    Two-Stage Self-Healing Restoration Strategy Considering Operating Performance

    Source: Journal of Energy Engineering:;2020:;Volume ( 146 ):;issue: 004
    Author:
    Kaiyuan Pang
    ,
    Chongyu Wang
    ,
    Fushuan Wen
    ,
    Ivo Palu
    ,
    Changsen Feng
    ,
    Zeng Yang
    ,
    Minghui Chen
    ,
    Hongwei Zhao
    ,
    Huiyu Shang
    DOI: 10.1061/(ASCE)EY.1943-7897.0000683
    Publisher: ASCE
    Abstract: Power system resilience requires highly effective self-healing restoration strategies, and calls for superior performance both in system restoration and operation. Most existing restoration methods focus only on restoring performance, such as generation capacity, restored load capacity, and recovery time, but ignore operating performance that can enhance resilience significantly. This paper sheds light on a two-stage self-healing system restoration strategy considering operating performance, which includes voltage balance, transmission loss, and generation cost, to enhance resilience. The first stage aims to determine the restoration sequence of generators, power lines, and loads with maximum restored load capacity. The second stage of the optimization problem focuses on readjusting the power outputs of generators to improve single or multiple operating performance indicators. The optimization model of the first stage is formulated as a linear integer programming (IP) problem and solved by the branch-and-bound method, while the second-stage problem considering AC optimal power flow is solved by the interior point method. The proposed two-stage strategy also provides a possible solution for an online restoration decision support system with superior computational performance. Case studies on the IEEE 30-bus and 118-bus power systems have demonstrated the correctness and effectiveness of the proposed strategy.
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      Two-Stage Self-Healing Restoration Strategy Considering Operating Performance

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4268634
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    contributor authorKaiyuan Pang
    contributor authorChongyu Wang
    contributor authorFushuan Wen
    contributor authorIvo Palu
    contributor authorChangsen Feng
    contributor authorZeng Yang
    contributor authorMinghui Chen
    contributor authorHongwei Zhao
    contributor authorHuiyu Shang
    date accessioned2022-01-30T21:40:06Z
    date available2022-01-30T21:40:06Z
    date issued8/1/2020 12:00:00 AM
    identifier other%28ASCE%29EY.1943-7897.0000683.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4268634
    description abstractPower system resilience requires highly effective self-healing restoration strategies, and calls for superior performance both in system restoration and operation. Most existing restoration methods focus only on restoring performance, such as generation capacity, restored load capacity, and recovery time, but ignore operating performance that can enhance resilience significantly. This paper sheds light on a two-stage self-healing system restoration strategy considering operating performance, which includes voltage balance, transmission loss, and generation cost, to enhance resilience. The first stage aims to determine the restoration sequence of generators, power lines, and loads with maximum restored load capacity. The second stage of the optimization problem focuses on readjusting the power outputs of generators to improve single or multiple operating performance indicators. The optimization model of the first stage is formulated as a linear integer programming (IP) problem and solved by the branch-and-bound method, while the second-stage problem considering AC optimal power flow is solved by the interior point method. The proposed two-stage strategy also provides a possible solution for an online restoration decision support system with superior computational performance. Case studies on the IEEE 30-bus and 118-bus power systems have demonstrated the correctness and effectiveness of the proposed strategy.
    publisherASCE
    titleTwo-Stage Self-Healing Restoration Strategy Considering Operating Performance
    typeJournal Paper
    journal volume146
    journal issue4
    journal titleJournal of Energy Engineering
    identifier doi10.1061/(ASCE)EY.1943-7897.0000683
    page11
    treeJournal of Energy Engineering:;2020:;Volume ( 146 ):;issue: 004
    contenttypeFulltext
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