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    Reliability Evaluation of Distribution Network with Electric Vehicles and Distributed Generations Based on Network Equivalence and Sequential Monte Carlo Method

    Source: Journal of Energy Engineering:;2024:;Volume ( 150 ):;issue: 004::page 04024019-1
    Author:
    Haipeng Wang
    ,
    Kaiwen Li
    ,
    Zixuan Liu
    ,
    Yuling He
    ,
    Xiaolong Wang
    ,
    Kai Sun
    ,
    Peng Yang
    DOI: 10.1061/JLEED9.EYENG-5391
    Publisher: American Society of Civil Engineers
    Abstract: This paper proposes a reliability evaluation method of a distribution network with electric vehicles (EVs) and distributed generations (DGs) based on network equivalence and sequential Monte Carlo. Unlike traditional studies, the proposed method not only can effectively simplify the complexity structure of the distribution network with EVs and DGs, but also can establish a multidimensional reliability evaluation system for the distribution network with EVs and DGs. Firstly, the related models of DGs and EVs are established respectively in our study. Based on the minimum path method, the impact of each component fault on each load point is analyzed, and the failure impact analysis (FIA) table is constructed. Then, a simplified method for the structure of the distribution network with EVs and DGs based on network equivalence is proposed and validated. Moreover, the reliability evaluation method of the distribution network with EVs and DGs is given based on the sequential Monte Carlo. Finally, an illustrative example of the improved IEEE RBTS BUS6 F4 feeder system, as well as multiple dimensions discussions, are elaborated in detail to demonstrate the effectiveness and superiority of the proposed model.
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      Reliability Evaluation of Distribution Network with Electric Vehicles and Distributed Generations Based on Network Equivalence and Sequential Monte Carlo Method

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4299149
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    • Journal of Energy Engineering

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    contributor authorHaipeng Wang
    contributor authorKaiwen Li
    contributor authorZixuan Liu
    contributor authorYuling He
    contributor authorXiaolong Wang
    contributor authorKai Sun
    contributor authorPeng Yang
    date accessioned2024-12-24T10:33:35Z
    date available2024-12-24T10:33:35Z
    date copyright8/1/2024 12:00:00 AM
    date issued2024
    identifier otherJLEED9.EYENG-5391.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4299149
    description abstractThis paper proposes a reliability evaluation method of a distribution network with electric vehicles (EVs) and distributed generations (DGs) based on network equivalence and sequential Monte Carlo. Unlike traditional studies, the proposed method not only can effectively simplify the complexity structure of the distribution network with EVs and DGs, but also can establish a multidimensional reliability evaluation system for the distribution network with EVs and DGs. Firstly, the related models of DGs and EVs are established respectively in our study. Based on the minimum path method, the impact of each component fault on each load point is analyzed, and the failure impact analysis (FIA) table is constructed. Then, a simplified method for the structure of the distribution network with EVs and DGs based on network equivalence is proposed and validated. Moreover, the reliability evaluation method of the distribution network with EVs and DGs is given based on the sequential Monte Carlo. Finally, an illustrative example of the improved IEEE RBTS BUS6 F4 feeder system, as well as multiple dimensions discussions, are elaborated in detail to demonstrate the effectiveness and superiority of the proposed model.
    publisherAmerican Society of Civil Engineers
    titleReliability Evaluation of Distribution Network with Electric Vehicles and Distributed Generations Based on Network Equivalence and Sequential Monte Carlo Method
    typeJournal Article
    journal volume150
    journal issue4
    journal titleJournal of Energy Engineering
    identifier doi10.1061/JLEED9.EYENG-5391
    journal fristpage04024019-1
    journal lastpage04024019-12
    page12
    treeJournal of Energy Engineering:;2024:;Volume ( 150 ):;issue: 004
    contenttypeFulltext
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