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  • Planning for Resilience in Power Distribution Networks: A Multi-Objective Decision Support

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    Author(s)
    Garmabdari, Rasoul
    Jamborsalamati, Pouya
    Hossain, MJ
    Lu, Junwei
    Dehghanian, Payman
    Griffith University Author(s)
    Garmabdari, Rasoul
    Lu, Junwei
    Hossain, Jahangir
    Year published
    2021
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    Abstract
    Power grid response against High-Impact Low-Probability (HILP) events could be enhanced by (a) hardening mechanisms to boost its structural resilience and (b) corrective recovery and mitigation analytics to improve its operational resilience. This paper focuses on planning for structural resilience and attempts to find the optimal location of the Tie switches in radially-operated power distribution networks that enables harnessing the network topology for maximized resilience against HILP disasters. This goal is achieved through a novel resilience-oriented multi-objective decision making platform, which employs a k-PEM based ...
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    Power grid response against High-Impact Low-Probability (HILP) events could be enhanced by (a) hardening mechanisms to boost its structural resilience and (b) corrective recovery and mitigation analytics to improve its operational resilience. This paper focuses on planning for structural resilience and attempts to find the optimal location of the Tie switches in radially-operated power distribution networks that enables harnessing the network topology for maximized resilience against HILP disasters. This goal is achieved through a novel resilience-oriented multi-objective decision making platform, which employs a k-PEM based Probabilistic Power Flow (PPF) algorithm. The proposed framework offers a decision making analytic embedded with the Fuzzy Satisfying Method (FSM) that characterizes the system resilience features such as robustness, restoration agility, load criticality, and recovered capacity, to assess different network reconfiguration options and select the optimal solution for implementation. The aforementioned resilience features are formulated in nodal level and then aggregated over the entire system to characterize the system-level objective functions. The performance of the suggested framework is analyzed on the IEEE 33-Bus test system under a designated HILP event and the applicability on larger networks has been verified on the IEEE 69-bus test system. The results demonstrate the efficacy and applicability of the proposed framework in boosting the network resilience against future extremes.
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    Journal Title
    IET Smart Grid
    Volume
    5
    Issue
    1
    DOI
    https://doi.org/10.1049/stg2.12005
    Copyright Statement
    © 2021 The Authors. IET Smart Grid published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution ‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited and no modifications or adaptations are made.
    Subject
    Electronics, sensors and digital hardware
    Distribution grid resilience; multi-objective optimization; high impact low probability (HILP) event; reconfiguration; state estimation.
    Publication URI
    http://hdl.handle.net/10072/402243
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    • Journal articles

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