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On the explicit formulation of reliability assessment of distribution systems with unknown network topology: Incorporation of DG, switching interruptions, and customer-interruption quantification

Jooshaki, M ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1016/j.apenergy.2022.119655
  3. Publisher: Elsevier Ltd , 2022
  4. Abstract:
  5. This paper presents an original approach for the evaluation of reliability of active distribution networks with unknown topology. Built upon novel reformulations of conventional definitions for distribution reliability indices, the dependence of system-oriented reliability metrics on network topology is explicitly formulated using a set of mixed-integer linear expressions. Unlike previously reported works also modeling mathematically the relationship between reliability assessment and network topology, the proposed approach allows considering the impact of distributed generation (DG) while accounting for switching interruptions. Moreover, for the first time in the emerging closely related literature, the nonlinearity and nonconvexity of the customer average interruption duration index are precisely characterized. The proposed mixed-integer linear model is suitable for various distribution optimization problems in which the operational topology of the network is not specified a priori. Aiming to exemplify its potential applicability, the proposed formulation is incorporated into a distribution reconfiguration optimization problem. The effectiveness and practicality of the proposed approach are numerically illustrated using various test networks. © 2022 The Authors
  6. Keywords:
  7. Active distribution networks ; Customer-interruption quantification ; Distributed generation ; Reliability assessment ; Switching interruptions ; Unknown network topology ; Distributed power generation ; Integer programming ; Reliability analysis ; Sales ; Active distribution network ; Active distributions ; Customer interruptions ; Integer Linear Programming ; Mixed integer linear ; Mixed-integer linear programming ; Network topology ; Reliability assessments ; Switching interruption ; Unknown networks ; Modeling ; Nonlinearity ; Optimization ; Topology
  8. Source: Applied Energy ; Volume 324 , 2022 ; 03062619 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S0306261922009539