Resilient Identification of Distribution Network Topology

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Title: Resilient Identification of Distribution Network Topology
Authors: Jafarian, MohammadSoroudi, AlirezaKeane, Andrew
Permanent link: http://hdl.handle.net/10197/12585
Date: Aug-2021
Online since: 2021-11-08T14:17:08Z
Abstract: IEEE Network topology identification (TI) is an essential function for distributed energy resources management systems (DERMS) to organize and operate widespread distributed energy resources (DERs). In this paper, discriminant analysis (DA) is deployed to develop a network TI function that relies only on the measurements available to DERMS. The propounded method is able to identify the network switching configuration, as well as the status of protective devices. Following, to improve the TI resiliency against the interruption of communication channels, a quadratic programming optimization approach is proposed to recover the missing signals. By deploying the propounded data recovery approach and Bayes' theorem together, a benchmark is developed afterward to identify anomalous measurements. This benchmark can make the TI function resilient against cyber-attacks. Having a low computational burden, this approach is fast-track and can be applied in real-time applications. Sensitivity analysis is performed to assess the contribution of different measurements and the impact of the system load type and loading level on the performance of the proposed approach.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: IEEE
Journal: IEEE Transactions on Power Delivery
Volume: 36
Issue: 4
Start page: 2332
End page: 2342
Copyright (published version): 2020 IEEE
Keywords: Discriminant analysisDistribution networkDistributed energy resources management systemsTopology identification
DOI: 10.1109/TPWRD.2020.3037639
Language: en
Status of Item: Peer reviewed
ISSN: 0885-8977
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Electrical and Electronic Engineering Research Collection

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