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Using Analytics to Minimize Errors in the Connectivity Model of a Power Distribution Network

Published: 14 July 2015 Publication History

Abstract

The connectivity model of a power distribution network can easily become outdated due to system changes. Maintaining and sustaining an accurate connectivity model is a key challenge for most distribution utilities today. This work presents novel analytics techniques that can infer the connectivity model from measurements already available from a distribution network. Our techniques utilize voltage data from customer smart meters and circuit metering points to identify and correct errors in the connectivity model. We report analysis results based on data collected from multiple feeders of a large electric distribution network in North America. Our analysis shows that customer voltage measurements exhibit hierarchical correlations, which can be exploited to cluster customers under the same distribution transformer or same phase with high accuracy. To the best of our knowledge, this is the first large scale measurement study of voltage data collected from smart meters and its use in inferring customer to transformer and phase connectivity information.

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Cited By

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  • (2020)Automating the Verification of the Low Voltage Network Cables and TopologiesIEEE Transactions on Smart Grid10.1109/TSG.2019.294172211:2(1657-1666)Online publication date: Mar-2020
  • (2019)Electrical principles of verification of the topological structure of a low‐voltage distribution network based on voltage from an Advanced Metering InfrastructureThe Journal of Engineering10.1049/joe.2019.00892019:11(8218-8224)Online publication date: 30-Jul-2019
  • (2018)Automated Verification of LV Network Topologies2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)10.1109/ISGTEurope.2018.8571892(1-6)Online publication date: Oct-2018
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cover image ACM Conferences
e-Energy '15: Proceedings of the 2015 ACM Sixth International Conference on Future Energy Systems
July 2015
334 pages
ISBN:9781450336093
DOI:10.1145/2768510
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 14 July 2015

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Author Tags

  1. power distribution grids
  2. topology inference
  3. voltage data

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e-Energy '15 Paper Acceptance Rate 20 of 85 submissions, 24%;
Overall Acceptance Rate 160 of 446 submissions, 36%

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Cited By

View all
  • (2020)Automating the Verification of the Low Voltage Network Cables and TopologiesIEEE Transactions on Smart Grid10.1109/TSG.2019.294172211:2(1657-1666)Online publication date: Mar-2020
  • (2019)Electrical principles of verification of the topological structure of a low‐voltage distribution network based on voltage from an Advanced Metering InfrastructureThe Journal of Engineering10.1049/joe.2019.00892019:11(8218-8224)Online publication date: 30-Jul-2019
  • (2018)Automated Verification of LV Network Topologies2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)10.1109/ISGTEurope.2018.8571892(1-6)Online publication date: Oct-2018
  • (2018)Input---output performance efficiency measurement of an electricity distribution utility using super-efficiency data envelopment analysisSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-018-3007-222:22(7339-7353)Online publication date: 1-Nov-2018
  • (2016)Predictive modeling of dissolved gas concentrationin oil-immersed substation transformers2016 IEEE Smart Energy Grid Engineering (SEGE)10.1109/SEGE.2016.7589536(261-267)Online publication date: Aug-2016

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