Exact topology and parameter estimation in distribution grids with minimal observability

Seiun Park, Deepjyoti Deka, Michael Chcrtkov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations

Abstract

Limited presence of nodal and line meters in distribution grids hinders their optimal operation and participation in real-time markets. In particular lack of real-time information on the grid topology and infrequently calibrated line parameters (impedances) adversely affect the accuracy of any operational power flow control. This paper suggests a novel algorithm for learning the topology of distribution grid and estimating impedances of the operational lines with minimal observational requirements-it provably reconstructs topology and impedances using voltage and injection measured only at the terminal (end-user) nodes of the distribution grid. All other (intermediate) nodes in the network may be unobserved/hidden. Furthermore no additional input (e.g., number of grid nodes, historical information on injections at hidden nodes) is needed for the learning to succeed. Performance of the algorithm is illustrated in numerical experiments on the IEEE and custom power distribution models.

Original languageEnglish (US)
Title of host publication20th Power Systems Computation Conference, PSCC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781910963104
DOIs
StatePublished - Aug 20 2018
Externally publishedYes
Event20th Power Systems Computation Conference, PSCC 2018 - Dublin, Ireland
Duration: Jun 11 2018Jun 15 2018

Publication series

Name20th Power Systems Computation Conference, PSCC 2018

Other

Other20th Power Systems Computation Conference, PSCC 2018
Country/TerritoryIreland
CityDublin
Period6/11/186/15/18

Keywords

  • Distribution networks
  • Impedance estimation
  • Missing data
  • Power flows
  • Topology learning

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality

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