Matrix Completion for Improved Observability in Low-Voltage Distribution Grids

Marija Markovic, Anthony Florita, Bri-Mathias Hodge

Research output: Contribution to conferencePaperpeer-review

1 Scopus Citations


This paper considers the problem of recovering missing entries in a partially observed matrix from relatively few measurements (i.e., the so-called matrix completion problem) with the aim of increasing the presently limited observability of low-voltage distribution grids. To this end, the partially observed matrix is formed using scarce voltage magnitude measurements while accounting for their spatial information. Voltage readings are assumed to be collected from distribution utility sensors and/or geographically-distributed cable television network sensors located in immediate proximity to distribution grid nodes. A matrix completion approach built on the parameter-less singular value shrinkage technique is used to estimate voltage magnitudes at otherwise non-observable low-voltage nodes using a small number of single- or multiple-snapshot data. The effectiveness of the proposed approach is demonstrated using a U.S.-style distribution test system from the synthetic SMART- DS data set under very low- to moderate-observability conditions.


Conference2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2021

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

NREL Publication Number

  • NREL/CP-5D00-80430


  • low-rank matrix completion
  • low-voltage distribution grid
  • observability
  • voltage magnitude estimation


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