Matrix Completion for Low-Observability Voltage Estimation

Priya Donti, Yajing Liu, Andreas Schmitt, Andrey Bernstein, Rui Yang, Yingchen Zhang

Research output: Contribution to journalArticlepeer-review

53 Scopus Citations


With the rising penetration of distributed energy resources, distribution system control and enabling techniques such as state estimation have become essential to distribution system operation. However, traditional state estimation techniques have difficulty coping with the low-observability conditions often present on the distribution system due to the paucity of sensors and heterogeneity of measurements. To address these limitations, we propose a distribution system state estimation algorithm that employs matrix completion (a tool for estimating missing values in low-rank matrices) augmented with noise-resilient power flow constraints. This method operates under low-observability conditions where standard least-squares-based methods cannot operate, and flexibly incorporates any network quantities measured in the field. We empirically evaluate our method on the IEEE 33- and 123-bus test systems, and find that it provides near-perfect state estimation performance (within 1% mean absolute percent error) across many low-observability data availability regimes.

Original languageAmerican English
Article number8930601
Pages (from-to)2520-2530
Number of pages11
JournalIEEE Transactions on Smart Grid
Issue number3
StatePublished - May 2020

Bibliographical note

Publisher Copyright:
© 2010-2012 IEEE.

NREL Publication Number

  • NREL/JA-5D00-70590


  • distribution system
  • distribution system state estimation
  • low observability
  • Matrix completion
  • power distribution
  • state estimation


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