Dynamic Power Network State Estimation with Asynchronous Measurements

Guido Cavraro, Andrey Bernstein, Emiliano Dall'Anese

Research output: Contribution to conferencePaperpeer-review

7 Scopus Citations


The operation of distribution networks is becoming increasingly volatile, due to fast variations of renewables and, hence, net-loading conditions. To perform a reliable state estimation under these conditions, this paper considers the case where measurements from meters, phasor measurement units, and distributed energy resources are collected and processed in real time to produce estimates of the state at a fast time scale. Streams of measurements collected in real time and at heterogenous rates render the underlying processing asynchronous, and poses severe strains on workhorse state estimation algorithms. In this work, a real-time state estimation algorithm is proposed, where data are processed on the fly. Starting from a regularized least-squares model, and leveraging appropriate linear models, the proposed scheme boils down to a linear dynamical system where the state is updated based on the previous estimate and on the measurement gathered from a few available sensors. The estimation error is shown to be always bounded under mild condition. Numerical simulations are provided to corroborate the analytical findings.

Original languageAmerican English
Number of pages5
StatePublished - Nov 2019
Event7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019 - Ottawa, Canada
Duration: 11 Nov 201914 Nov 2019


Conference7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019

Bibliographical note

See NREL/CP-5D00-75064 for preprint

NREL Publication Number

  • NREL/CP-5D00-76207


  • asynchronous measurements
  • smart grid
  • state estimation


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