Real-Time Distribution System State Estimation with Asynchronous Measurements

Cavraro, Guido; Comden, Joshua; DallrAnese, Emiliano; Bernstein, Andrey

doi:10.1109/tsg.2022.3171466

Real-Time Distribution System State Estimation with Asynchronous Measurements

Journal Article · Mon May 02 00:00:00 EDT 2022 · IEEE Transactions on Smart Grid

DOI:https://doi.org/10.1109/tsg.2022.3171466· OSTI ID:1869797

Cavraro, Guido ^[1]; Comden, Joshua ^[1]; DallrAnese, Emiliano ^[2]; Bernstein, Andrey ^[1]

National Renewable Energy Lab. (NREL), Golden, CO (United States)
Univ. of Colorado, Boulder, CO (United States)

We report state estimation is a fundamental task in power systems. Although distribution systems are increasingly equipped with sensing devices and smart meters, measurements are typically reported at different rates and asynchronously; these aspects pose severe strains on workhorse state estimation algorithms, which are designed to process batches of data collected in a synchronous manner from all the measurement units. In this paper, we develop a novel state estimation algorithm to continuously update the estimate of the state based on measurements received in an asynchronous manner from measurement units. The synthesis of the algorithm hinges on a proximal-point type method, implemented in an online fashion, and capable of processing measurements received sequentially from sensors. A performance analysis is presented by providing bounds on the estimation error in terms of the mean and variance that hold at each iteration and asymptotically. The scheme is also compared with a more traditional Weighted Least Squares estimator that compensates for the lack of measurement data by using, as pseudo measurements, the measurement retrieved during a certain time window. Numerical simulations on the IEEE 37-bus feeder corroborate the analytical findings.

View Accepted Manuscript (DOE)

Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1869797

Report Number(s):: NREL/JA-5D00-82754; MainId:83527; UUID:676de0b7-5592-4d83-af79-edeeecfb284b; MainAdminID:64572

Journal Information:: IEEE Transactions on Smart Grid, Journal Name: IEEE Transactions on Smart Grid Journal Issue: 5 Vol. 13; ISSN 1949-3053

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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