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Parameter estimation of three-phase untransposed short transmission lines from synchrophasor measurements
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Wehenkel, Antoine, Mukhopadhyay, Arpan, Le Boudec, Jean-Yves and Paolone, Mario (2020) Parameter estimation of three-phase untransposed short transmission lines from synchrophasor measurements. IEEE Transactions on Instrumentation and Measurement . doi:10.1109/TIM.2020.2969059 (In Press)
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WRAP-parameter-estimation-three-phase-untransposed-short-transmission-lines-synchrophasor-measurements-Mukhopadhyay-2020.pdf - Accepted Version - Requires a PDF viewer. Download (1050Kb) | Preview |
Official URL: http://dx.doi.org/10.1109/TIM.2020.2969059
Abstract
We present a new approach for estimating the parameters of three-phase untransposed electrically short transmission lines using voltage/current synchrophasor measurements obtained from phasor measurement units. The parameters to be estimated are the entries of the longitudinal impedance matrix and the shunt admittance matrix at the rated system frequency. Conventional approaches relying on the admittance matrix of the line cannot accurately estimate these parameters for short lines, due to their high sensitivity to measurement noise. Our approach differs from the conventional ones in the following ways: First, we model the line by the three-phase transmittance matrix that is observed to be less sensitive to measurement noise than the admittance matrix. Second, we compute an accurate noise covariance matrix using the realistic specifications of noise introduced by instrument transformers and phasor measurement units. This noise covariance matrix is then used in least-squares-based estimation methods. Third, we derive different least-squares-based estimation methods based on a statistical model of estimation and show that the weighted least-squares and the maximum likelihood methods, which make use of the noise covariance matrix produce the best estimates of the line parameters. Finally, we apply the proposed methods to a real dataset and show that our approach significantly outperforms existing ones.
| Item Type: | Journal Article | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||
| Divisions: | Faculty of Science > Computer Science | ||||||
| Library of Congress Subject Headings (LCSH): | Electric measurements, Electric lines, Electric power systems, Electric power distribution -- Research, Parameter estimation -- Mathematical models, Electric power systems -- State estimation | ||||||
| Journal or Publication Title: | IEEE Transactions on Instrumentation and Measurement | ||||||
| Publisher: | IEEE | ||||||
| ISSN: | 0018-9456 | ||||||
| Official Date: | 23 January 2020 | ||||||
| Dates: |
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| Date of first compliant deposit: | 7 August 2020 | ||||||
| DOI: | 10.1109/TIM.2020.2969059 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | In Press | ||||||
| Publisher Statement: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| RIOXX Funder/Project Grant: |
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