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Regular Paper | Open Access

Data-driven Detection and Identification of Line Parameters with PMU and Unsynchronized SCADA Measurements in Distribution Grids

Jinping Sun, Qifang Chen, Mingchao Xia ( )
School of Electrical Engineering, Beijing Jiaotong University (BJTU), Beijing 100044, China
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Abstract

Line parameters play an important role in the control and management of distribution systems. Currently, phasor measurement unit (PMU) systems and supervisory control and data acquisition (SCADA) systems coexist in distribution systems. Unfortunately, SCADA and PMU measurements usually do not match each other, resulting in inaccurate detection and identification of line parameters based on measurements. To solve this problem, a data-driven method is proposed. SCADA measurements are taken as samples and PMU measurements as the population. A probability parameter identification index (PPII) is derived to detect the whole line parameter based on the probability density function (PDF) parameters of the measurements. For parameter identification, a power-loss PDF with the PMU time stamps and a power-loss chronological PDF are derived via kernel density estimation (KDE) and a conditional PDF. Then, the power-loss samples with the PMU time stamps and chronological correlations are generated by the two PDFs of the power loss via the Metropolis-Hastings (MH) algorithm. Finally, using the power-loss samples and PMU current measurements, the line parameters are identified using the total least squares (TLS) algorithm. Hardware simulations demonstrate the effectiveness of the proposed method for distribution network line parameter detection and identification.

Keywords

Distribution systemsline parameter detection and identificationprobability density functionsampling algorithmthe time skew of PMU and SCADA measurements

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CSEE Journal of Power and Energy Systems
Volume 10 Issue 1,
January 2024
Pages 261-271
DOI: 10.17775/CSEEJPES.2020.06860
Cite this article:
Sun J, Chen Q, Xia M. Data-driven Detection and Identification of Line Parameters with PMU and Unsynchronized SCADA Measurements in Distribution Grids. CSEE Journal of Power and Energy Systems, 2024, 10(1): 261-271. https://doi.org/10.17775/CSEEJPES.2020.06860

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Received: 22 December 2020
Revised: 02 March 2021
Accepted: 12 May 2021
Published: 06 May 2022
© 2020 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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