LAPSE:2023.27210
Published Article

LAPSE:2023.27210
Online Evaluation for the Accuracy of Electronic Voltage Transformer Based on Recursive Principal Components Analysis
April 4, 2023
Abstract
The electronic voltage transformer (EVT) has received much attention with the recent global trend to establish smart grids and digital substations. One of the main issues of the EVT is the deterioration of its performance with long-term operation which affects the control and protection systems it is employed for and hence the overall reliability of the power grids. This calls for the essential need for a reliable technique to regularly assess the accuracy of operating EVT in real-time. Unfortunately, traditional calibration methods cannot detect the incipient EVT performance change in real-time. As such, this paper presents a new online method to evaluate the accuracy of the EVT. In this regard, the Q-statistic is calculated based on the recursive principal components analysis (RPCA) using the output data of EVT to map up the changes of metering error on the electric−physics relationship. By employing the output data of the EVT along with the power grid characteristics, the performance of the EVT is evaluated without the need for a standard transformer, as per the current industry practice. Results show that the proposed method can assess the EVT with a 0.2 accuracy class.
The electronic voltage transformer (EVT) has received much attention with the recent global trend to establish smart grids and digital substations. One of the main issues of the EVT is the deterioration of its performance with long-term operation which affects the control and protection systems it is employed for and hence the overall reliability of the power grids. This calls for the essential need for a reliable technique to regularly assess the accuracy of operating EVT in real-time. Unfortunately, traditional calibration methods cannot detect the incipient EVT performance change in real-time. As such, this paper presents a new online method to evaluate the accuracy of the EVT. In this regard, the Q-statistic is calculated based on the recursive principal components analysis (RPCA) using the output data of EVT to map up the changes of metering error on the electric−physics relationship. By employing the output data of the EVT along with the power grid characteristics, the performance of the EVT is evaluated without the need for a standard transformer, as per the current industry practice. Results show that the proposed method can assess the EVT with a 0.2 accuracy class.
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Keywords
asset management, electronic voltage transformer, measurement accuracy, online evaluation, recursive principal components analysis
Suggested Citation
Li Z, Zheng Y, Abu-Siada A, Lu M, Li H, Xu Y. Online Evaluation for the Accuracy of Electronic Voltage Transformer Based on Recursive Principal Components Analysis. (2023). LAPSE:2023.27210
Author Affiliations
Li Z: College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China; Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443002, China [ORCID]
Zheng Y: College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
Abu-Siada A: Discipline of Electrical and Computer Engineering, Curtin University, Perth, WA 6000, Australia [ORCID]
Lu M: College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
Li H: School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Xu Y: College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
Zheng Y: College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
Abu-Siada A: Discipline of Electrical and Computer Engineering, Curtin University, Perth, WA 6000, Australia [ORCID]
Lu M: College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
Li H: School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Xu Y: College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
Journal Name
Energies
Volume
13
Issue
21
Article Number
E5576
Year
2020
Publication Date
2020-10-25
ISSN
1996-1073
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Original Submission
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PII: en13215576, Publication Type: Journal Article
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LAPSE:2023.27210
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https://doi.org/10.3390/en13215576
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