LAPSE:2023.7810v1
Published Article

LAPSE:2023.7810v1
Research on the Application of Uncertainty Quantification (UQ) Method in High-Voltage (HV) Cable Fault Location
February 24, 2023
Abstract
In HV cable fault location technology, line parameter uncertainty has an impact on the location criterion and affects the fault location result. Therefore, it is of great significance to study the uncertainty quantification of line parameters. In this paper, an impedance-based fault location criterion was used for an uncertainty study. Three kinds of uncertainty factors, namely the sheath resistivity per unit length, the equivalent grounding resistance on both sides, and the length of the cable section, were taken as random input variables without interaction. They were subject to random uniform distribution within a 50% amplitude variation. The relevant statistical information, such as the mean value, standard deviation and probability distribution, of the normal operation and fault state were calculated using the Monte Carlo simulation (MCS) method, the polynomial chaos expansion (PCE) method, and the univariate dimension reduction method (UDRM), respectively. Thus, the influence of uncertain factors on fault location was analyzed, and the calculation results of the three uncertainty quantification methods compared. The results indicate that: (1) UQ methods are effective for simulation analysis of fault locations, and UDRM has certain application prospects for HV fault location in practice; (2) the quantification results of the MCS, PCE, and UDRM were very close, while the mean convergence rate was significantly higher for the UDRM; (3) compared with the MCS, PCE, and UDRM, the PCE and UDRM had higher accuracy, and MCS and UDRM required less running time.
In HV cable fault location technology, line parameter uncertainty has an impact on the location criterion and affects the fault location result. Therefore, it is of great significance to study the uncertainty quantification of line parameters. In this paper, an impedance-based fault location criterion was used for an uncertainty study. Three kinds of uncertainty factors, namely the sheath resistivity per unit length, the equivalent grounding resistance on both sides, and the length of the cable section, were taken as random input variables without interaction. They were subject to random uniform distribution within a 50% amplitude variation. The relevant statistical information, such as the mean value, standard deviation and probability distribution, of the normal operation and fault state were calculated using the Monte Carlo simulation (MCS) method, the polynomial chaos expansion (PCE) method, and the univariate dimension reduction method (UDRM), respectively. Thus, the influence of uncertain factors on fault location was analyzed, and the calculation results of the three uncertainty quantification methods compared. The results indicate that: (1) UQ methods are effective for simulation analysis of fault locations, and UDRM has certain application prospects for HV fault location in practice; (2) the quantification results of the MCS, PCE, and UDRM were very close, while the mean convergence rate was significantly higher for the UDRM; (3) compared with the MCS, PCE, and UDRM, the PCE and UDRM had higher accuracy, and MCS and UDRM required less running time.
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Keywords
fault location, high-voltage cable, Monte Carlo simulation (MCS), polynomial chaos expansion (PCE), uncertainty quantification, univariate dimension reduction method (UDRM)
Subject
Suggested Citation
Yang B, Xia Z, Gao X, Tu J, Zhou H, Wu J, Li M. Research on the Application of Uncertainty Quantification (UQ) Method in High-Voltage (HV) Cable Fault Location. (2023). LAPSE:2023.7810v1
Author Affiliations
Yang B: State Grid Wuhan Electric Power Company, Wuhan 430077, China
Xia Z: State Grid Wuhan Electric Power Company, Wuhan 430077, China
Gao X: State Grid Wuhan Electric Power Company, Wuhan 430077, China
Tu J: State Grid Wuhan Electric Power Company, Wuhan 430077, China
Zhou H: Wuhan Fujia Anda Electric Technology Co., Ltd., Wuhan 430074, China
Wu J: School of Electrical Engineering, Nantong University, Nantong 226019, China
Li M: School of Electrical Engineering, Nantong University, Nantong 226019, China
Xia Z: State Grid Wuhan Electric Power Company, Wuhan 430077, China
Gao X: State Grid Wuhan Electric Power Company, Wuhan 430077, China
Tu J: State Grid Wuhan Electric Power Company, Wuhan 430077, China
Zhou H: Wuhan Fujia Anda Electric Technology Co., Ltd., Wuhan 430074, China
Wu J: School of Electrical Engineering, Nantong University, Nantong 226019, China
Li M: School of Electrical Engineering, Nantong University, Nantong 226019, China
Journal Name
Energies
Volume
15
Issue
22
First Page
8447
Year
2022
Publication Date
2022-11-11
ISSN
1996-1073
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PII: en15228447, Publication Type: Journal Article
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LAPSE:2023.7810v1
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