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author:

Zhu, Tiechao (Zhu, Tiechao.) [1] | Shao, Zhenguo (Shao, Zhenguo.) [2] | Nie, Yixiong (Nie, Yixiong.) [3]

Indexed by:

EI

Abstract:

When the manufacturers produce capacitor voltage transformers (CVT), the function of harmonic measurement is not considered. Therefore, this paper explores methods to solve the problems of harmonic measurement from the perspective of manufacturers. Using the amplitude-frequency characteristic curve of CVT under no-load condition and standard environment as the benchmark, the estimation method of stray capacitance parameters in CVT based on CSO algorithm is proposed. Besides, in order to improve the accuracy of harmonic correction of CVT in different operating environments, this paper deeply studies the influence of oil temperature and industrial frequency on internal parameters and harmonic transfer characteristics of CVT. On this basis, this paper proposes a correction method of CVT harmonic transfer characteristic curves under different operating environments based on BP neural network algorithm. Finally, under the actual operating environment, calculating the amplitude-frequency characteristic curve of CVT by utilizing the actual harmonic voltages at the secondary side of the (Formula presented.) CVT and RCVT, and comparing it with the amplitude-frequency characteristic curve of CVT predicted by the BP neural network. The results show that the proposed methods are effective and feasible. © 2022 John Wiley & Sons Ltd.

Keyword:

Capacitance Frequency estimation Harmonic analysis Manufacture Neural networks Power transformers Variable speed transmissions

Community:

  • [ 1 ] [Zhu, Tiechao]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 2 ] [Shao, Zhenguo]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 3 ] [Nie, Yixiong]School of Automation, Guangdong University of Technology, Guangzhou, China

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International Journal of Numerical Modelling: Electronic Networks, Devices and Fields

ISSN: 0894-3370

Year: 2022

Issue: 6

Volume: 35

1 . 6

JCR@2022

1 . 6 0 0

JCR@2023

ESI HC Threshold:66

JCR Journal Grade:3

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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