Comparison and Analysis of the Influence of Different Data Transformation Methods on the Fault Identification of Flexible DC Transmission Lines by Convolutional Neural Network

Can Ding, Zhenyi Wang, Qingchang Ding and Taiping Nie

Mathematical Problems in Engineering, 2021, vol. 2021, 1-17

Abstract:

In the fault classification and identification of flexible DC transmission lines, it is inevitable to use the voltage and current characteristics of the transmission line. All kinds of data transformation methods can highlight the hidden characteristics of the original fault electrical quantity. Various artificial intelligence algorithms can further reduce the difficulty of transmission line fault classification. For such fault classification methods, this paper first builds a four-terminal flexible direct current transmission system model on PSCAD/EMTDC platform and obtains data by simulating different faults of transmission lines. Then, empirical mode decomposition (EMD), wavelet transform (WT), fast Fourier transform (FFT), and variational mode decomposition (VMD) are performed on the obtained data, respectively. Finally, the transformed data and original data are used as inputs to classify by convolutional neural network (CNN). The influence of one data transformation method and different combinations of two data transformation methods on CNN classification results is explored. The simulation results show that when only one data transformation method is used, CNN has the best classification effect for the data after VMD transformation. The classification accuracy and recall rate are both increased from 96.9% and 96.3% without data transformation to 99.88%. When VMD and FFT are combined, CNN classification results’ accuracy and recall rate are further improved to 99.96%.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2021/1759866.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2021/1759866.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1759866

DOI: 10.1155/2021/1759866

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().