Symmetry in Three-Phase Electrical Power Systems

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Engineering and Materials".

Deadline for manuscript submissions: closed (30 April 2025) | Viewed by 1183

Special Issue Editors


E-Mail Website
Guest Editor
Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defense, North China Electric Power University, Baoding 071003, China
Interests: deterioration mechanism of insulation materials of power transmission and transformation equipment and its performance improvement method; intelligent assessment method of status of power transmission and transformation equipment driven by data-knowledge fusion
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Interests: structure optimization of high-speed train electrical equipment; optimization of CATenary arm insulator/transmission line insulator/phase separation insulator structure; transformer condition monitoring and evaluation

Special Issue Information

Dear Colleagues,

Symmetry/asymmetry is a universal issue for engineering. Regarding electrical and electronic engineering, there are also symmetry/asymmetry-related problems. For instance, charging and de-charging is a typical symmetrical process. To further dig into symmetry/asymmetry research in electrical and electronic engineering, the Special Issue “Symmetry in Three-Phase Electrical Power Systems” has been organized. This Special Issue will cover various research in electrical and electronic engineering related of symmetry/asymmetry. Researchers are invited to submit original research papers and review articles related to any electrical engineering and electronic engineering discipline in which theoretical or practical issues of symmetry are considered. Topics of interest for this Special Issue include (but are not limited to) the following:

  • Symmetry/asymmetry in topology/geometry design of electrical and electronic engineering;
  • Symmetry/asymmetry in modelling and computing of electrical and electronic engineering;
  • Symmetry/asymmetry in experiments and tests of electrical and electronic engineering;
  • Symmetry/asymmetry in physical/chemical processes of electrical and electronic engineering;
  • Symmetry/asymmetry in system analysis of electrical and electronic engineering;
  • Symmetry/asymmetry in component analysis of electrical and electronic engineering;
  • Symmetry/asymmetry in material research of electrical and electronic engineering.

Dr. Jun Xie
Prof. Dr. Jianqiao Ma
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • new topology and geometry design
  • in-depth physical/chemical process study
  • novel modelling and computing theories and methods
  • design of new experiment and test result analysis
  • system/component/material research

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

16 pages, 4507 KiB  
Article
Partial Discharge Data Enhancement and Pattern Recognition Method Based on a CAE-ACGAN and ResNet
by Songyuan Li, Xiaopeng Wang, Yue Han, Junji Feng, Zhen Yin, Jiawang Yang, Weipeng Luo and Jun Xie
Symmetry 2025, 17(1), 55; https://doi.org/10.3390/sym17010055 - 31 Dec 2024
Viewed by 904
Abstract
In order to address the issue of the accuracy of partial discharge pattern recognition being constrained by unbalanced samples and the deep structure of the deep learning network, a method for partial discharge data enhancement and pattern recognition based on a convolutional autoencoder [...] Read more.
In order to address the issue of the accuracy of partial discharge pattern recognition being constrained by unbalanced samples and the deep structure of the deep learning network, a method for partial discharge data enhancement and pattern recognition based on a convolutional autoencoder auxiliary classifier generative adversarial network (CAE-ACGAN) and a residual network (ResNet) is proposed. The initial step involves the preprocessing of the acquired partial discharge signals, with the phase resolved partial discharge (PRPD) spectra subsequently employed as the training samples. Secondly, a CAE-ACGAN is constructed. The model combines the advantages of a deep convolutional self-coding structure and a generative adversarial paradigm to generate high-quality phase resolved partial discharge spectrograms. Subsequently, a ResNet is employed as the classifier for partial discharge pattern recognition, utilising the CAE-ACGAN-enhanced partial discharge dataset for network training to achieve accurate recognition of partial discharge signals. The experimental findings demonstrate that the SSIM and PSNR indexes of the CAE-ACGAN model utilised in this study are 0.92 and 45.88 dB, respectively. The partial discharge pattern method employing the CAE-ACGAN and ResNet exhibits superiority in identifying partial discharges, attaining an identification accuracy of 98%, which is 7.25% higher than the pre-enhancement level. Full article
(This article belongs to the Special Issue Symmetry in Three-Phase Electrical Power Systems)
Show Figures

Figure 1

Back to TopTop