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Insulating Materials for Future Power Systems: Performance Analysis, Defect Detection and Condition Assessment

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D1: Advanced Energy Materials".

Deadline for manuscript submissions: 15 April 2025 | Viewed by 6538

Special Issue Editors


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Guest Editor
Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
Interests: dielectric insulation; insulation aging; intelligent optimization; state evaluation; fault diagnosis

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Guest Editor
Department of Electrical Engineering, State Key Laboratory of Power System, Tsinghua University, Beijing 100084, China
Interests: insulating material; DC gas-insulated equipment
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Guest Editor
Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
Interests: high voltage engineering; power transmission; partial discharge; dielectric insulation

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Guest Editor
Department of Electrical Engineering, Guangxi University, Nanning 530004, China
Interests: fault diagnosis and condition monitoring of high-voltage power equipment.
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
Interests: Interrupting performance of SF6 circuit breakers; Measurement, analysis and suppression of switching transients in power equipment and networks; on-line condition monitoring of power equipment

Special Issue Information

Dear Colleagues,

A wide variety of electrical materials, such as polymeric insulating materials, energy storage materials, functional ceramics, semi-conductive sensing materials, and high-conductive metallic materials, compose the complicated power transmission system. Recently, modern renewable energy systems will replace traditional energy systems owing to the more precise and controlled power stations. In this context, the insulation materials, as one of the core components in electrical power equipment, will undergo unprecedented challenges and opportunities that may enhance the operational complexity and reduces the power system’s safety and reliability.

The variations in operational conditions mark a question on the insulation strength of newly developed countless ultra-high voltage (UHV) assets. Consequently, there is an essential need for a credible performance analysis, defect detection, and condition assessment of insulation materials in UHV equipment.

Therefore, in this Research Topic, we call for papers focusing on the fabrication, performance analysis, deterioration mechanism, defect detection, and condition assessment of new electrical materials. We welcome researchers to contribute Original Research, Brief Research Reports, and Review papers for this Research Topic. Potential topics include, but are not limited to:

  • Advanced measurement and characterization technology
  • Advanced electrical materials fabrication and their deterioration mechanism
  • Advanced insulation defect detection and condition assessment technique
  • Dielectric materials and relaxation phenomena
  • Operation, maintenance, and optimal design of UHV equipment
  • Other related aspects

Dr. Xianhao Fan
Dr. Chuangyang Li
Dr. Fangwei Liang
Dr. Jiefeng Liu
Prof. Dr. Weidong Liu
Guest Editors

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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. Energies is an international peer-reviewed open access semimonthly 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 2600 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

  • high voltage engineering
  • insulation materials
  • performance characterization and analysis
  • defect detection
  • condition assessment

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Published Papers (4 papers)

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Research

13 pages, 5802 KiB  
Article
Fault Diagnosis for Motor Bearings via an Intelligent Strategy Combined with Signal Reconstruction and Deep Learning
by Weiguo Li, Naiyuan Fan, Xiang Peng, Changhong Zhang, Mingyang Li, Xu Yang and Lijuan Ma
Energies 2024, 17(19), 4773; https://doi.org/10.3390/en17194773 - 24 Sep 2024
Cited by 1 | Viewed by 577
Abstract
To overcome the incomplete decomposition of vibration signals in traditional motor-bearing fault diagnosis algorithms and improve the ability to characterize fault characteristics and anti-interference, a diagnostic strategy combining dual signal reconstruction and deep learning architecture is proposed. In this study, an improved complete [...] Read more.
To overcome the incomplete decomposition of vibration signals in traditional motor-bearing fault diagnosis algorithms and improve the ability to characterize fault characteristics and anti-interference, a diagnostic strategy combining dual signal reconstruction and deep learning architecture is proposed. In this study, an improved complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD)-based signal reconstruction method is first introduced to extract features representing motor bearing faults. A feature matrix construction method based on improved information entropy is then proposed to quantify these fault features. Finally, a fault diagnosis algorithm architecture integrating a multi-scale convolutional neural network (MSCNN) with attention mechanisms and a bidirectional long short-term memory network (BiLSTM) is developed. The experimental results for four fault states show that this model can effectively extract fault features from original vibration signals and, compared to other fault diagnosis models, offer high diagnostic accuracy and strong generalization, maintaining high accuracy even under varying speeds and noise interference. Full article
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21 pages, 14914 KiB  
Article
Composite Insulator Defect Identification Method Based on Acoustic–Electric Feature Fusion and MMSAE Network
by Bizhen Zhang, Shengwen Shu, Cheng Chen, Xiaojie Wang, Jun Xu and Chaoying Fang
Energies 2023, 16(13), 4906; https://doi.org/10.3390/en16134906 - 23 Jun 2023
Cited by 2 | Viewed by 1378
Abstract
Aiming to solve the partial discharge problem caused by defects in composite insulators, most existing live detection methods are limited by the subjectivity of human judgment, the difficulty of effective quantification, and the use of a single detection method. Therefore, a composite insulator [...] Read more.
Aiming to solve the partial discharge problem caused by defects in composite insulators, most existing live detection methods are limited by the subjectivity of human judgment, the difficulty of effective quantification, and the use of a single detection method. Therefore, a composite insulator defect diagnosis model based on acoustic–electric feature fusion and a multi-scale perception multi-input of stacked auto-encoder (MMSAE) network is proposed in this paper. Initially, during the withstanding voltage experiment, the electromagnetic wave spectrometer and ultrasonic detector were used to collect and process the data of six types of composite insulator samples with artificial defects. The electromagnetic wave spectrum, ultrasonic power spectral density, and n-S map were then obtained. Then, the network architecture of MMSAE was built by integrating a stacked auto-encoder and multi-scale perception module; the feature extraction and fusion methods of the electromagnetic wave spectrum and ultrasonic signal were investigated. The proposed method was used to diagnose test samples, and the diagnostic results were compared to those obtained using a single input source and the artificial neural network (ANN) method. The results demonstrate that the detection accuracy of acoustic–electric feature fusion is greater than that of a single feature; the accuracy of the proposed method is 99.17%, which is significantly higher than the accuracy of the conventional ANN method. Finally, composite insulator defect diagnosis software based on PYQT5 and Keras was developed. Ten 500 kV aging composite insulators were used to validate the effectiveness of the proposed method and design software. Full article
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13 pages, 5711 KiB  
Article
Comprehensive Properties of Grafted Polypropylene Insulation Materials for AC/DC Distribution Power Cables
by Shangshi Huang, Yuxiao Zhou, Shixun Hu, Hao Yuan, Jun Yuan, Changlong Yang, Jun Hu, Qi Li and Jinliang He
Energies 2023, 16(12), 4701; https://doi.org/10.3390/en16124701 - 14 Jun 2023
Cited by 7 | Viewed by 2001
Abstract
Polypropylene (PP) exhibits excellent insulation properties, high thermo-stability, and recyclable nature, thus expected to be the next-generation insulation material for HV cable application. Chemical grafting modification is an effective technology to improve the electrical properties of polypropylene. In this paper, we develop and [...] Read more.
Polypropylene (PP) exhibits excellent insulation properties, high thermo-stability, and recyclable nature, thus expected to be the next-generation insulation material for HV cable application. Chemical grafting modification is an effective technology to improve the electrical properties of polypropylene. In this paper, we develop and report a new-type grafted PP insulation material by water-phase grafting technology. The comprehensive properties including electrical, thermal, and mechanical of it are tested and compared with traditional cable insulation material—crosslinked polyethylene (XLPE). The results show that the grafted PP holds superior thermal properties and enough mechanical flexibility. The electrical properties are of significant advantages, including resistivity enhanced by nearly two degrees of magnitudes, AC/DC breakdown strength raised by over 20%, and obviously suppressed space charge accumulation. These results indicate that grafted PP is very suitable for application in HV cable systems, either AC or DC. This research lays a foundation for the research and development of the next-generation recyclable polypropylene cables at higher voltage levels. Full article
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14 pages, 210757 KiB  
Article
Impact of Air Gap Defects on the Electrical and Mechanical Properties of a 320 kV Direct Current Gas Insulated Transmission Line Spacer
by Yuan Deng, Xianhao Fan, Hanhua Luo, Yao Wang, Keyan Wu, Fangwei Liang and Chuanyang Li
Energies 2023, 16(10), 4006; https://doi.org/10.3390/en16104006 - 10 May 2023
Cited by 5 | Viewed by 1475
Abstract
Air gap defects inside a spacer reduce its insulation performance, resulting in stress concentration, partial discharge, and even flashover. If such gap defects are located at the interface between the insulation and conductor, a decrease in mechanical stress may occur. In this work, [...] Read more.
Air gap defects inside a spacer reduce its insulation performance, resulting in stress concentration, partial discharge, and even flashover. If such gap defects are located at the interface between the insulation and conductor, a decrease in mechanical stress may occur. In this work, a finite element method-based simulation model is developed to analyze the influence of gap defects on the electrical and mechanical properties of a ±320 kV direct current gas insulated line (DC GIL) spacer. Present findings reveal that a radially distributed air gap produces a more significant effect on the electric field distribution, and an electric field strength 1.7 times greater than that of the maximum surface value is observed at the air gap. The axial distribution dominates the distortion of the surface stress by generating a stress concentration region in which the maximum stress of the air gap is twice the pressure in the surrounding area. Full article
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