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Advances in Design, Operation and Maintenance Technology for Electric Power Equipment—2nd Edition

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: 20 September 2026 | Viewed by 4508

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Editors

Prof. Dr. Jiachen Gao

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Guest Editor

State Key Laboratory of High-Efficiency and High-Quality Conversion for Electric Power, College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Interests: design and maintenance technology for high-voltage power equipment
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Prof. Dr. Tianyan Jiang

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Guest Editor

School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China
Interests: intelligent sensing and condition assessment of power equipment
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Dr. Yaqi Fang

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Guest Editor

School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 432200, China
Interests: outdoor insulation and live working
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Dr. Jinxin Cao

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Guest Editor

School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Interests: lightning protection
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Special Issue Information

Dear Colleagues,

Electric power equipment is crucial for five major aspects of power systems: generation, transmission, substation, distribution, and consumption. Guaranteeing the reliable operation of electric power equipment is key to ensuring the stability of a power system. Proven experience in design, operation and maintenance contributes to the reliability of electric power equipment. Therefore, the aim of this Special Issue is to discuss the latest research advances in electric power equipment design, operation and maintenance technologies to promote the reliability, efficiency and sustainability of power systems. We invite researchers in the field of power engineering to submit reviews and research articles on related topics.

Electric power equipment encompasses, for instance, thermal/hydroelectric generators, wind turbines, photovoltaic systems, grounding grids, transmission lines, towers, insulators, GIS/GIL, transformers, circuit breakers, cables, switchgear, electric vehicles, and new power electronics-based equipment (flexible DC converters, power electronic transformers, etc.).

Potential topics include (but are not limited to) the following: the discharge mechanism and its characteristics, insulation aging and life, topology, multiphysics, loss optimization, automation and intelligence, inspection and detection technology, condition monitoring and fault diagnosis, disaster prevention technology (lightning, wildfire, bird, etc.), maintenance technology, live-line work, operational control and optimization, and new AI-based applications.

Prof. Dr. Jiachen Gao
Prof. Dr. Tianyan Jiang
Dr. Yaqi Fang
Dr. Jinxin Cao
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

electric power equipment
electrical insulation
multiphysics
operation and maintenance
artificial intelligence

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Related Special Issue

Advances in Design, Operation and Maintenance Technology for Electric Power Equipment in Energies (20 articles)

Published Papers (6 papers)

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Research

19 pages, 1612 KB

Open AccessArticle

Research on Breakdown Voltage During Live-Line Work on Equipotential Bands at Different Altitudes

by Yong Peng, Rui-Xun Qiao, Xing-Lie Lei, Kai Liu, Zhong-Hua Qiu, Bin Xiao and Ya-Di Zhang

Energies 2026, 19(13), 3095; https://doi.org/10.3390/en19133095 - 30 Jun 2026

Viewed by 170

Abstract

High-altitude, low-pressure environments significantly reduce the insulation strength of air gaps, posing severe risks to live-line working on Ultra High Voltage and Extra High Voltage (UHV/EHV) transmission lines. To address this challenge and ensure operational safety, this paper proposes a predictive gap discharge voltage calculation model based on the dynamic coupling of time-varying electric fields and space charge. Unlike existing approaches that rely on static, geometry-dependent empirical corrections, the proposed model achieves high predictive capability by intrinsically mapping air relative density and absolute humidity to dynamically modify key microscopic discharge parameters, including the effective ionization coefficient, attachment coefficient, and streamer internal electric field strength. This physical framework enables the successful simulation of the complete progression from streamer inception to leader development and final breakdown, thereby calculating the 50% breakdown voltage under varying altitudes and gap distances. To rigorously validate the proposed model, breakdown tests were conducted using simplified sphere–plane gaps and full-scale simulated gaps between a human worker and a tower window at altitudes of 23 m and 2100 m. Additionally, third-party experimental datasets were utilized for comprehensive comparative analysis. The results demonstrate that the model’s predictive values align excellently with multi-source experimental data, establishing its high accuracy and practical engineering value for complex electrode configurations under diverse high-altitude conditions. Full article

(This article belongs to the Special Issue Advances in Design, Operation and Maintenance Technology for Electric Power Equipment—2nd Edition)

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18 pages, 41308 KB

Open AccessArticle

Condition Assessment of Field-Aged Composite Insulators Following Incidents of Insulator Flashunder

by Nikolaos Mavrikakis and Kiriakos Siderakis

Energies 2026, 19(10), 2325; https://doi.org/10.3390/en19102325 - 12 May 2026

Viewed by 355

Abstract

A condition assessment of a group of field-aged insulators operated for only 6 years on the island of Rhodes after incidents of intense electrical activity is presented in this paper. The investigated insulators were in service in 150 kV overhead transmission lines operating in proximity to the seacoast, exposed to the action of marine pollution. Although the same type of insulator has been widely used in similar conditions, both on the island of Rhodes and on the island of Crete, incidents of intense electrical activity have only been experienced in a specific area on the southwest side of Rhodes. To understand the deterioration mechanism, in addition to a group of failed insulators, a number of insulators from the same area without indication of deterioration were removed to be tested. In total, 40 insulators were examined: 23 with extensive failure, three without any deterioration and 14 with different levels of tracking and erosion traces along the polymeric housing. A series of tests were performed, including visual inspection, hydrophobicity classification, insulation performance through tanδ measurements, an adhesion test between the polymeric housing and the rod and material identification of the housing material through FTIR-ATR. The results indicate that the main failure mechanism is insulator flashunder due to the poor adhesion between the polymeric housing and the rod, as well as the poor sealing of insulators, favoring the ingress of water on the insulator rod and the initiation of electrical discharges. Full article

(This article belongs to the Special Issue Advances in Design, Operation and Maintenance Technology for Electric Power Equipment—2nd Edition)

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15 pages, 3133 KB

Open AccessArticle

Physiochemical Properties Investigation of Thermal–Moisture-Aged Low Voltage PVC Cable Insulation

by Attique Ur Rehman, Muhammad Zeeshan, Usman Ali and Ehtasham Mustafa

Energies 2026, 19(7), 1628; https://doi.org/10.3390/en19071628 - 26 Mar 2026

Viewed by 703

Abstract

This study investigates the combined effects of thermal and moisture aging on PVC-insulated low voltage (LV) photovoltaic (PV) cables using an accelerated-aging design to represent realistic PV operating conditions commonly encountered in hot and humid climates. Thermal aging was carried out at 90 °C for five aging cycles, with each thermal cycle followed by controlled moisture injection to simulate moisture stress. The degradation behavior was evaluated using broadband dielectric spectroscopy, FTIR analysis, and Shore D hardness measurements. Changes in dielectric dissipation factor (tanδ) and real permittivity (

ε^{'}

) were analyzed over a wide frequency range, with 100 kHz selected for its high sensitivity to aging-induced oxidation-related dipolar and interfacial polarization mechanisms. Degradation indices (DI) and degradation rates (DR) were derived from tanδ and correlated with mechanical and chemical changes. The results showed a 5% and 7% increase in tanδ at 100 kHz and in hardness, respectively, with decreases of 68% and 75% in the carbonyl and hydroxyl indices, respectively. Three distinct aging stages were identified: early thermo-oxidation with limited functional impact; mid-stage dehydrochlorination and moisture interaction; and late-stage chain scission, plasticizer loss, and insulation stiffening. The findings demonstrate the importance of climate-specific aging assessment and confirm the effectiveness of integrated electrical, mechanical, and chemical diagnostics for PV cable condition monitoring. Full article

(This article belongs to the Special Issue Advances in Design, Operation and Maintenance Technology for Electric Power Equipment—2nd Edition)

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24 pages, 4044 KB

Open AccessArticle

Climate-Driven Load Variations and Fault Risks in Humid-Subtropical Mountainous Grids: A Hybrid Forecasting and Resilience Framework

by Ruiyue Xie, Jiajun Lin, Yuesheng Zheng, Chuangli Xie, Haobin Lin, Xingyuan Guo, Zhuangyi Chen, Boye Qiu, Yudong Mao, Xiwen Feng and Zhaosong Fang

Energies 2026, 19(3), 778; https://doi.org/10.3390/en19030778 - 2 Feb 2026

Viewed by 468

Abstract

Against the backdrop of global climate change, remote subtropical mountainous power grids face severe operational challenges due to their fragile infrastructure and complex climatic conditions. However, existing research has insufficiently addressed load forecasting in data-sparse regions, particularly lacking systematic analysis of the “meteorology–load–failure” coupling mechanism. To address this gap, this study focused on 10 kV distribution lines in a typical subtropical monsoon region of southern China. Based on hourly load and meteorological data from 2016 to 2025, we propose a two-stage hybrid model combining “Random Forest (RF) feature selection + Long Short-Term Memory (LSTM) time series forecasting”. Through deep feature engineering, composite, lagged, and interactive features were constructed. Using the RF algorithm, we quantitatively identified the core drivers of load variation across different time scales: at the hourly scale, variations are dominated by historical inertia (with weights of 0.5915 and 0.3757 for 1-h and 24-h lagged loads, respectively); at the daily scale, the logic shifts to meteorological triggering and cumulative effects, where the composite feature load_lag1_hi_product emerged as the most critical driver (weight of 0.8044). Experimental results demonstrate that the hybrid model significantly improved forecasting accuracy compared to the full-feature LSTM benchmark: on a daily scale, RMSE decreased by 13.29% and MAE by 16.67%, with R² reaching 0.8654; on an hourly scale, R² reached 0.9687. Furthermore, correlation analysis with failure data revealed that most grid faults occurred during intervals of extremely low load variation (0–5%), suggesting that “chronic stress” from environmental exposure in hot and humid conditions is the primary cause, with lightning identified as the leading external threat (26.90%). The interpretable forecasting framework proposed in this study transcends regional limitations. It provides a strategic “low-cost, high-resilience” prototype applicable to power systems in humid-subtropical zones worldwide, particularly for developing regions facing the dual challenges of data sparsity and climate vulnerability. Full article

(This article belongs to the Special Issue Advances in Design, Operation and Maintenance Technology for Electric Power Equipment—2nd Edition)

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17 pages, 2212 KB

Open AccessArticle

A Lightweight Model for Power Quality Disturbance Recognition Targeting Edge Deployment

by Hao Bai, Ruotian Yao, Tong Liu, Ziji Ma, Shangyu Liu, Yiyong Lei and Yawen Zheng

Energies 2026, 19(2), 368; https://doi.org/10.3390/en19020368 - 12 Jan 2026

Viewed by 907

Abstract

To address the dual demands of accuracy and real-time performance in power quality disturbance (PQD) recognition for new power system, this paper proposes a lightweight model named the Cross-Channel Attention Three-Layer Convolutional Model (1D-CCANet-3), specifically designed for edge deployment. Based on the one-dimensional convolutional neural network (1D-CNN), the model features an ultra-compact architecture with only three convolutional layers and one fully connected layer. By incorporating a set of cross-channel attention (CCA) mechanisms in the final convolutional layer, the model further enhances disturbance recognition accuracy. Compared to other deep learning models, 1D-CCANet-3 significantly reduces computational and storage requirements for edge devices while achieving accurate and efficient PQD recognition. The model demonstrates robust performance in recognizing 10 types of PQD under varying signal-to-noise ratio (SNR) conditions. Furthermore, the model has been successfully deployed on the FPGA platform and exhibits high recognition accuracy and efficiency in real-world data validation. This work provides a feasible and effective solution for accurate and real-time PQD monitoring on edge devices in new power systems. Full article

(This article belongs to the Special Issue Advances in Design, Operation and Maintenance Technology for Electric Power Equipment—2nd Edition)

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21 pages, 1147 KB

Open AccessArticle

Assessment of Insulation Aging Condition for Dry-Type Transformer Epoxy Resin Based on Dielectric Response and Activation Energy Analysis

by Yu Dong, Youhang Wang, Zhiqiang Li, Ning Lei, Yanchen Wei and Bin Song

Energies 2026, 19(1), 144; https://doi.org/10.3390/en19010144 - 26 Dec 2025

Cited by 1 | Viewed by 1382

Abstract

The accurate assessment of the aging state of epoxy resin insulation is critical for the safe operation of cast resin dry-type transformers. This study investigates the evolution of activation energy during thermal aging and its correlation with insulation degradation. Accelerated aging experiments at 150 °C, 170 °C, and 200 °C were conducted, followed by frequency-domain dielectric spectroscopy and Havriliak–Negami (HN) model analysis. An improved method for calculating activation energy, incorporating temperature correction via an HN-based model, is proposed. The evolution of key HN parameters—relaxation strength (Δε), relaxation time (τ), and shape parameters (α, β)—serves as the criterion for identifying the dominant aging mechanism: crosslinking at 150 °C, competition between crosslinking and degradation at 170 °C, and degradation-dominated chain scission at 200 °C. Using 150 °C data as a baseline, the initial activation energy is determined to be 90.03 kJ/mol, increasing to 166.83 kJ/mol at the end of service life. A practical, graded insulation condition indicator based on the rate of change in activation energy (ΔEa) is established, providing clear guidance for maintenance decisions—from routine monitoring (ΔEa ≤ 20%) to prioritized inspection or replacement (ΔEa > 60%). The proposed method offers a non-destructive tool for insulation diagnosis, residual life prediction, and condition-based maintenance of dry-type transformers. Full article

(This article belongs to the Special Issue Advances in Design, Operation and Maintenance Technology for Electric Power Equipment—2nd Edition)

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