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Table of Content

    28 July 2026, Volume 60 Issue 7 Previous Issue   
    New Type Power System and the Integrated Energy
    Joint Scheduling Method for Peak and Frequency Regulation in Unit Commitment Using Battery Energy Storage Systems
    LIU Hang, LI Canbing, LIU Jianzhe, WU Yuhang, SHI Minjie
    2026, 60 (7):  1045-1054.  doi: 10.16183/j.cnki.jsjtu.2024.404
    Abstract ( 427 )   HTML ( 3 )   PDF (1506KB) ( 384 )   Save

    Battery energy storage (BES) is one of the most effective resources for consuming renewable energy and ensuring frequency security. With large-scale integration into power grids, BESs coordinate with thermal power units to participate in peak regulation and frequency regulation, and must reserve sufficient capacity in advance. The required frequency regulation capacity is determined by the implicit relationship between frequency and power. Existing methods linearize the frequency regulation capacity model according to the mixed integer linear programming framework of the unit commitment problem, which ensure computational efficiency at the cost of increased approximation errors. To address the trade-off between model accuracy and computational efficiency, this paper develops a frequency-power relationship model based on the universal approximation theorem of deep neural network (DNN), which not only keeps the structure of unit commitment problem unchanged but also theoretically approximates the original model with arbitrary accuracy. Based on this method, a joint scheduling method for battery energy storage in unit commitment is proposed. First, the mechanism of multi-source joint frequency regulation is analyzed, and a control strategy is developed in which energy storage provides fast power support in response to load step disturbance. According to this control strategy, a DNN is built to predict the maximum disturbance that the system can withstand, and a frequency regulation capacity reservation method for energy storage is proposed. Then, a joint scheduling model for BES peak and frequency regulation is developed to optimize the unit operating state and the capacity allocation of energy storage for the above services. Finally, the simulation results of case studies based on the IEEE 39-bus system verify that the proposed method can ensure the frequency security of the system under the maximum step disturbance, and improve the economy of the system operation, demonstrating the superiority of data-driven methods in representing frequency fluctuations.

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    Capacity Configuration and Operation Method of Wind-Solar-Hydro-Storage Integrated Power Station Based on Hybrid Pumped Storage
    ZHANG Yanzhi, CHEN Sijie, ZHENG Linfeng, LI Qingxin, ZHU Zhongyu, YAN Zheng
    2026, 60 (7):  1055-1064.  doi: 10.16183/j.cnki.jsjtu.2024.429
    Abstract ( 458 )   HTML ( 1 )   PDF (14280KB) ( 408 )   Save

    Integrated wind, solar, hydropower, and storage power plants can fully leverage the complementarities of multiple energy sources, with hybrid pumped storage serving as a key energy type in such systems. However, the mathematical model for hybrid pumped storage is highly nonlinear, which has not been integrated with wind, solar, and electrochemical storage in a unified configuration yet. To address this issue, a two-stage stochastic optimization model is established for the configuration and operation of an integrated power plant comprising wind power, photovoltaics, hybrid pumped storage, and electrochemical storage. Then, the big-M method and piecewise linear fitting are employed to relax the nonlinear parts of the model. Finally, the configuration and operational status of various energy sources as well as power generation schemes under different resource endowments are derived by simulation. The results indicate the competitiveness and economic viability of hybrid pumped storage in a complementary wind-solar-hydro-storage system.

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    Operational Target-Oriented Joint Parameter Optimization for Source-Load Power Forecasting in Park Integrated Energy System
    LIU Songyuan, FAN Feilong, PU Chuanqing, DOU Zhenlan, ZHANG Chunyan, CHEN Hongyin
    2026, 60 (7):  1065-1075.  doi: 10.16183/j.cnki.jsjtu.2024.405
    Abstract ( 347 )   HTML ( 1 )   PDF (2281KB) ( 382 )   Save

    Existing parameter design for power forecasting in park integrated energy systems (PIESs) focuses on minimizing the forecasting error of either source or load power, aiming at obtaining prediction results closest to the actual power without considering the comprehensive impact of forecasting results on operation objectives. This limitation leads to reduced overall economic benefits when the forecasting parameters are applied in practice. To address this issue, this paper proposes an operational target-oriented joint parameter optimization method for source-load power forecasting in PIESs. First, a joint optimization objective function for forecasting parameters is constructed based on a two-stage day-ahead and intraday operational model, integrating total economic operational indices from both day-ahead and intraday stages. Then, a joint parameter optimization model for source-load power forecasting with an embedded two-stage operation strategy is built, formulated by constructing the optimality conditions of the day-ahead model. Simultaneously, a warm-start scheme for the forecasting model is designed to accelerate the solution process of the joint parameter optimization problem. Finally, a simulation model is established based on commercial and residential energy consumption data from Anchorage, USA, to validate the proposed method, of which the results indicate that the proposed method can effectively reduce the operating costs of urban PIESs, decrease the curtailment of wind and solar energy, and increase the operational revenue of energy storage.

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    Calculation Method of Dynamic Network Usage Charge for Distributed Energy Nearby Trading with Rights and Responsibilities Matching
    YAN Yi, PING Jian, YAN Zheng, JIA Qiangang
    2026, 60 (7):  1076-1086.  doi: 10.16183/j.cnki.jsjtu.2024.462
    Abstract ( 208 )   HTML ( 0 )   PDF (2708KB) ( 359 )   Save

    Reasonable calculation of network usage charge is an important prerequisite for promoting the development of distributed energy nearby trading. However, existing methods for calculating network usage charge struggle to balance the needs of grid companies to recover transmission and distribution asset investment and the operational requirement of guiding distributed energy nearby trading in smoothing the net load curve. Therefore, a two-stage calculation method for dynamic network usage charge considering rights-responsibilities matching is proposed in this paper. First, a calculation method for static network usage charge based on rights-responsibilities matching is developed to ensure the fair and reasonable recovery of network construction costs. Then, a time-of-use dynamic adjustment method for network usage charge is designed to incentivize participants in distributed energy nearby trading to flatten the peak-to-valley differences of net load curves through price signals. On this basis, a bilevel optimization model is established, with a dynamic adjustment model of network usage charge in the upper level and a distributed energy nearby trading model in the lower level. The value of the dynamic network usage charge is measured by solving the model. Finally, simulation results show that the proposed calculation method for dynamic network usage charge can not only effectively ensure the reasonable recovery of transmission and distribution asset investments for grid companies but also significantly reduces the peak-to-valley difference rate of net load curves.

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    Short-Term Wind and Solar Power Forecasting Method Based on Closed-Loop Empirical Mode Decomposition and Temporal Convolutional Feature Extraction
    WANG Danhao, PENG Daogang, HUANG Dongmei, LIU Yu
    2026, 60 (7):  1087-1098.  doi: 10.16183/j.cnki.jsjtu.2024.431
    Abstract ( 383 )   HTML ( 2 )   PDF (7037KB) ( 379 )   Save

    The strong randomness and volatility inherent in wind and solar power generation results in single forecasting models insufficient for capturing their nonlinear and non-stationary characteristics. To address this issue, this paper proposes a combined short-term forecasting model for wind and solar power based on closed-loop complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and temporal convolutional feature extraction. First, CEEMDAN is applied to decompose the original wind and solar power generation data across multiple time scales, extracting high-energy intrinsic mode functions to effectively reduce the non-stationarity and complexity of the data. Then, a temporal convolutional network (TCN) is employed to extract the temporal features of the wind and solar power data, while a bidirectional gated recurrent unit (BiGRU) further captures the bidirectional dynamic characteristics of the time series. An Attention mechanism is also integrated to enhance the focus on key features, thereby constructing the TCN-BiGRU-Attention forecasting model. Additionally, the salp swarm algorithm (SSA) is introduced to optimize the hyperparameters of the model, and a feedback mechanism is used to dynamically adjust the decomposition parameters of CEEMDAN, further improving the forecasting performance. Finally, experiment results based on wind and solar power generation data from a certain region demonstrate that, compared with other forecasting models, the proposed method improves coefficient of determination R2 by 2.35% and 2.92%, respectively, effectively enhancing the prediction accuracy.

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    Coordinated Optimization Strategies for Integrated Energy Systems Considering Mobile Energy Storage Vehicles and Battery-Swapping Heavy Trucks
    DING Wenbin, LI Yutong
    2026, 60 (7):  1099-1109.  doi: 10.16183/j.cnki.jsjtu.2025.301
    Abstract ( 331 )   HTML ( 1 )   PDF (2091KB) ( 232 )   Save

    Battery-swapping heavy trucks play a crucial role in the development of green logistics parks. However, their large-scale deployment and improvement of profitability face challenges due to limited grid access and capacity expansion at swapping stations. To address these issues, this paper introduces mobile energy storage vehicles (MESVs) as flexible dispatch resources within the truck-station system and proposes a comprehensive energy scheduling strategy for rigid heavy-truck load scenarios. First, based on typical daily wind-solar-thermal power output scenarios, a full-state transition model of MESV is established, incorporating coordinated charging/discharging constraints between plant and field sites as well as transportation resource limitations. Then, with the objective of minimizing total operating costs, a mixed-integer linear programming (MILP) method is developed to simultaneously optimize MESV states, charging/discharging power, and transport arrangements. By integrating minimum feasible configuration determination with vehicle-discharge duration coupling analysis, operational thresholds are identified. Finally, multi-scenario simulation results demonstrate that the proposed strategy ensures the temporal continuity of coordinated charging/discharging operations while achieving optimal balance between task completion time and operational economy under the minimum operational boundary, highlighting its practical value in grid-constrained environments.

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    Transmission Capacity Analysis of Low-Frequency AC Transmission System with Onshore Renewable Energy Integration
    XIE Lijun, LU Zhengang, HAO Ruixiang, ZHAO Guoliang, HOU Gaoshan, CUI Jingxin
    2026, 60 (7):  1110-1119.  doi: 10.16183/j.cnki.jsjtu.2024.401
    Abstract ( 299 )   HTML ( 1 )   PDF (2325KB) ( 1081 )   Save

    Flexible low-frequency alternating current (AC) transmission technology features superior transmission capacity and flexible control capability compared with power-frequency AC transmission technology, thereby enabling its application to wide-area collection and delivery of large-scale onshore renewable energy. This paper investigates the transmission capacity of overhead lines to determine the applicable voltage levels and operating ranges of low-frequency systems. First, a function taking the reactance-to-resistance ratio (X/R) as the independent variable is established to analyze the line voltage-current characteristics as well as static voltage stability under different voltages and operating frequencies, and the dominant influencing factors limiting the power transfer capability of low-frequency systems are summarized. Then, the transmission capacity of overhead lines ranging from 10 kV to 1 000 kV is quantified. Calculation results reveal that for 220 kV and above voltage grades, low-frequency overhead lines achieve more than twice the transmission capacity and over three times the transmission radius of standard power-frequency counterparts. Finally, a 220 kV/1 000 MW low-frequency transmission model is built on the PSCAD/EMTDC platform to verify the effectiveness of the proposed low-frequency scheme for long-distance high-capacity power delivery.

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    Quantitative Evaluation Method for Effective Support Capability of Wind Turbine Virtual Inertia
    LI Dongdong, LIU Di, XU Bo, DING Haoyin, LIU Jiachen
    2026, 60 (7):  1120-1129.  doi: 10.16183/j.cnki.jsjtu.2024.479
    Abstract ( 245 )   HTML ( 0 )   PDF (2222KB) ( 358 )   Save

    Virtual inertia provided by wind turbines can effectively improve the inertia level of power systems. However, the quantitative evaluation of the effective support capability of the virtual inertia of wind turbine needs further studies. Therefore, this paper proposes a quantitative evaluation method for the effective support capability of the virtual inertia of wind turbines. First, the system frequency response (SFR) model of a power system with wind turbines is developed, which is compared with the traditional SFR model of the power system to propose the concept of an inertia efficiency factor, and the mapping relationship between the virtual inertia of wind turbines and the inertia of synchronous machine is built from the perspective of frequency response index. Then, considering influencing factors such as control parameters and response delay of the virtual inertia of wind turbines, an expression of the inertia efficiency factor is derived, hence the evaluation formulation of the effective support capability of the virtual inertia of wind turbines is obtained. Finally, simulation results verify the effectiveness of the proposed method.

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    Evaluation Method for Demand Response Interval of Cement Industry Users Considering Multiple Uncertainties
    DUAN Yao, GAO Chong, WANG Xiaoyan, ZHANG Shenxi, CHENG Haozhong, CHENG Ran, ZHANG Junxiao, XU Zhiheng
    2026, 60 (7):  1130-1140.  doi: 10.16183/j.cnki.jsjtu.2024.448
    Abstract ( 112 )   HTML ( 2 )   PDF (2924KB) ( 371 )   Save

    To accurately evaluate the demand response capability of cement industry users for the operation of power system under the fluctuations of process multivariate loads and wind and photovoltaic generation, an evaluation method for the demand response interval of cement industry users considering multiple uncertainties is proposed. First, a box uncertainty set is employed to describe the fluctuation characteristics of process multivariate loads and wind and photovoltaic generation in cement industry users, and the mapping relationship between uncertainty width and conservatism parameter is established. Based on this, the constraints of conservatism parameter are improved, and adaptive optimization of conservatism parameter is used to address the coupling influence among process multivariate loads. Then, a robust optimization evaluation model of the demand response interval of cement industry users with the lowest operating cost as the objective function is built, and the column and constraint generation algorithm is adopted to obtain the operating status of each process equipment. The external response power is used as the boundary to evaluate the demand response interval of cement industry users. Finally, the numerical example shows that the proposed method can effectively evaluate the demand response interval of cement industry users at optimal cost while considering the fluctuations influence of process multivariate loads and wind and photovoltaic generation, providing guidance for cement industry users to participate in power grid dispatching and power trading.

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    Single-Phase-to-Ground Fault Protection on Valve Side of Hybrid Modular Multilevel Converters Based on Thyristor-Branch-Loop
    LIN Jinjiao, ZHU Zijian, ZHENG Junchao, TAO Yan, DENG Fujin
    2026, 60 (7):  1141-1150.  doi: 10.16183/j.cnki.jsjtu.2024.381
    Abstract ( 240 )   HTML ( 1 )   PDF (5022KB) ( 367 )   Save

    In high voltage direct current (HVDC) systems based on modular multilevel converters (MMCs), single phase to ground (SPG) fault on the MMC valve side may lead to serious consequences such as overvoltage damage to the submodules of MMC bridge arms, and affect system reliability. Therefore, this paper analyzes the characteristics of SPG faults on the valve side of traditional hybrid MMC based HVDC systems, and proposes a hybrid MMC topology based on a thyristor-branch-loop for value-side SPG fault protection of the HVDC system. In the proposed topology, each arm consists of full bridge and half bridge submodules, while the thyristor branch connects the three-phase lower-arm inductors to form a loop. In the case of SPG fault, the proposed hybrid MMC can suppress the lower-arm current, clamp the alternating current voltage on the MMC valve side, and interrupt the MMC fault current through the thyristor-branch-loop and blocking submodules. The proposed topology features low overvoltage, short current self-shutdown time, fewer full bridge submodules, and low power consumption. The effectiveness of the proposed topology and control strategy is verified by PSCAD/EMTDC simulation and experiments.

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    Dividend Redistribution Mechanism and Consensus Algorithm for Joint Clearing in Regional Power Markets
    FANG Shengzhe, CHEN Sijie, QIN Yuyao, PING Jian, YAN Zheng
    2026, 60 (7):  1151-1159.  doi: 10.16183/j.cnki.jsjtu.2024.364
    Abstract ( 391 )   HTML ( 2 )   PDF (1513KB) ( 380 )   Save

    In regional power market, electricity generation and consumption resources from different provinces and cities compete on the same platform and are jointly cleared, enabling the free flow and optimal allocation of power resources. However, implementation faces two technical bottlenecks: joint clearing changes the existing distribution of interests among market participants, potentially reducing the interests and motivation of some participants, and the joint clearing and settlement process is complex, opaque, and difficult to supervise, making fairness hard to guarantee. To address these problems, this paper proposes a dividend redistribution mechanism for regional joint clearing and a joint clearing and settlement consensus algorithm which combines the proof of solution consensus mechanism with the traditional Byzantine fault tolerance consensus mechanism. The calculation results show that regional joint clearing can significantly reduce the total regional power supply cost and improve the efficiency of power resource allocation. Besides, the proposed dividend redistribution mechanism can achieve Pareto improvement, ensuring the willingness of market participants to engage in joint clearing. Furthermore, the proposed consensus algorithm enables market participants to reach consensus on clearing results and settlement schemes, ensuring the fairness, feasibility, and transparency of joint clearing.

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    Short-Term Probabilistic Power Forecasting of Photovoltaic Clusters Based on Spatial Encoded Image Generation
    CHEN Junjie, LI Yiyan, ZHOU Zhenghao, YAN Zheng
    2026, 60 (7):  1160-1172.  doi: 10.16183/j.cnki.jsjtu.2024.427
    Abstract ( 509 )   HTML ( 1 )   PDF (5745KB) ( 419 )   Save

    A short-term probabilistic forecasting method for distributed photovoltaic (PV) clusters based on spatial encoding maps is proposed in this paper. First, the distributed PV clusters are encoded into a two-dimensional matrix according to their spatial layout, thereby forming PV output feature maps and weather feature maps. Then, using a conditional generative adversarial network as the forecasting model, the short-term power forecasting problem of the cluster is transformed into a problem of generating future multi-period PV output feature maps under given conditions. Multiple forecast scenarios can be generated by adjusting the input random vectors, thereby constructing probabilistic forecasting results. Finally, the effectiveness of the forecast results is comprehensively evaluated by three metrics: point-to-point error, interval coverage rate, and data distribution similarity. Case study results based on data from the Alice Springs distributed PV project at the Desert Knowledge Australia Solar Centre indicate that the proposed method can fully exploit the spatiotemporal correlations within the cluster, simultaneously providing forecasting results for all PV units in the cluster. Compared with traditional point-wise forecasting methods, the proposed approach achieves higher prediction accuracy and computational efficiency.

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    Traveling Wave Fault Location Technology for Distribution Networks Based on Tunneling Magnetoresistance Current Sensors
    BI Lanxi, ZENG Xiangjun, YU Kun, BAI Hao, YAO Ruotian, LIU Yipeng
    2026, 60 (7):  1173-1182.  doi: 10.16183/j.cnki.jsjtu.2024.382
    Abstract ( 354 )   HTML ( 0 )   PDF (6989KB) ( 452 )   Save

    Existing traveling wave (TW) location devices in distribution networks often struggle to accurately detect fault transient traveling waves, resulting in significant location errors. To address this issue, this paper proposes a TW fault location method based on tunneling magnetoresistance (TMR) current sensors and develops a prototype. First, a TMR-based current measurement method is proposed. Comparative experiments on wide-band transient signal current measurements are conducted, and a compact intelligent TMR sensor with edge computing capabilities is developed to precisely capture fault transient signals. Then, distributed sensors are installed in the distribution network to measure transient current signals. An improved empirical mode decomposition method is employed to reduce noise interference. Subsequently, the energy values of decomposed signals are calculated, and the arrival time of the traveling wavefront is accurately calibrated to achieve precise fault location. Finally, results from simulation and full-scale tests on a 10 kV distribution network demonstrate that the proposed method is effective for accurate fault location, while the sensor devices are easy to install and have significant engineering value.

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    Thermal-Electrical Characteristics and Failure Mechanisms of 26650 Ternary Lithium-Ion Batteries Under Overdischarge at Different Ambient Temperatures
    JIANG Wenjie, ZHOU Xiaoyu, WU Yuhang, LI Canbing, LI Xinxi, WANG Jianpeng, ZENG Run
    2026, 60 (7):  1183-1193.  doi: 10.16183/j.cnki.jsjtu.2024.376
    Abstract ( 707 )   HTML ( 1 )   PDF (5714KB) ( 388 )   Save

    26650 ternary lithium-ion batteries with LiNiCoMnO2 (NCM) as the cathode material have been widely adopted in electric vehicles due to their excellent electrochemical performance and low cost. To investigate the effects of ambient temperature and depth of discharge (DOD) on the overdischarge behavior of these batteries, this paper performs discharge tests at 100%, 110%, 120%, and 130% DOD under normal, low, and high ambient temperatures, followed by impedance analysis before and after the tests. The results show that at low ambient temperatures, the onset of internal short circuits is delayed. During discharge at 110%—130% DOD, severe voltage oscillations may occur, accompanied by an extended time to reach peak temperature and an increased overall temperature rise rate. At high ambient temperatures, the occurrence of internal short circuits is also delayed, while the time required for the battery to reach its maximum temperature is prolonged. Impedance test results indicate that the change in internal resistance is significantly reduced after overdischarge at low ambient temperatures. After 110%, 120%, and 130% DOD overdischarge at high ambient temperatures, the rate of change in internal resistance is higher than that at room temperature. This study reveals the failure mechanisms of 26650 NCM lithium-ion batteries under overdischarge conditions at different ambient temperatures and DOD levels, providing critical support for setting early warning parameters for overdischarge faults and developing preventive strategies against thermal runaway induced by over-discharge.

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    Analysis of Dynamic Characteristics and Coordinated Control Strategies for Fuel Cell-Based Distributed Energy System
    YANG Lu, LI Songyi, XU Jialing, LIU Zuming
    2026, 60 (7):  1194-1206.  doi: 10.16183/j.cnki.jsjtu.2024.529
    Abstract ( 469 )   HTML ( 1 )   PDF (5104KB) ( 536 )   Save

    To address the challenges posed by cross-timescale electrothermal dynamic characteristics and the flexibility and stability requirements resulting from high renewable energy penetration in solid oxide fuel cell (SOFC)-based distributed energy systems, a distributed energy system incorporating SOFCs is proposed. First, an innovative SOFC-assisted peak regulation control strategy is designed based on an analysis of SOFC electrothermal dynamic characteristics across different timescales. Then, the electrothermal dynamic responses and coordinated operation under varying load fluctuations are explored using the Simulink simulation platform. The results indicate that thermal maintenance effectively reduces the thermal inertia of SOFCs, thereby enhancing peak regulation capability and operation stability. The proposed control strategy ensures safe operation while meeting electrothermal demands, providing a theoretical basis for the regulation and stability of SOFC-based distributed energy systems.

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    Degradation Degree Classification of GIS Insulation Surface Defects Based on Mean Value Normalized by Work Function
    ZHANG Zhaoqi, SONG Hui, WANG Zonglin, SHENG Gehao, JIANG Xiuchen
    2026, 60 (7):  1207-1215.  doi: 10.16183/j.cnki.jsjtu.2024.435
    Abstract ( 195 )   HTML ( 1 )   PDF (3291KB) ( 362 )   Save

    Insulation surface defects are common defects inside gas insulated switchgear (GIS). The ultra-high frequency (UHF) method is the most widely used method to detect GIS insulation defects in operation. However, as the mechanisms of signal change during defect degradation remain unclear, the amplitudes of UHF signals cannot be directly correlated with the severity of defects, making it difficult to reasonably divide defect degradation stages. An experiment is conducted to measure UHF signals during the degradation of insulation surface defects and the change mechanism of UHF signals is explored through simulation. Then, a method is proposed to divide the degradation stages of surface defects based on the normalized mean of work function according to the simulation results of UHF signals at different degradation stages. The findings suggest that the surface work function is closely related to the number of discharge pulses and the UHF mean values during the degradation. The UHF mean values normalized by the work function can be used as a criterion for dividing the defect degradation stages into three categories: low, medium, and high. It is verified that the proposed method can effectively divide the insulation surface defect degradation process.

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    Electro-Thermal Aging Characteristics of Polypropylene Films in Pulsed Electric Fields
    XU Yang, CHEN Yang, LI Wei, TANG Yu, CAO Xuanhe, YANG Jinggang, ZHAO Ke, REN Chengyan
    2026, 60 (7):  1216-1226.  doi: 10.16183/j.cnki.jsjtu.2024.525
    Abstract ( 303 )   HTML ( 1 )   PDF (12724KB) ( 412 )   Save

    Biaxially oriented polypropylene (BOPP) is the primary dielectric material used in metallized film capacitors, of which the dielectric, physical, and chemical properties directly affect the performance and service life of capacitors. Currently, the aging mechanisms of BOPP in the complex multi-physical field environment inside capacitors lack sufficient research, and the degradation mechanisms of capacitors remain unclear. Therefore, this paper conducts electro-thermal combined aging experiments of BOPP under pulsed electric fields to examine the breakdown field strength, charge and trap characteristics, and surface composition and morphology of BOPP samples under different aging conditions, and analyzes the impact of pulse parameters and environmental temperature on the aging process of the samples. The results show that at a pulse frequency of 500 Hz and a temperature of 60 ℃, the direct current (DC) breakdown field strength of BOPP samples decreases from 610 kV/mm to 515 kV/mm when the pulse voltage amplitude increases from 1 kV to 5 kV. Under fixed conditions of pulse voltage, the breakdown field strength decreases from 630 kV/mm to 490 kV/mm when the temperature increases from 40 ℃ to 100 ℃. Under synergistic effects of pulse voltage and ambient temperature, BOPP simultaneously undergoes both molecular chain scission and thermo-oxidative aging, leading to a decrease in electrical strength of the samples. Among all aging-related factors, pulse voltage amplitude and ambient temperature have the most significant impact on the degradation in electrical performance of BOPP.

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