23 June 2026, Volume 45 Issue 6

    

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Treatise and Report
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  Equivalent magnetic network of no-load model for line-start permanent magnet synchronous reluctance motor based on hybrid grid method

  WANG Zicheng, LI Yan, YU Zhanyang, WANG Jin

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 1-12. https://doi.org/10.12067/ATEEE2404004

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  In order to analyze the no-load performance efficiently and accurately, an equivalent magnetic network model of no-load for line-start permanent magnet synchronous reluctance motor is proposed. The model firstly equates the multi-layer permanent magnet of the motor with the complex structure such as magnetic barrier, slots of stator and rotor. Secondly, based on the grid method, the hybrid cross mesh permeability is constructed in the disordered magnetic field area, the cross mesh is applied to the magnetic bridge and the air gap, and the improved cross mesh is applied to other areas. The magnetic permeability and magnetic potential of each area are calculated, and the magnetic network equation in matrix form is established. Finally, the influence of the core saturation of stator and rotor is considered for iteration. Theoretical analysis is made on the electromagnetic performance of the motor with slots of both stator and rotor under no load. Taking a 4-pole 5.5 kW line-start permanent magnet synchronous reluctance motor with 36/44 slots of stator and rotor as an example, the electromagnetic properties of the motor under no-load, such as the radial air gap flux density and the radial electromagnetic force density, are respectively considered, and the effects of different grid layers of the air gap on the calculation accuracy and time are compared. The accuracy of the equivalent magnetic network model is verified by finite element method and experiment, which provides theoretical guidance for the analytical calculation of this type of motor.
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  Study on optimization of rotor hole placement in high-speed aviation asynchronous motors based on multi-physics fields

  ZHU Jun, HU Longhao, LI Yifei, FENG Haichao, AI Liwang, LIU Tongliang

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 13-24. https://doi.org/10.12067/ATEEE2506016

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  In light of the high performance, reliability, and lightweight characteristics of high-speed aviation asynchronous motors, this paper proposes a rotor hole placement and collaborative optimization design method based on multi-physics field analysis results. A 15 kW motor rotor is analyzed using the finite element method to assess electromagnetic performance, modal analysis, and stress distribution. Comprehensive sensitivity analysis identifies the impact of rotor lightweight design on multi-physics fields. The effects of key parameters, such as hole shape and size, on rotor performance are examined, and main objective factors are selected for multi-objective optimization. Optimization is performed using the fast non-dominated sorting genetic algorithm, followed by prototype fabrication and experimental validation. Results show that the optimized design reduces rotor mass by 13.2%, improves power density, and enhances dynamic characteristics, confirming the feasibility of the optimization method and providing a practical approach for high-speed aviation motor rotor design.
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  Robust model predictive control strategy for grid-connected inverters based on Smith predictor

  LIU Chunxi, HONG Fangrui, LIN Zhiwei, XU Ke, SUN Huaze

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 25-38. https://doi.org/10.12067/ATEEE2407076

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  The traditional finite control set model predictive control (FCS-MPC) for LCL-type grid-connected inverters suffers from calculation delays and parameter mismatches, which lead to decreased prediction accuracy. To address this issue, a robust model predictive control strategy based on a Smith predictor for grid-connected inverters is proposed. Firstly, to suppress the high-frequency resonance peaks in the frequency response of the LCL filter and simplify the control algorithm, a reduced-order mathematical model of the grid-connected inverter is established using a weighted average current strategy. Secondly, an extended state observer (ESO) is designed to achieve lumped estimation of model parameter perturbations and provide feedforward compensation. Third, to mitigate the delay introduced by system computation, and considering that such delay might cause the two signals entering the ESO to become unsynchronized, leading to inaccurate disturbance estimation by the ESO, a Smith predictor is introduced to form an enhanced ESO with delay compensation functionality. This setup compensates for delays in the FCS-MPC system while reducing the impact of computational delay on the ESO’s performance. Finally, the effectiveness of the proposed control strategy is verified through simulations and experiments.
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  Study on power allocation strategy of grid-forming converters under asymmetric faults in power grid

  MA Tinghao, DU Xiong, ZHANG Jie, CAO Qingshan

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 39-49. https://doi.org/10.12067/ATEEE2502008

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  When an asymmetric fault occurs in the power grid, the grid-connected system of grid-forming converters (GFM) will encounter power quality issues such as over-limit fault currents, DC voltage fluctuations, and triple-frequency harmonic currents. To ensure that the power quality of the GFM output during the fault meets the grid-connection requirements and to provide a certain amount of reactive power support for the system, this paper proposes a GFM power coordination control strategy under asymmetric grid faults. Firstly, based on the GFM grid-connected topology, the analytical expressions and constraint conditions of the GFM active power fluctuation amplitude and the maximum phase current under asymmetric faults are derived, and the safe operating region of the GFM is obtained. Subsequently, a reactive power-prioritized GFM power coordination control strategy is proposed based on the safe operating region, which precisely regulates the active power output on the premise of meeting the reactive power support requirements of the system. Finally, the accuracy of the theoretical analysis and the effectiveness of the power control strategy in this paper are verified based on the Matlab/Simulink simulation platform.
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  Evaluation of stress state in grain-oriented silicon steel using magnetic Barkhausen noise

  QIAO Zhi, LI Lin

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 50-60. https://doi.org/10.12067/ATEEE2503026

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  Magnetic Barkhausen noise (MBN) is a high-frequency electromagnetic signal generated by irreversible magnetic domain wall jumps during the magnetization of ferromagnetic materials. It exhibits high sensitivity to microstructural variations, compositional changes, and stress states, making it widely applicable in non-destructive testing of ferromagnetic materials. When grain-oriented silicon steel is subjected to mechanical stress in directions deviating from its easy magnetization axis, the MBN signal undergoes alterations due to the material’s anisotropic magnetization characteristics. This study investigates the variations in multiple MBN signal features of grain-oriented silicon steel sheets (30RK105) under tensile stresses of varying magnitudes and directions. Principal component analysis is employed to extract the most influential features contributing to MBN signal changes. Combined with multiple linear regression, the magnitude and direction of applied tensile stress are quantitatively evaluated. The accuracy of the proposed method is validated through calculations of root mean square error and correlation coefficient.
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  Study on effect of no-load commissioning inrush current of converter transformers on AC filters protection

  PAN Zhicheng, ZHANG Zhanlong, LYU Jinzhuang, DENG Jun, HOU Mingchun, XIE Zhicheng, GAO Jiatai, PEI Xichen

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 61-71. https://doi.org/10.12067/ATEEE2502041

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  In LCC-HVDC converter stations, the inrush current generated by converter transformers during no-load commissioning often causes the tripping of AC filter protection. However, current research on the impact of inrush current during no-load commissioning on AC filter protection is insufficient and has not clearly identified the reasons for protection tripping. This paper analyzes the time-frequency characteristics of inrush curre nt, and the impedance and shunting characteristics of the AC filter, combines these with the operating principles of the AC filter protection device, quantifies the impact of inrush current on AC filters, and clarifies that the greatest threat of inrush current to AC filter protection is the overloading of resistors in AC filters caused by the third harmonic. The study is verified by using a recorded inrush current waveform from ±800 kV Kunbei Converter Station and a simulation analysis was conducted on the factors affecting the overload of the AC filter resistor. The results show that the slowly decaying sympathetic inrush current can directly lead to resistor overload, and ±800 kV Kunbei Station can withstand an inrush current peak of approximately 6 300~6 500 A.
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  Simulation and study of temperature field of 10 kV T-type cable joint and its influencing factors

  CHEN Daoyuan, YANG Mingyuan, NIE Yongjie, HUANG Bo, WANG Jiayin, ZHAO Xuetong

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 72-81. https://doi.org/10.12067/ATEEE2412034

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  With the development of power distribution systems and the acceleration of urbanization, power cable transmission is advancing toward higher loads, safety, and reliability. The cable branch box, as an essential component of the distribution network, houses the 10 kV T-type cable joint, which serves as a core element within the box. The operational state of the T-type cable joint directly affects the safety and reliability of the power system. Based on the finite element analysis method, this study employs COMSOL Multiphysics software to establish a three-dimensional electro-thermal-fluid coupling model of the cable branch box and its internal T-type cable joint. The work investigates the effects of current load, ambient temperature, airflow velocity, and the number of ventilation openings on the temperature field distribution of the joint. The results reveal that variations in current load lead to a nonlinear increase in the joint temperature, the rise in ambient temperature significantly amplifies the temperature increase of the joint, and ventilation conditions present a more pronounced effect on the temperature field distribution. Specifically, airflow velocity within a certain range greatly enhances cooling performance, but the cooling effect saturates beyond a threshold. Additionally, increasing the number of ventilation openings improves cooling efficiency, especially under high-load operating conditions. This study provides theoretical support for the optimization of cooling systems in cable branch boxes and offers valuable insights for the operational management and fault prevention of cables and T-type cable joints.
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  Unit commitment model and solution algorithm considering dynamic line rating

  TANG Chong, LIU Yuzheng, JIANG Youquan, DAI Jiang, TIAN Nianjie, XUAN Peizheng, CHENG Lanfen, YAO Wenfeng, XIAO Yang, DING Tao

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 82-91. https://doi.org/10.12067/ATEEE2407003

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  To enhance the transmission capacity in power system scheduling computations, this paper proposes a multi-scenario unit commitment model considering dynamic line capacities, accompanied by a Lagrangian relaxation solving algorithm tailored for the model. Initially, leveraging quantile regression principles, a data-driven dynamic line capacity augmentation model is constructed based on historical environmental parameter data. Next, the dynamic transmission line model is embedded into a multi-scenario unit commitment framework, thereby forming a unit commitment model that accounts for fluctuating line capacities. Lastly, system constraints within the model are relaxed and decomposed into multiple subproblems, which are then resolved through an iterative algorithm until convergence is achieved. The proposed unit commitment model and its corresponding algorithm are applied to IEEE-118 and IEEE-300 test systems, validating the efficacy and feasibility of both the model and the algorithm.
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  Abnormal electricity usage detection based on improved grey wolf optimization and density peak clustering

  ZHANG Haoyu, WANG Chaoqun, CHEN Le

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 92-102. https://doi.org/10.12067/ATEEE2508028

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  To address the instability and insufficient detection accuracy of density peak clustering (DPC) caused by manual setting of the cutoff distance, this study proposes an anomaly detection method combining improved grey wolf optimization and DPC. An improved chaotic mapping is employed to uniformly initialize the grey wolf population, and a nonlinear decaying convergence factor is designed to dynamically balance global exploration and local exploitation. The Davis-Bouldin index is used as the fitness function to automatically optimize key DPC parameters, achieving parameter adaptivity. Case studies on electricity consumption datasets from multiple regions and comparative experiments against mainstream anomaly detection algorithms show a notable improvement in AUC relative to the baseline, validating the method’s significant advantages in detection accuracy and stability.
New Technolog Application
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  Modeling of symmetrical two-core phase-shifting transformer and calculation of inter-turn short circuit current

  TIAN Yuan, MA Cheng, GAO Shuguo, ZHANG Fan, JI Shengchang

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 103-109. https://doi.org/10.12067/ATEEE2408039

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  Phase-shifting transformers (PSTs) can effectively control power flow distribution within an electrical grid by adjusting and regulating parameters such as voltage magnitude, phase angle, and line reactance at nodes and transmission lines. This paper focuses on a symmetrical dual-core phase-shifting transformer. Through phasor analysis and calculations of its unique topological structure, the phase shift angle and equivalent impedance under steady-state operation are determined. A Simulink simulation model of a 230 kV/370 MV·A phase-shifting transformer was developed to obtain technical parameter values under different tap positions, verifying its phase-shifting functionality. Furthermore, the current characteristics under inter-turn short-circuit conditions were analyzed. The research results indicate that the equivalent impedance of the phase-shifting transformer is minimal at the 0 tap position and increases as the tap position moves away from zero (either increasing or decreasing). Compared to a conventional two-winding transformer, when an inter-turn short circuit occurs on the primary side of the dual-winding phase-shifting transformer, the primary current of the phase-shifting transformer increases and shows an upward trend with the increase of the short-circuit turns, while the secondary current remains basically unchanged. The research conclusions can guide the condition analysis and assessment of phase-shifting transformers.
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  Heavy gas action characteristics and setting method of gas relay under transient oil flow impact

  XUE Bing, TIAN Siyu, YI Wanshuang, LIU Chengxiang, LIU Wei, WAN Shuting

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 110-118. https://doi.org/10.12067/ATEEE2503002

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  In traditional gas relay, heavy gas trip is judged according to the flow velocity in the pipeline, but heavy gas maloperation often occurs. In order to fully explore the action mechanism of heavy gas, a new type of gas relay that can monitor the angle of the baffle is developed, and the heavy gas signal of the gas relay and the dynamic characteristics of the baffle under the impact of transient oil flow are further studied. The flow velocity, pressure, heavy gas and the angle signal of the baffle are collected synchronously, and the correlation between the collected signals is analyzed. The test and simulation results show that under low energy excitation, heavy gas action and baffle opening depend on pipeline flow velocity. Under high energy excitation, heavy gas action and baffle opening depend on pipeline oil flow pressure. At the end of heavy gas operation and the return of baffle, the pressure decays quickly, and the return of heavy gas operation and baffle is maintained by the oil flow velocity. On this basis, a method of heavy gas action setting of gas relay is proposed, which takes into account the characteristic quantity of pipeline oil flow velocity and pressure, and can be used as the auxiliary decision basis of heavy gas trip signal of gas relay.
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  A bad data identification method based on Spark random forest in DC transmission system

  XIAO Chao, GUO Pei, LIN Yaowei, OUYANG Jinxin, WANG Mo, DONG Manling

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 119-129. https://doi.org/10.12067/ATEEE2409042

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  With the development of UHV DC transmission technology, DC measurement equipment represented by fiber-optic current transformers, DC voltage dividers, and zero-flux transformers have been applied in large numbers. However, DC measurement data may have accuracy and drift problems due to equipment quality defects, poor safety processes, and long-term operation aging. The self-test logic of DC measurement equipment cannot fundamentally avoid the influence of bad data, and the existing power system bad data identification methods cannot meet the requirements of DC control and protection reliability and rapidity. To this end, the characteristics of bad data of DC measurement devices are analyzed, a training method for generating bad data of DC measurement devices is proposed, and a training method for bad data identification model of DC measurement devices is proposed, so as to propose a bad data identification method for DC transmission system based on the improvement of Random Forest in Spark, and the validity of the proposed method is verified by the arithmetic examples. The method introduces Spark architecture to improve the speed of DC measurement equipment abnormal data identification, and uses generative algorithms to improve the data distribution and enhance the accuracy of DC measurement data bad data identification.
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  Defect detection algorithm of photovoltaic panel based on fusion of attention guidance and multi-scale features

  ZOU Hao, LI Yang, GUO Yuting, YANG Jinbiao, HE Guochun, WU Feng

  Advanced Technology of Electrical Engineering and Energy. 2026, 45(6): 130-144. https://doi.org/10.12067/ATEEE2409058

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  Aiming at the problems of low detection accuracy and poor real-time performance caused by complex background and small scale targets in photovoltaic panel defect detection, a photovoltaic panel defect detection algorithm based on attention guidance and multi-scale feature fusion was proposed, called PP-YOLO. In order to enhance the feature extraction ability of irregular targets and improve the detection speed, AKConv(Alterable Karnel Convolution) is used to replace some traditional convolution in the backbone network. The spatial attention and channel attention (SACA) mechanism is proposed in the neck network to integrate spatial attention information and channel attention information simultaneously to reduce the interference of background noise. A self-attention module (SAM) embedded neck network is constructed. By capturing the global feature relationship and focusing on local semantic information, more low-level detailed features are retained, and a high-resolution detection head is added to the detection layer, so as to achieve accurate identification of small defect targets. The experimental results show that on the self-made PV panel defect detection data set, PP-YOLO ’s mAP reaches 95.28%, which is significantly better than the baseline model and other mainstream detection algorithms. In addition, the comparative results of embedded experiments further verify that PP-YOLO can still achieve efficient and accurate real-time detection under the environment of limited computing resources, and can provide effective technical support for real-time defect identification and automated maintenance.