23 February 2025, Volume 44 Issue 2

    

• Select all
  |

Treatise and Report
• Select
  High-torque and low-noise IPMSM multi-objective collaborative optimization based on multi-layer surrogate model

  LI Xiaohua, LI Guangxu, HAN Zhongchuan, HAN Xu, WEI Shurong

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 1-12. https://doi.org/10.12067/ATEEE2403004

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  In order to establish the mapping relationship between key electromagnetic force harmonics and structural parameters in the motor NVH design stage, and achieve an orderly, efficient and rapid optimization of high-density and low-noise IPMSM, this paper proposes a multi-layer surrogate model IPMSM optimization method based on structural parameter sensitivity classification. First, the key-order electromagnetic force of the multi-operating electromagnetic noise source of the motor is obtained through the “finite element method + unit force wave response” hybrid model, taking its amplitude, IPMSM’s average output torque, and torque pulsation as optimization targets at the same time, analyzing the sensitivity of structural parameters through the random forest algorithm to achieve screening and grading of structural parameters, integrating multi-objective particle swarm algorithm, multi-island genetic algorithm, parametric scanning and other optimization methods are used for hierarchical optimization. Compared with the traditional motor multi-field coupling optimization method, this method saves computing power and reduces the calculation time by 549%. After optimization, the average output torque is increased by 346% as compared with before optimization, the electromagnetic force amplitude of the key order of the motor decreased by 137% as compared with before optimization, and the torque ripple decreased by 678% as compared with before optimization.
• Select
  Influence analysis of step-up transformer on port impedance of resistive active filter and compensation strategy

  QIN Risheng, KUANG Hua, JIANG He, YU Hui, LI Hong, WAN Mingkai, LI Lei, LEI Wanjun

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 13-23. https://doi.org/10.12067/ATEEE2310033

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  The problem of harmonic pollution has attracted more and more attention as the ‘double high’ characteristics of the power system becoming more and more obvious. For the harmonic resonance amplification phenomenon on the transmission line, the resistive active filter (RAPF) can well suppress this situation. It is usually necessary to connect the step-up transformer in series between the RAPF and the distribution network in order to match the voltage. However, the structure of the transformer will have a certain impact on the original control, which will lead to the weakening of the harmonic suppression effect. Therefore, it is necessary to analyze the equivalent model of the transformer in the harmonic transmission and compensate the influence of the transformer on the control. In this paper, the equivalent model of transformer under harmonic transmission is analyzed and established, and then its influence mechanism on current control is analyzed. Finally, a compensation strategy is proposed to eliminate the influence of transformer on control and improve the ability of RAPF to suppress harmonics.
• Select
  Transient response characteristics and protection adaptability analysis of doubly-fed induction generation transmission lines

  HAN Wei, ZHANG Yuxuan, HAO Gaofeng, HUANG Taiyu, LIU Lei, LI Xiaoyu, SONG Guobing

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 24-32. https://doi.org/10.12067/ATEEE2405022

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  This article analyzes the impact of transient response characteristics of doubly-fed induction generation on traditional protection from the perspective of phasor extraction. Firstly, this article analyzed the relationship between the transient response of doubly-fed induction generation and the rotor side converter as well as crowbar circuit under different fault depths, and obtained conclusions on the transient response analysis of doubly-fed induction generation under different voltage drop levels. Secondly, based on the conclusion of the fault analysis, the impact of the transient response of doubly-fed induction generation on the differential protection and distance protection of the AC line under different fault depths was analyzed from the perspective of phasor extraction. Finally, scenarios of protection malfunction were provided in the article, and reasons for malfunction were explained combined with the fault analysis conclusion.
• Select
  Source-grid-load-storage planning of integrated energy system for large buildings

  TAN Xiaolin, AN Jiakun, ZHANG Runfan, ZHAO Yang, YANG Shuqiang, LIU Zixuan

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 33-43. https://doi.org/10.12067/ATEEE2307042

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  Scientific planning and optimized configuration of comprehensive energy distribution systems have significant practical engineering implications for improving the operation and overall performance of integrated energy systems in large buildings. This article proposes a multi-objective optimization method for comprehensive energy distribution systems that includes wind and solar energy, gas, and hybrid energy storage. First, a composite objective function is proposed that takes into account operating economics, life-cycle costs of energy storage systems, and low carbon emissions over multiple periods. A constraint model is established that considers the coordinated operation of new energy and energy storage systems for heating and power generation. Then composite objective optimization planning is carried out in several typical scenarios during the year when new energy output corresponds to heating and power generation needs, and the optimal design of the hybrid energy storage system is obtained. Finally, a large-scale building energy example is illustrated using YALMIP+CPLEX to verify the feasibility of this method. The results show that this method can be used to plan source-network-load-storage for comprehensive energy distribution systems, thereby improving the overall performance and efficiency of the system.
• Select
  Resilience assessment of power system considering mobile energy storage pre-arrangement under severe convective disaster

  LI Zhe, WANG Jian, LIU Shanfeng, WANG Delin, WANG Jinyu

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 44-54. https://doi.org/10.12067/ATEEE2402012

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  To address the need for operational risk assessment and resilience improvement for power systems under extreme disasters, a resilience assessment method for power systems considering mobile energy storage pre-arrangement is proposed in this paper. First, a fault probability prediction model for grid equipment and a meteorological condition dependent output model for distributed generation are constructed with input from strong convective weather forecast information to assess the time-varying risk level of the power system. Second, a pre-arrangement scheme for mobile energy storage is proposed with the goal of minimizing the amount of mobile energy storage and its transportation cost and load shedding cost by considering the constraints of mobile energy storage resources, spatial-temporal scheduling, path planning, and network traffic. The resilience of the power system is then evaluated using the missing area of the system function curve, the load level of the continuous power supply, and the load loss rate as resilience metrics. Finally, for a severe convective weather process, the proposed method is validated in a modified IEEE 30-bus power system. The results show that, compared with the case of not using the mobile energy storage pre-arrangement scheme, the total cost can be reduced by 7805% and the resilience of the power system can be improved, which can provide reference for the emergency plan of the power system under severe convective disasters.
• Select
  Research on active arc extinguishing technology for flexible distribution network interconnection system under grounding faults

  YANG Jindong, ZHANG Xiran, HUANG Chunhui, RONG Fei

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 55-64. https://doi.org/10.12067/ATEEE2311046

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  Addressing the problem of low arc-extinguishing accuracy of passive devices and high arc-extinguishing cost of active devices, this paper proposes a flexible distribution network interconnection system to address single-phase ground faults. The system consists of a phase-separated networking device and two power distribution networks, which can improve the power quality and enhance the load rate of power supply transformers during normal operation of the distribution network. Upon occurrence of a single-phase ground fault, the system disconnects the non-fault phase circuit breakers used to access the faulty distribution network, achieving reliable arc extinction by injecting current through the fault phase bridge arm. The control modes of the flexible distribution network interconnection system in various operating states of the distribution network and the necessity of mode switching are analyzed. Simulation results demonstrate that the proposed method can achieve fault arc extinction without the need for additional arc extinction devices, while maintaining the function of regulating the power quality of the non-fault power distribution network, thus exhibiting superior arc extinction effectiveness and cost-effectiveness.
• Select
  Photovoltaic access capability evaluation of distribution networks based on adversarial neural networks and K-means++ clustering

  ZHANG Jiamei, SUN Kai, SUN Pei

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 65-73. https://doi.org/10.12067/ATEEE2311029

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  The widespread and extensive access of distributed photovoltaics has a significant impact on the planning and operation of distribution networks. How to evaluate the maximum accessible capacity of existing distribution networks is the foundation for guiding the safe consumption of distributed photovoltaics. Considering the impact of photovoltaic output uncertainty on the evaluation results, this paper proposes a method for evaluating the photovoltaic accessible capacity of distribution networks based on generative adversarial networks (GAN) and K-means++ clustering analysis. This method automatically learns the complex spatiotemporal relationships explicitly modeled between photovoltaic output data through GAN, generating a sufficient amount of “false” data that can reflect real weather conditions. Using K-means++ clustering analysis method for scene reduction and typical scene generation, based on typical scenarios, an optimization model is constructed with the goal of maximizing photovoltaic access capacity while meeting the constraints of safe operation and using second-order cone optimization to linearize the power flow model of the distribution network. Finally, the results of the proposed method are analyzed and evaluated based on the IEEE 33 node distribution network. The calculation results verify that the capacity optimization method proposed in this article can comprehensively consider the impact of different weather types and provide a photovoltaic access scheme that is more in line with actual operational requirements.
• Select
  Copula function based on second-order cone relaxation optimal power flow and robust weighted K-Means method for PV carrying capacity evaluation

  LI Cuiping, WANG Yanli, ZHU Xingxu, QI Xuesong, GUAN Xiaozhuo, LI Junhui, CHANG Zhihua, BAI Yanyang, LI Huashun

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 74-88. https://doi.org/10.12067/ATEEE2410039

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  In this paper, the PV carrying capacity as well as the enhancement of PV carrying capacity is investigated based on the consideration of PV uncertainty and source-load correlation. Firstly, a source-load correlation method based on Copula function combined with improved Latin hypercubic sampling is proposed to generate the source-load correlation matrix. Afterwards, a robust K-Means method is used to cluster the source-load correlation matrix to generate typical scenarios. Then, considering the influence of economic and technical indicators on the carrying capacity results, a second-order cone relaxation optimal current planning model for PV carrying capacity assessment with the objective of minimising the total cost of investment and operation is established, and the YALMIP and CPLEX solvers are used to find the optimal solution for the model. Finally, the effectiveness of the proposed method is verified by the IEEE-33 node simulation.
• Select
  Short-term photovoltaic power interval prediction based on mechanism model and XGBoost

  YUAN Wei, PEI Wei, ZENG Zeng, ZHANG Rui, TENG Changzhi, ZHAO Zhenxing

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 89-97. https://doi.org/10.12067/ATEEE2310034

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  With the increasing scale of distributed photovoltaic power generation, accurate prediction of photovoltaic power generation is very important for the safe and stable operation of power systems. In order to improve the accuracy of photovoltaic power prediction, an integrated model based on mechanism model and extreme gradient boosting algorithm is proposed for short-term distributed photovoltaic power probability interval prediction. Firstly, combined with the meteorological data, a density-based spatial clustering of applications with noise algorithm is used to design a photovoltaic power data governance method to filter out abnormal data in historical data. Then, the integrated model is constructed based on the optimized samples after screening. Specifically, the basic photovoltaic power prediction model is constructed based on the mechanism model for preliminary prediction, and the prediction results and other environmental data are used as input variables of the XGBoost model, and then the prediction error generated by the basic prediction model is corrected. Different feature data are extracted to train the mechanism model and XGBoost model and forecast respectively. Finally, the prediction error probability density function is established by non-parametric kernel density estimation, and the fluctuation range of photovoltaic power is predicted at a certain confidence level. The accuracy and effectiveness of the method are verified by the actual data of photovoltaic power station.
• Select
  Study on influence of different arc burning time on breaking performance of asymmetric short circuit current of certain UHV SF₆ circuit breaker

  WEI Ying, WANG Daqi, MA Feiyue, XIANG Bin, LI Longqi, WANG Dongyu, DU Huixin, LIU Zhiyuan

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 98-105. https://doi.org/10.12067/ATEEE2311020

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  In this paper, based on the T100a test of a certain type of UHV pneumatic SF6 circuit breaker, the T100a breaking test of EHV pneumatic SF6 circuit breaker is tested by using a nanosecond current zero zone measuring device. The variation rules of arc key parameters such as arc peak, pre-zero arc conductance and arc current are studied when interrupting high DC component asymmetric short circuit current under different arc time. At the same time, based on the internal structure of the circuit breaker, the physical simulation model of gas arc enthalpy flow is established to study the pressure and distance change of the pressure chamber at different arc times. The results show that under the same on-off current, the longer the arc burning time is, the larger the arc quenching peak is and the smaller the pre-zero arc conductance is. At the same time, the pressure of the compressor chamber and the contact distance also increase positively with the arc time, which makes it easier for the circuit breaker to break, and that provides a theoretical basis for the SF6 circuit breaker to break the asymmetric short-circuit current in practical application.
New Technolog Application
• Select
  Research on fault diagnosis of low-voltage circuit breaker based on vibration and coil current signals

  PENG Wei, ZHANG Gang

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 106-115. https://doi.org/10.12067/ATEEE2405091

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  To guarantee the stability and reliability of low-voltage circuit breakers within power supply systems, this paper proposes a fault diagnosis method that is based on a combination of Genetic Algorithm (GA) and Deep Belief Network (DBN). The proposed method employs features derived from multi-physical domain information as input to the network for the purpose of diagnosing faults in low-voltage circuit breakers. Firstly, vibration and current signals from the circuit breakers are collected via sensors and denoised using wavelet soft thresholding to preserve feature information effectively, avoiding losses typical in conventional methods. Subsequently, time-domain and frequency-domain features are extracted from both signal types to form a multi-physical domain feature matrix, which serves as input for subsequent modeling. The multi-physical domain feature matrix is then fed into a DBN neural network for fine-tuning, with GA optimizing the network’s weights and thresholds to enhance fault diagnosis accuracy. Experimental results demonstrate that the proposed model achieves a diagnostic accuracy of 9846%. Compared to models using vibration or current signals alone, this represents an improvement of 149% and 679%, respectively. This fully demonstrates the superior performance of the multi-physical domain-based GA-DBN diagnostic model in fault diagnosis of low-voltage circuit breakers, further validating the criticality and practicality of this technology in the intelligent power supply system of subways.
• Select
  An online rapid diagnosis method for lithium-ion battery’s state of health based on multi-point impedance

  YU Siqi, MU Xianmin, CHEN Xiyou, FAN Xianguo, YAN Wenqian

  Advanced Technology of Electrical Engineering and Energy. 2025, 44(2): 116-128. https://doi.org/10.12067/ATEEE2307009

  Abstract ( ) Download PDF ( )   Knowledge map   Save

  With the widespread use of lithium-ion batteries, rapid diagnosis of the health state of lithium-ion batteries has attracted extensive attention. Aiming at the traditional impedance diagnostic methods, which are affected by the change of state of charge (SOC) during online measurement, involving complex calculations, and less impedance information obtained, this paper conducts electrochemical impedance spectroscopy on lithium-ion batteries with different states of charge (SOH) and different states of health (SOH) and establishes a more physically interpretable equivalent circuit model by decoupling the complex dynamics in lithium batteries through the distribution of relaxation time (DRT) method. Based on the dependence of the characteristic peaks of the relaxation time distribution function on the SOC and SOH, three characteristic frequency points are screened for online impedance measurements. A fast online SOH estimation method with multi-point impedance is proposed, which can infer the state of health of the battery based on the characteristic impedance measurement data injected by the superposition of multiple feature frequency points at a time. It is experimentally verified that the method has good accuracy and practicality in online battery characteristic parameter measurement and health state estimation.