Iet Electric Power Applications最新文献_第3页

Research on Dynamic Reduced-Order Model for Fast Calculation of Transient Temperature Field in Transformer Windings 快速计算变压器绕组瞬态温度场的动态降阶模型研究

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-07-01 DOI: 10.1049/elp2.70056

Kexin Liu, Dongyang Li, Yunpeng Liu, Gang Liu, Zhenbin Du, Shuqi Zhang, Ke Wang, Xiaolin Zhao

{"title":"Research on Dynamic Reduced-Order Model for Fast Calculation of Transient Temperature Field in Transformer Windings","authors":"Kexin Liu, Dongyang Li, Yunpeng Liu, Gang Liu, Zhenbin Du, Shuqi Zhang, Ke Wang, Xiaolin Zhao","doi":"10.1049/elp2.70056","DOIUrl":"https://doi.org/10.1049/elp2.70056","url":null,"abstract":"To mitigate the potential loss of computational accuracy in the Reduced-Order Model (ROM) due to modal changes during transformer operation, this paper proposes a dynamic updating method for the ROM. This method enables the model to dynamically adjust and adapt to system changes. When transformer operating conditions change, new snapshot data is employed to update the original snapshot matrix, while the POD modes are updated by integrating matrix low-rank decomposition with the Singular Value Decomposition (SVD) results of the original snapshot matrix—thus avoiding the need of SVD for the new snapshot matrix. By incorporating discrete measurement data from the winding temperature, the modal coefficients are solved in real-time based on Gappy POD, facilitating the construction of the dynamic ROM. The proposed method was validated using a simulation model of 110 kV transformer windings. The results demonstrates that the maximum error in updating the POD modes is only 3.60 × 10−6, with a single update requiring approximately 0.12s. Furthermore, the dynamic ROM reduces the maximum error by 1.78 K. Without considering the snapshot matrix formation time, the average computation time for each time step is about 0.02s. This study presents a novel solution for the dynamic application of the ROM in the transformer temperature field.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Attention-Guided Semi-Supervised Model for Power Transformer Fault Diagnosis via Vibration-Acoustic Data Fusion 基于振动-声数据融合的电力变压器故障诊断的注意力引导半监督模型

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-07-01 DOI: 10.1049/elp2.70062

Yanfei Sun, Tao Zhao, Li Gao, Yunpeng Liu

{"title":"An Attention-Guided Semi-Supervised Model for Power Transformer Fault Diagnosis via Vibration-Acoustic Data Fusion","authors":"Yanfei Sun, Tao Zhao, Li Gao, Yunpeng Liu","doi":"10.1049/elp2.70062","DOIUrl":"https://doi.org/10.1049/elp2.70062","url":null,"abstract":"Reliable fault diagnosis of power transformers is vital for ensuring the safe and continuous operation of power systems. Although deep learning methods have shown success with single-sensor data, their diagnostic performance remains limited due to the inability to capture complex, multimodal fault characteristics. To address this, we propose an attention-guided semi-supervised vibration-acoustic fusion (AG-SVAF) model, which combines vibration and acoustic signals to enhance diagnostic robustness under limited labelled data conditions. The model integrates time-frequency representations derived via short-time Fourier transform (STFT) with a multilevel attention mechanism—including channel, spatial and self-attention—to highlight fault-relevant features and model cross-modal dependencies. A novel attention-weighted consistency loss further improves the utilisation of unlabelled data during training. Validated on practical transformer datasets, AG-SVAF achieves superior performance in terms of diagnostic accuracy and stability, particularly under challenging scenarios involving class imbalance and label scarcity. This approach provides a promising and scalable solution for intelligent condition monitoring in real-world power system applications.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Thermal Analysis and Improved Thermal Modelling of a 200 kW Traction Induction Motor in Urban Electric Train Application 200kw牵引感应电动机在城市电力列车中的热分析及改进热建模

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-06-30 DOI: 10.1049/elp2.70049

Mohammad Rasool Khazaeli, Amir Rashidi, Sayed Morteza Saghaian Nejad, Esmaeil Keyvanloo

{"title":"Thermal Analysis and Improved Thermal Modelling of a 200 kW Traction Induction Motor in Urban Electric Train Application","authors":"Mohammad Rasool Khazaeli, Amir Rashidi, Sayed Morteza Saghaian Nejad, Esmaeil Keyvanloo","doi":"10.1049/elp2.70049","DOIUrl":"https://doi.org/10.1049/elp2.70049","url":null,"abstract":"One important usage of electric motors is railway transportation. There are different types of motor analyses available in railway transportation such as electromagnetic, thermal and mechanical analyses. The goals of thermal analysis are to calculate and monitor motor temperature in components, avoid motor damage, insulation break and increase lifetime. Methods of thermal analysis include: lumped parameters (LP), finite element (FEA) and computational fluid dynamics (CFD). Good analysis should be suitable for the motor type and geometry, obtain good accuracy and reduce time consumption. In this paper, the authors perform the thermal analysis of a self-ventilated 200 kW induction traction motor used in urban trains. First, the thermal network is created and the proposed LP approach is provided to calculate temperatures. This model consists of two steps which makes calculation easier, takes less time and can be used for complex parts without changing the whole model. The temperatures of important parts such as end winding can be calculated by the proposed model with simple equations, without any change in motor parameters matrix, so the proposed model is more flexible and can be used for different cases. Then, FEA and CFD are used to simulate the motor. Some model parameters are optimised using equations to make the model more accurate. Finally, simulation results are compared with experimental test results in order to validate motor performance and the proposed model results.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Electromechanical Coupling Resonance Suppression Method for IPMSM Drive System Considering the Fluctuation of DC-Link Voltage 考虑直流电压波动的IPMSM驱动系统机电耦合谐振抑制方法

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-06-21 DOI: 10.1049/elp2.70050

Junwen Mu, Xinglai Ge, Chunxu Lin, Yun Zuo

引用次数: 0

Fault-Tolerant Control of a High-Reliability Six-Phase Axial Flux Switching Permanent Magnet Machine 高可靠性六相轴向磁通开关永磁电机的容错控制

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-06-18 DOI: 10.1049/elp2.70055

Javad Rahmani-Fard, Ali Mohammed Ridha, Mustafa Habeeb Chyad, Mohammed Jamal Mohammed

{"title":"Fault-Tolerant Control of a High-Reliability Six-Phase Axial Flux Switching Permanent Magnet Machine","authors":"Javad Rahmani-Fard, Ali Mohammed Ridha, Mustafa Habeeb Chyad, Mohammed Jamal Mohammed","doi":"10.1049/elp2.70055","DOIUrl":"https://doi.org/10.1049/elp2.70055","url":null,"abstract":"In this study, a novel six-phase axial flux switching permanent magnet machine (AFFSSPM-TS) with a twisted structure is explored to enhance fault tolerance and overall system reliability. This design integrates the advantages of flux switching permanent magnet (FSPM) machines, such as high-power density and robust structural characteristics, while significantly improving fault resilience. The machine's electromagnetic behaviour and fault-tolerant capabilities are assessed through experimental validation. To ensure stable torque output under single-phase faults, an advanced control strategy is introduced, regulating the q-axis current and zero-sequence components within the synchronous reference frame. This approach effectively mitigates torque loss caused by phase disconnection while optimising copper losses. Furthermore, a weighted multi-objective optimisation framework, utilising a Genetic Algorithm (GA), is implemented to refine the fault-tolerant current references, maximising torque output and minimising energy dissipation under fault conditions. For short-circuit faults, a compensation strategy based on fault decomposition is developed, eliminating the need for complex real-time computations by directly compensating for faulty phase currents. Experimental results on a prototype machine confirm the proposed control strategy's effectiveness in maintaining torque performance and fault-handling capability.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid Electromagnetic Modelling of Tubular Permanent Magnet Linear Motors Based on Transfer Learning Physics-Informed Neural Networks 基于迁移学习物理信息神经网络的管状永磁直线电机混合电磁建模

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-06-14 DOI: 10.1049/elp2.70057

Jiale Guo, Tao Wu, Xinmei Wang, Xiongbo Wan

{"title":"Hybrid Electromagnetic Modelling of Tubular Permanent Magnet Linear Motors Based on Transfer Learning Physics-Informed Neural Networks","authors":"Jiale Guo, Tao Wu, Xinmei Wang, Xiongbo Wan","doi":"10.1049/elp2.70057","DOIUrl":"https://doi.org/10.1049/elp2.70057","url":null,"abstract":"Due to the inherent nonlinearity and saturation in the magnetic circuits of tubular permanent magnet linear motors, the analytical method (AM), while computationally efficient, often fails to capture complex electromagnetic behaviours accurately. In contrast, the finite element analysis (FEA) offers high precision but is time consuming. The nonlinearity of magnetic materials introduces strong input–output coupling, while saturation leads to localised deviations in field distributions, both of which reduce the effectiveness and generalisability of conventional modelling approaches. To overcome these challenges, a physics-informed, data-driven modelling approach is proposed. Initially, a novel hybrid modelling framework based on physics-informed neural networks (PINNs) is introduced. In this framework, AM is incorporated into both the input-output layers and the relevant variables, thereby enabling the direct embedding of physical constraints into the loss function. Consequently, the network's training process is rigorously guided in accordance with established physical principles. To further enhance prediction accuracy and generalisation, a transfer learning framework is integrated into PINN, utilising pre-trained datasets from AM and fine-tuning the model using high-accuracy datasets derived from FEA. Additionally, to optimise the physical information-related hyperparameters that impact model accuracy, functional analysis of variance is employed to quantitatively assess their importance and determine the optimal hyperparameter values. Experimental results show that, with training sample sizes representing only 5% of the FEA data, TL-PINN achieves significant improvements over DNN, including a 74.25% reduction in (1 − R2), a 49.51% reduction in RMSE, and a 50.46% reduction in MAE. These findings demonstrate that TL-PINN delivers superior accuracy while utilising substantially fewer FEA datasets.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of the Electromagnetic Field Model on the Calculated No-Load Magnetic Field of Tubular Hydro Generators 电磁场模型对管式水轮发电机空载磁场计算的影响

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-06-05 DOI: 10.1049/elp2.70052

Qi-Rui Yin, Zhi-Ting Zhou, Zhen-Nan Fan, Yong Yang, Jing-Can Li

{"title":"Influence of the Electromagnetic Field Model on the Calculated No-Load Magnetic Field of Tubular Hydro Generators","authors":"Qi-Rui Yin, Zhi-Ting Zhou, Zhen-Nan Fan, Yong Yang, Jing-Can Li","doi":"10.1049/elp2.70052","DOIUrl":"https://doi.org/10.1049/elp2.70052","url":null,"abstract":"The selected electromagnetic field model of a hydro generator directly affects the calculation of the no-load magnetic field, which in turn affects the grid-connected power quality of the hydrogenerator and the power transmission safety. Tubular hydro generators have a horizontal structure with less internal space than the conventional vertical hydro generator, which results in a particularly complex and strong internal magnetic field distribution. This study investigated the influence of the selected electromagnetic field model on the calculation of the no-load magnetic field of a tubular hydro generator. Straight and skewed stator slots were considered for the structure of the hydro generator. Three models were considered: the transient motion electromagnetic field-circuit coupling model, the transient motion electromagnetic field model, and the static electromagnetic field model. The calculation accuracy and computational efficiency of the three models were evaluated by comparison to measured data. The results were used to make reasonable suggestions for the selection of a suitable electromagnetic field model in different scenarios. The findings are expected to support the electromagnetic field analysis and design of hydro generators.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144220191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novel Hybrid Rare-Earth and Ferrite Magnet Asymmetric V-Shape and U-Shape IPMSMs Accounting for Demagnetisation Withstand Capability 新型混合稀土和铁氧体不对称v形和u形电磁永磁同步电动机的消磁承受能力

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-06-05 DOI: 10.1049/elp2.70054

Seyedmilad Kazemisangdehi, Zi Qiang Zhu, Liang Chen, Lei Yang, Yanjian Zhou

{"title":"Novel Hybrid Rare-Earth and Ferrite Magnet Asymmetric V-Shape and U-Shape IPMSMs Accounting for Demagnetisation Withstand Capability","authors":"Seyedmilad Kazemisangdehi, Zi Qiang Zhu, Liang Chen, Lei Yang, Yanjian Zhou","doi":"10.1049/elp2.70054","DOIUrl":"https://doi.org/10.1049/elp2.70054","url":null,"abstract":"This paper presents two novel hybrid rare-earth and ferrite permanent magnet (HPM) asymmetric V-shape and U-shape interior PM synchronous machines (IPMSMs) with high ferrite PM (FEPM) torque contribution accounting for the enhanced demagnetisation withstand capability of FEPM at both open circuit and overload conditions. The proposed topologies are designed and compared with a rare-earth PM (REPM)-based symmetrical V-shape baseline in terms of electromagnetic performances, mechanical strength, demagnetisation withstand capability, and PMs cost. All machines are optimised for the same torque with the minimum volume of high-cost REPM at the same specification and size as a commercialised electric vehicle (EV) IPMSM. It is shown that the synergies of magnetic field shifting effect and HPM utilisation have improved the torque per REPM usage in both proposed machines. However, the magnetic field shifting of the proposed HPM asymmetric U-shape IPMSM is twice of that in the V-shape IPMSM counterpart along with a slightly better FEPM demagnetisation withstand capability. Meanwhile, the results show that the proposed HPM asymmetric V-shape IPMSM would be cheaper than the U-shape counterpart as the former and latter topologies require ∼31% and ∼23.5% less REPM volume than the baseline, respectively. Finally, two small laboratory size prototypes are made and tested to verify the finite element analyses.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70054","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144220190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sub-Synchronous Oscillation Suppression Strategy for DFIG Based on Morris-EFAST Global Sensitivity Analysis and Multi-Parameter Co-Optimisation 基于Morris-EFAST全局灵敏度分析和多参数协同优化的DFIG次同步振荡抑制策略

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-05-29 DOI: 10.1049/elp2.70051

Gaojun Meng, Junyi Wang, Lei Huang, Yangfei Zhang, Linlin Yu, Haitao Liu

{"title":"Sub-Synchronous Oscillation Suppression Strategy for DFIG Based on Morris-EFAST Global Sensitivity Analysis and Multi-Parameter Co-Optimisation","authors":"Gaojun Meng, Junyi Wang, Lei Huang, Yangfei Zhang, Linlin Yu, Haitao Liu","doi":"10.1049/elp2.70051","DOIUrl":"https://doi.org/10.1049/elp2.70051","url":null,"abstract":"With the growing share of wind power generation in the global energy structure, sub-synchronous oscillations (SSOs) triggered by the integration of wind power into the grid, as a potential dynamic instability phenomenon, have a non-negligible impact on the performance and safety of the power system and even lead to serious operational risks. Starting from the operation mechanism of the doubly-fed induction generator (DFIG) and in combination with the control of the rotor-side converter (RSC), an equivalent impedance model of the DFIG is constructed. Employing the Morris method and the extended Fourier amplitude sensitivity test (EFAST) method, a comprehensive global sensitivity analysis of the system impedance is conducted, progressing from qualitative to quantitative analysis. High-sensitivity parameters are identified, and the system dynamic interval is partitioned through the joint adjustment among these parameters. Subsequently, a cooperative optimisation method for high-sensitivity parameters is proposed to optimise the parameter set within the instability region to effectively suppress SSO. Finally, the simulation model of the DFIG grid-connected system with series compensation is established, and the feasibility of the optimisation method is verified using the Middlebrook criterion. The results demonstrate that the optimisation method exhibits strong adaptability under different operating conditions, effectively mitigating the risk of SSOs and ensuring stable operation of the wind power system.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic dq Model of PMSM Using FE-Based LUTs 基于fe的LUTs的永磁同步电机动态dq模型

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-05-27 DOI: 10.1049/elp2.70037

Christian Kukura, Judith Apsley, Siniša Djurovic

引用次数: 0