Iet Electric Power Applications最新文献

{"title":"Analysis and calculation of electromagnetic force of stator winding and damping bar during dynamic loading of pumped storage generator/motor","authors":"Dajun Tao,&nbsp;Xu Dai,&nbsp;Baojun Ge,&nbsp;Guifen Li,&nbsp;Gang Hu","doi":"10.1049/elp2.12501","DOIUrl":"https://doi.org/10.1049/elp2.12501","url":null,"abstract":"<p>Frequently and rapidly dynamic conversion is one of the main differences between pumped-storage motor and general hydro-generator. In the process of changing operating conditions, in order to achieve fast dynamic conversion, the loading rate requirement of pumped storage motors is often much higher than that of conventional generators, which brings great impact on the key structural components of generators, it affects the safe operating life of motors directly. To solve the impact of dynamic loading rate on key structural components of pumped storage motors, for a pumped storage motor as an example, investigating different loading rates during the dynamic conversion of two main operating conditions on pumped storage motors (power generation and electric power) of pumped storage motors are investigated. Calculating accurately the distribution laws of electromagnetic forces of key structural components which contains stator tooth walls and damping strips during dynamic loading. The results show that the different loading rates will affect the force distribution of the key position directly, under the condition of generator state and motor state, the distribution of force on stator winding and damping bar present different laws, it will provide reference for the determination of multi-state conversion loading rate of pumped storage motor and the improvement of pumped storage motor structure scheme.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12501","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143397217","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}

{"title":"Mathematical sizing and design analysis of permanent magnet vernier machine for contra-rotating wind power applications","authors":"Mehroz Fatima,&nbsp;Faisal Khan,&nbsp;Wasiq Ullah,&nbsp;Udochukwu Bola Akuru","doi":"10.1049/elp2.12531","DOIUrl":"https://doi.org/10.1049/elp2.12531","url":null,"abstract":"<p>Over the years, wind energy technology has vividly made progress, as it is economical and cleaner against fossil-fuel alternatives. With the rapid upsurge in turbine ratings up to the MW-power generation level, an unceasing effort is crucial to increase the torque/power density and power factor of the wind-powered machines. Amongst wind-powered machines, the permanent magnet vernier machine (PMVM) is renowned for its high torque density. This paper discusses the detailed design flow of a novel contra-rotating PMVM including sizing equation, geometric relationships, and FEA-based electromagnetic performance analysis compared to the conventional PMVM. The proposed contra-rotating PMVM is analysed with two different winding configurations that is, first with crossed-toroidal and later with concentrated winding configuration, and a comprehensive comparative analysis is made between proposed and conventional PMVM topologies. The contra-rotation of rotors provides more torque/power than the co-rotation within the given machine's size. This comparative analysis provides noteworthy insights into the superior performance of the proposed contra-rotating PMVM topologies regarding torque/power, power factor, and efficiency. A superior torque/power of value 538.23 Nm/1.6 kW is achieved in the case of the design with crossed-toroidal winding configuration with an efficiency of 97.82% whereas, a high-power factor of 0.98 with an efficiency of 91.36% is achieved in the case of the design with concentrated winding configuration.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12531","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396857","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}

{"title":"Inversion of the temperature field in oil-immersed reactors using optimal measurement points selected by random forest","authors":"Jiayi Guo,&nbsp;Kaizhuang Zhu,&nbsp;Xiaopeng Li,&nbsp;Jingyun Zhao,&nbsp;Yunpeng Liu,&nbsp;Fangcheng Lv","doi":"10.1049/elp2.12532","DOIUrl":"https://doi.org/10.1049/elp2.12532","url":null,"abstract":"<p>To address the subjective issue of selecting measurement points based on mainstream line methods for hotspot temperature inversion in oil-immersed power equipment, this paper demonstrates an oil-immersed reactor temperature field inversion method based on random forest (RF) measurement point optimisation. Firstly, a temperature field calculation method for a 22-kV oil-immersed reactor is proposed. In combination with Latin hypercube sampling, 50 sets of temperature field data are calculated. Based on these samples, the selection of measurement points based on RF feature importance and the training of the genetic algorithm-optimised back propagation (GA-BP) inversion model are undertaken. Finally, the optimal combination of external tank wall measurement points is determined based on comprehensive error indicators, achieving accurate inversion of internal hotspot temperatures in the reactor (with an error of 0.243 °C). The inversion errors are reduced by 2.91 °C and 1.47 °C on average per group compared to existing methods, evincing the superiority of the proposed model.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12532","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143397003","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}

{"title":"Analytical modelling and analysis of magnet eddy current loss in magnet-surrounded permanent magnet synchronous machine caused by stator slot effect","authors":"Yuhang Long,&nbsp;Zhanfeng Song","doi":"10.1049/elp2.12527","DOIUrl":"https://doi.org/10.1049/elp2.12527","url":null,"abstract":"<p>To improve the machine torque density, this paper proposes a magnet-surrounded permanent magnet synchronous machine (MSPMSM). As the critical material of MSPMSM, the permanent magnet (PM) will produce significant eddy current loss under the action of eddy current electromotive force. Therefore, it is essential to investigate the change in PM eddy current loss and methods to suppress it. To solve the above problems, a simplified analytical calculation model for the eddy current loss of PMs caused by stator slotting is proposed. The distribution law of eddy current loss of PMs caused by stator slotting is studied. The concept of influence depth is proposed to solve the problem of unclear correspondence between the groove depth on the PM surface and the eddy current loss of PMs. The calculation results of the influence depth are used to guide the single-side partial grooving method to reduce the eddy current loss of PMs. In addition, a comparative analysis is conducted on the anti-demagnetisation ability of PMs before and after MSPMSM optimisation. Finally, the experiment verifies the correctness of the analytical calculation and the high torque density of the MSPMSM.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12527","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143397004","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}

{"title":"Genetic algorithm-based approach for torque control and increased efficiency across an optimised speed range in switched reluctance drives","authors":"Euan MacRae,&nbsp;Ali Abdel-Aziz,&nbsp;Khaled Ahmed,&nbsp;Richard Pollock,&nbsp;Barry W. Williams","doi":"10.1049/elp2.12526","DOIUrl":"https://doi.org/10.1049/elp2.12526","url":null,"abstract":"<p>This paper presents a novel genetic algorithm (GA) design for current profiling in switched reluctance machines that eliminates torque ripple (TR) while inherently guaranteeing minimal RMS currents across the machines speed range. Minimising RMS current provides an increase to machine efficiency and the elimination of TR is required for potential SRM applications such as traction vehicles. This paper proposes a novel method for intentional greater-than-two-phase overlap in the algorithm design. This allows any SRM configuration capable of three or more phase conduction to utilise its full speed range with zero torque ripple, in the case where it is limited using two-phase torque sharing. An optimal set of current profiles is created using the algorithm across the full speed range of an exemplary 8/6 SRM and these are analysed. A current profiling-based control scheme using these results is then proposed and simulated for the 8/6 SRM. This is then compared to classical and recently published SRM control methods to highlight the merits of the overall GA design and its resultant control scheme.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 12","pages":"1818-1832"},"PeriodicalIF":1.5,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12526","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252488","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}

{"title":"Fault diagnosis of power transformers based on dissolved gas analysis and improved LightGBM hybrid integrated model with dual-branch structure","authors":"Xuebin Lv,&nbsp;Fuzheng Liu,&nbsp;Mingshun Jiang,&nbsp;Faye Zhang,&nbsp;Lei Jia","doi":"10.1049/elp2.12528","DOIUrl":"https://doi.org/10.1049/elp2.12528","url":null,"abstract":"<p>Aiming at the fault diagnosis problems of imbalanced data and insufficient mapping of characteristic information in fault samples collected by transformers at present, which lead to low accuracy and large diagnostic deviation in actual applications, a power transformer fault diagnosis method based on dissolved gas analysis and an improved LightGBM hybrid integrated model with a dual-branch structure (DIL-DS) is proposed. Firstly, multi-characteristic dissolved gas ratio analysis is used to construct multi-dimensional supplementary feature vectors, which enrich the characterisation features of transformers and facilitate efficient diagnosis of classification models. Secondly, a dual-branch structure combining focal-gradient harmonic loss and cross-entropy loss is introduced to improve the attention and recognition ability of the model to a few categories in the dataset and alleviate the influence of data imbalance on the diagnostic results. Then, an improved grey wolf optimisation (GWO) is designed to improve LightGBM and realise the iterative optimisation of hyperparameters. At the same time, the Jacobian regularisation method is introduced to denoise LightGBM to solve the problem that the model is sensitive to noise. Finally, the LightGBM hybrid integrated model is developed to ensure the accuracy and stability of model diagnosis under the changeable and imbalanced dataset. Experiments show that the proposed DIL-DS can effectively solve the limitation of class imbalance, improve the overall fault diagnosis performance, and is suitable for transformer fault identification.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 12","pages":"2008-2020"},"PeriodicalIF":1.5,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12528","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252534","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}

{"title":"Hybrid mechanism-data-driven iron loss modelling for permanent magnet synchronous motors considering multiphysics coupling effects","authors":"Lin Liu,&nbsp;Wenliang Yin,&nbsp;Youguang Guo","doi":"10.1049/elp2.12530","DOIUrl":"https://doi.org/10.1049/elp2.12530","url":null,"abstract":"<p>The precise calculation of iron losses in permanent magnet synchronous motors (PMSMs) remains challenging due to the interplay between various disciplines such as electromagnetism, magnetism, and thermal/mechanical dynamics. Purely mechanistic models require detailed theoretical knowledge and exact parameters, often struggling to accurately describe complex systems, while purely data-driven methods lack interpretability, which are susceptible to data noise and outliers in feature extraction and complicated pattern recognition. Consequently, this paper aims to present a hybrid mechanism-data-driven model for accurately estimating the iron loss for PMSMs, considering the multiphysics coupling effects. Specifically, based on the well-defined physical principles, an advanced iron loss analytical model that simultaneously considers mechanical stress, temperature rise, harmonics, load currents, and changing frequency is developed and then utilised to calculate numerous loss data under different operating conditions, providing a certain level of stability and reliability for prediction accuracy. Subsequently, a convolutional neural network (CNN) algorithm is employed to perform deep learning to extract features and patterns from the data. By defining a suitable loss function, the pre-trained model was fine-tuned and optimised using a small amount of actual data. To validate its superiority, extensive numerical and experimental analyses are conducted on the prototype. The results demonstrate that the iron losses computed using this hybrid model overcome the limitations of singular methods by effectively leveraging both theoretical knowledge and real-world data, thus accurately accommodating various application scenarios. This integrated approach enhances the accuracy, stability, and interpretability of the model, laying a solid foundation for more specialised applications in the future.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 12","pages":"1833-1843"},"PeriodicalIF":1.5,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12530","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252165","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}

{"title":"Computationally efficient data-driven model predictive control for modular multilevel converters","authors":"Muneeb Masood Raja,&nbsp;Haoran Wang,&nbsp;Muhammad Haseeb Arshad,&nbsp;Gregory J. Kish,&nbsp;Qing Zhao","doi":"10.1049/elp2.12523","DOIUrl":"https://doi.org/10.1049/elp2.12523","url":null,"abstract":"<p>The application of model predictive control (MPC) for the control of modular multilevel converters (MMCs) is widely explored because it offers flexibility in integrating multiobjective control and delivers superior dynamic response. Nonetheless, the increase in computational complexity due to the rise in the number of submodules (SMs) is one of the major drawbacks of this technique. This paper presents a finite control set model predictive control (FCS-MPC) that significantly reduces the computational complexity by employing sparse identification of non-linear systems (SINDy) to obtain a simplified linear model for the MMC. The SINDy model reduces the complexity of performing the prediction step by integrating input terms into the dynamics of load current and circulating current. This simplifies the implementation compared to the conventional FCS-MPC approaches by eliminating the need to evaluate the voltage dynamics. The computational burden is further reduced while maintaining <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>2</mn>\u0000 <mi>N</mi>\u0000 <mo>+</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 <annotation> $2N+1$</annotation>\u0000 </semantics></math> voltage levels at the output by restricting the number of combinations for the inserted SMs to only <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <mfrac>\u0000 <mi>N</mi>\u0000 <mn>3</mn>\u0000 </mfrac>\u0000 <mo>+</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 </mfenced>\u0000 </mrow>\u0000 <annotation> $left(frac{N}{3}+1right)$</annotation>\u0000 </semantics></math> instead of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mrow>\u0000 <mo>(</mo>\u0000 <mrow>\u0000 <mi>N</mi>\u0000 <mo>+</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 <mo>)</mo>\u0000 </mrow>\u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> ${(N+1)}^{2}$</annotation>\u0000 </semantics></math>. A detailed comparison between the proposed technique and the existing strategies demonstrates that the proposed technique offers a more computationally efficient solution for implementing FCS-MPC on MMCs, while improving the circulating current suppression due to more accurate predictions. Simulation and experimental results are presented to validate the performance of the proposed approach.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 12","pages":"1844-1859"},"PeriodicalIF":1.5,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12523","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248839","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}

{"title":"Fault diagnosis of inter-turn short circuits in PMSM based on deep regulated neural network","authors":"Ahmed Mesai Belgacem,&nbsp;Mounir Hadef,&nbsp;Enas Ali,&nbsp;Salah K. Elsayed,&nbsp;Prabhu Paramasivam,&nbsp;Sherif S. M. Ghoneim","doi":"10.1049/elp2.12525","DOIUrl":"https://doi.org/10.1049/elp2.12525","url":null,"abstract":"<p>Permanent Magnet Synchronous Machine (PMSM) is widely utilised in numerous industrial applications due to its precise control capabilities. However, these motors frequently encounter operational faults, potentially leading to severe safety and performance issues. Consequently, effective health monitoring techniques for early fault detection are essential to maintain optimal performance and extend the lifespan of these systems. This study presents a qualification-based methodology for diagnosing faults in three-phase PMSMs through vibration–current data fusion analysis. The stator faults, specifically inter-turn short circuits (ITSC) induced via bypassing resistances, were investigated using experimental data from a custom-built test rig. The collected current and vibration signals were transformed into statistical features. Various operating scenarios were diagnosed utilising a deep regulated neural network (RegNet), an improved convolutional neural network based on an enhanced residual architecture. The proposed approach was assessed through various metrics including training efficiency, precision, recall, f1-score, and accuracy, and compared against several neural network methods. The findings reveal that the proposed RegNet model achieves perfect accuracy, attaining 100%. This research highlights the efficacy of data fusion analysis and deep learning in fault diagnosis, facilitating proactive maintenance strategies and improving the reliability of PMSMs in diverse industrial applications and renewable energy systems.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 12","pages":"1991-2007"},"PeriodicalIF":1.5,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12525","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248398","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}

{"title":"Analysis of the influence of configuration parameters on the electric field distribution of the main insulation structure of valve-side winding of converter transformer considering electro-thermal coupling","authors":"Lijun Yang,&nbsp;Zhidong Cheng,&nbsp;Li Cheng,&nbsp;Ruijin Liao","doi":"10.1049/elp2.12511","DOIUrl":"https://doi.org/10.1049/elp2.12511","url":null,"abstract":"<p>The variation of configuration parameters in the insulation structure of transformers significantly impacts the distribution of electric fields. Current research on electric field distribution calculations often overlooks the influence of electric field intensity and temperature on this distribution. However, considering that the direct current conductivity of oil-paper materials is easily affected by both electric field intensity and temperature, any changes in their conductivity will inevitably affect the electric field distribution. Therefore, this paper incorporates the influence of electric field intensity and temperature on the calculation process of the electric field distribution in the main insulation structure of the valve-side winding. Additionally, it calculates the distribution of multi-fields for a wide range of structural configuration parameters. Consequently, the influence law of insulation structure configuration parameters on the electric field distribution of the main insulation structure of valve-side winding for converter transformer when considering electro-thermal coupling is obtained. This finding can serve as a crucial reference for designing and optimising converter transformers.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 12","pages":"1948-1964"},"PeriodicalIF":1.5,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12511","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248320","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}