Iet Electric Power Applications最新文献

As one of the key main equipment of the power system, the transformer directly affects the safe and reliable operation of the system. In the process of transformer reclosing, the internal electromagnetic environment is obviously different from that of the initial short circuit. The nonperiodic component of the short-circuit current exceeds that of the initial short circuit, increasing the electromagnetic force on the winding and severely threatening its dynamic stability. In order to study the influence of reclosing short-circuit impact on the radial dynamic stability of transformer winding, this paper takes SFSZ9-50000/110 transformer as an example. Firstly, the numerical model of short-circuit current of infinite power system is constructed by Matlab/Simulink, and the short-circuit current of initial short-circuit and reclosing process is calculated. The increase value of the reclosing short-circuit current compared with the initial short-circuit current is calculated, and the accuracy of the short-circuit current numerical calculation model is verified by comparison with the theoretical value. The results show that for the power transformer studied in this paper, the three-phase short-circuit current of the transformer under the reclosing short-circuit condition increases by about 6% compared with the initial short-circuit current. Then, based on the short-circuit current, the finite element method is used to analyse the leakage magnetic field of the transformer winding by using ANSYS Maxwell and the variation law of the electromagnetic force under the reclosing short-circuit impact. Finally, various kinds of radial stress of transformer winding under initial short-circuit and reclosing short-circuit conditions are compared and checked. The results show that under the reclosing condition, the average circumferential stress and inner winding radial bending stress of the transformer increase by about 12%, which leads to the decrease of the dynamic stability margin of the transformer. The research results have reference significance for optimising the dynamic stability verification method of transformer winding under reclosing short-circuit impact.

The zeroth-order vibration and noise are worthy of attention in integer slot motor vibration when it is applied to underwater vehicles. In this article, the source of the zeroth-order vibration and the deep relationship between the rotor modulation and the radial force are demonstrated for the wound field synchronous machines (WFSM). First, based on the Maxwell tensor method and the modulation effect of the stator and rotor teeth, the generation mechanism of zeroth-order vibration on the WFSM is clarified. Then, taking an integer slot distributed salient pole WFSM as an example, based on the modulation effect of the rotor teeth on the radial force density, the weakening mechanism of the zeroth-order vibration is demonstrated in detail. The rotor structural parameters of the distributed salient pole WFSM are adjusted to weaken zeroth-order vibration. In the finite element model, the radial force influence components of the zeroth-order vibration, key electromagnetic performance, and vibration spectrum of the machine before and after improvement are compared. Finally, the vibration experiment on the prototype is carried out to verify the correctness and effectiveness of the analysis and improvement.

This study proposes a hybrid feature selection method (HBPSWOA) based on binary particle swarm optimisation and whale optimisation algorithm for bearing fault diagnosis. To validate the proposed method, a fault diagnosis framework integrating feature extraction, feature selection and classification is constructed. In the feature extraction stage, variational mode decomposition and fast Fourier transform are combined to capture both time-domain and frequency-domain features. In the feature selection stage, HBPSWOA integrates the local search efficiency of BPSO with the global exploration ability of WOA. This integration is further enhanced by introducing a Hamming distance-based position update mechanism and a roulette wheel selection strategy, improving solution diversity and robustness. Selected features are evaluated using k-nearest neighbours and support vector machine. The method is validated across three datasets, and its robustness is demonstrated through experiments with Gaussian white noise of varying intensities. Compared to four traditional feature selection methods (BPSO, BWOA, GA and BGWO), the proposed method achieves higher classification accuracy while selecting fewer and more informative features. This optimisation not only enhances classification accuracy but also improves computational efficiency, including under varying noise conditions. The highest accuracy of 99.51% was achieved on the CWRU benchmark dataset using an SVM classifier. Future research directions include exploring its scalability on larger datasets and leveraging deep learning classifiers to fully exploit the potential of the selected features, further enhancing diagnostic performance.

As the core hub equipment of offshore wind power low-frequency transmission systems, low-frequency transformers generate complex harmonic disturbances during internal faults, severely compromising the reliability of traditional current differential protection. To address this engineering challenge, this paper innovatively proposes a transformer fast main protection method based on excitation inductance parameter identification. Rooted in the unique application scenarios of offshore wind power, the research focuses on overcoming the limitations of existing ratio-restraint differential protection constrained by magnetising inrush current identification. Specifically, the distinctive harmonic characteristics exhibited during low-frequency transformer faults can invalidate second-harmonic restraint principles. A novel identification model based on the dynamic characteristics of instantaneous excitation inductance is developed, which breaks through the limitations of traditional harmonic analysis methods and achieves precise discrimination between fault currents and magnetising inrush currents using single-terminal current-voltage data. Simulation experiments demonstrate that this method can reduce protection operation time to less than 10 ms, particularly suitable for special offshore platform conditions characterised by space constraints and maintenance difficulties. The proposed approach provides critical technical support for enhancing low-frequency transformer protection in offshore wind farm grid-connected low-frequency transmission systems, demonstrating significant engineering application value.

Relative to the traditional pumped storage machines, the variable speed pumped storage machine (VSPSM) has strong frequency and voltage regulation capabilities by the AC excitation. However, the enhancement of the regulation capability also leads to the increment of the temperature rise. For the purpose of investigating the temperature variation in the end zone of the VSPSM, a 336-MVA VSPSM is chosen as the research reference in this article. The electromagnetic-fluid-thermal coupled heat transfer calculation model in the end zone of the VSPSM is constructed. The flux density and loss distribution in the end zone of the VSPSM are calculated under different power factors and slips. The losses of the stator end parts are less influenced by the slip compared to the rotor end parts, which are more affected. The variations of temperature rise in the tooth plate, end core, clamping plate and the rotor retaining ring are revealed along with the power factor and slip. It is found that the stator tooth plate is the end part with the peak temperature. This research is able to lay a theoretical basis for optimising and designing the end structure of the VSPSM.

A position sensorless control method for interior permanent magnet synchronous motors (IPMSMs) has been developed to reduce cost and improve reliability. The performance of position estimation largely depends on the motor parameters. Inductance varies due to magnetic saturation during operation. Therefore, model-based position estimation deteriorates if the inductance variation is not taken into account. Traditional position estimation methods use an ideal IPMSM model that assumes the d-axis and q-axis are completely magnetically decoupled, that is, only the d-axis and q-axis self-inductances are considered. However, in reality, a cross-coupling effect exists in actual IPMSMs, resulting in mutual inductance between the d-axis and q-axis. This mutual inductance also degrades position estimation performance, particularly under heavy load conditions. Thus, it is important to identify the inductance while considering both magnetic saturation during operation and cross-coupling, in order to achieve accurate position estimation. In this paper, we propose a novel flux observer that accounts for the cross-coupling inductance and present an adaptive approach. Using the adaptive scheme, time-varying parameter identification can be effectively addressed. The effectiveness of the proposed method is verified through experimental results.

The intermittent and variable nature of external wind speeds often causes traditional wind power systems to misalign with electricity demand resulting in significant wind energy waste and reduced utilisation efficiency. Additionally, the growing global population and economic development have increased demands for residential heating and industrial thermal energy. In order to improve the controllability of wind energy conversion and simultaneously meet the heat demand, this study proposes a novel dual-stator generator capable of electrical-thermal flexible output, which offers significant advantages in terms of adaptable electrothermal energy output and enhanced operational efficiency. Initially, the topology and magnetic circuit model of the generator are systematically established, with its parameters meticulously designed to accommodate the simultaneous generation of both electrical and thermal energy outputs. Subsequently, in order to meet the standards of the power grid, a comprehensive multi-objective optimisation methodology is implemented to enhance the operational performance of the generator, achieving remarkable improvements: a 63.31% reduction in harmonic content, a 20.50% increase in heating capacity, a 44.35% reduction in torque pulsation, a 0.13% improvement in conversion efficiency, and a 13.60% enhancement in power density. Through the significant reduction of harmonic content and torque pulsation, the proposed design significantly enhances grid compatibility while minimising mechanical vibrations, thereby ensuring stable power generation even under highly fluctuating wind speed conditions. Finally, through extensive testing under various operational conditions, the generator demonstrates a remarkable 2:1 adjustable ratio of electrical-to-thermal output across variable wind speeds, achieving a peak efficiency of 97.41%.

Permanent magnet motors (PMMs) are a good choice for many applications due to their merits. These motors include synchronous motors (SMs) and flux modulation motors (FMMs). Their principles of operation depend on the air-gap permeance harmonics. Permeance harmonics are one of the main factors influencing the performance characteristics of PMMs, including torque, back-electromotive force (EMF), power factor, flux-linkage, phase inductance, and flux-weakening capability. This paper investigates the effect of air-gap permeance harmonics on PMM performance. For this purpose, the winding function theory (WFT) and the Fourier series are used and various PMM structures having different effective permeance harmonics are presented. Since it is not possible to analyse all these structures, four structures of conventional PMMs are selected as representatives of all the structures. In this paper, the improved analytical modelling of WFT is used, in which the turn function is modified to include the saturation and slot effects. Also, it is possible to calculate the leakage inductance between two stator teeth. Ansys Maxwell software is applied to verify the analytical modelling. Finally, two designs of FMM with different air-gap permeances are analysed and compared. The superior structure of this FMM is fabricated and tested to confirm the simulation results.

Dual three-phase induction motor drives are gaining attention in applications where reliability is a critical concern, such as automotive. Although the dual-stator winding reduces the impact of stator phase failures, these motors remain susceptible to broken rotor bar (BRB) faults. This paper presents a comprehensive methodology for their detection. The proposed approach encompasses all the key components of the detection algorithm, from motor modelling—used to generate a virtual dataset for training—to the selection of the most suitable variables for machine learning classification. Technical challenges, practical implementation insights, and experimental validation on real motors are discussed to provide a thorough understanding of the methodology and best design practices.

The equivalent circuit method is an accurate and versatile tool to estimate the losses and efficiency of induction motors during energy audits. However, determining the circuit parameters of in-service motors usually involves disrupting their operation. A less intrusive option is to estimate the parameters from performance data provided in catalogues and datasheets. Nine parameter estimation methods are assessed in this work according to accuracy and robustness criteria. Three relatively simple methods stand out with good performance on both criteria. Yet, the combination of high accuracy and total absence of failures is not observed in any of the tested methods. Additionally, a conceptual error repeated in four references regarding the use of the Thévenin equivalent is identified and corrected. Finally, a case study of loss estimation in two tested motors shows that good accuracy is achievable as long as the data reported by the manufacturer matches the real motor characteristics. A mismatch between reported and real characteristics may be detected by comparing the measured input power with its calculated value for the same slip.