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Volume 51,Issue 3,2024 Table of Contents
2024, 51(3):1-9.
DOI: 10.12177/emca.2024.001
Abstract:
In response to the demand for grid harmonic impedance measurement in the context of new power systems, a novel grid harmonic impedance measurement method based on photovoltaic inverter is proposed. The proposed method does not disturb the power grid, does not require the installation of additional measurement equipment, and can also control grid harmonics during the impedance measurement. The method controls the photovoltaic inverter to function as a normal power generator under fundamental waves and controls it to be equivalent to a virtual resistor under harmonics. By changing the equivalent virtual harmonic resistance value of the inverter, the amplitude of the harmonic voltage at the grid connection point is measured,and combined with the least squares method to estimate the harmonic impedance amplitude of the system. The impedance measurement experiment is conducted using the hardware-in-loop real-time simulation experimental platform, and the measurement results are consistent with the set values. The measurement accuracy of the 5th harmonic impedance of the system reaches 99%, and the measurement accuracy of the 7th harmonic impedance reaches 97%, which verifies that the proposed method can not only measure the amplitude of the system’s multiple harmonic impedance, but also ensure high measurement accuracy.
In response to the demand for grid harmonic impedance measurement in the context of new power systems, a novel grid harmonic impedance measurement method based on photovoltaic inverter is proposed. The proposed method does not disturb the power grid, does not require the installation of additional measurement equipment, and can also control grid harmonics during the impedance measurement. The method controls the photovoltaic inverter to function as a normal power generator under fundamental waves and controls it to be equivalent to a virtual resistor under harmonics. By changing the equivalent virtual harmonic resistance value of the inverter, the amplitude of the harmonic voltage at the grid connection point is measured,and combined with the least squares method to estimate the harmonic impedance amplitude of the system. The impedance measurement experiment is conducted using the hardware-in-loop real-time simulation experimental platform, and the measurement results are consistent with the set values. The measurement accuracy of the 5th harmonic impedance of the system reaches 99%, and the measurement accuracy of the 7th harmonic impedance reaches 97%, which verifies that the proposed method can not only measure the amplitude of the system’s multiple harmonic impedance, but also ensure high measurement accuracy.
2024, 51(3):10-20.
DOI: 10.12177/emca.2024.005
Abstract:
Aiming at the problem of abnormal or faulty operation mechanism of gas insulated switchgear (GIS), which leads to faults or inability to trip when operating its switches, an abnormal classification model of the operation mechanism of GIS equipment based on the Mel-frequency cepstrum coefficient (MFCC) and random forest is proposed. Firstly, according to the preprocessing of the collected voiceprint signal, MFCC is used to extract the features of the voiceprint signal. Then, a random forest is constructed to identify the voiceprint feature, and the classification results of GIS action anomalies are obtained. Finally, taking a 110 kV GIS equipment as an example, the voiceprint signals of the energy storage mechanism and transmission mechanism of the circuit breaker and the isolating switch are collected when they are abnormal or faulty, and the audio sample library is constructed. The classification model proposed in this paper is compared with a variety of classical models. The results show that MFCC can effectively extract the features of voiceprint signals under different working conditions of GIS actions, and random forest performs best among many classification and recognition models, which can effectively improve the accuracy of abnormal working conditions recognition of GIS actions.
Aiming at the problem of abnormal or faulty operation mechanism of gas insulated switchgear (GIS), which leads to faults or inability to trip when operating its switches, an abnormal classification model of the operation mechanism of GIS equipment based on the Mel-frequency cepstrum coefficient (MFCC) and random forest is proposed. Firstly, according to the preprocessing of the collected voiceprint signal, MFCC is used to extract the features of the voiceprint signal. Then, a random forest is constructed to identify the voiceprint feature, and the classification results of GIS action anomalies are obtained. Finally, taking a 110 kV GIS equipment as an example, the voiceprint signals of the energy storage mechanism and transmission mechanism of the circuit breaker and the isolating switch are collected when they are abnormal or faulty, and the audio sample library is constructed. The classification model proposed in this paper is compared with a variety of classical models. The results show that MFCC can effectively extract the features of voiceprint signals under different working conditions of GIS actions, and random forest performs best among many classification and recognition models, which can effectively improve the accuracy of abnormal working conditions recognition of GIS actions.
2024, 51(3):21-29.
DOI: 10.12177/emca.2023.191
Abstract:
The capacity prediction of residential charging stations can provide a reference for its capacity selection and contribute to the carbon peaking and caron neutrality goals. In this regard, a datadriven method for predicting the capacity of residential charging stations is proposed. Firstly, historical capacity data of residential charging stations are collected and preprocessed. Secondly, differentsized time windows are used to slice the data as input features. Finally, a prediction model combining multihead attention mechanism and gated recurrent unit neural network is constructed, and the features are input into the model to achieve accurate prediction of future capacity. The results of the case analysis show that the exponential mean absolute error and exponential root mean square error of the model are 33.19 and 102.14% respectively. Compared to other models, the proposed model significantly improves the prediction accuracy and provides new insights for capacity prediction of residential charging stations.
The capacity prediction of residential charging stations can provide a reference for its capacity selection and contribute to the carbon peaking and caron neutrality goals. In this regard, a datadriven method for predicting the capacity of residential charging stations is proposed. Firstly, historical capacity data of residential charging stations are collected and preprocessed. Secondly, differentsized time windows are used to slice the data as input features. Finally, a prediction model combining multihead attention mechanism and gated recurrent unit neural network is constructed, and the features are input into the model to achieve accurate prediction of future capacity. The results of the case analysis show that the exponential mean absolute error and exponential root mean square error of the model are 33.19 and 102.14% respectively. Compared to other models, the proposed model significantly improves the prediction accuracy and provides new insights for capacity prediction of residential charging stations.
2024, 51(3):30-37.
DOI: 10.12177/emca.2023.194
Abstract:
Bearing faults can cause changes in the air gap of doubly-fed wind turbines, generating unbalanced magnetic pull (UMP). In order to accurately reveal the bearing fault vibration characteristics of doublyfed wind turbines, a study on dynamic modeling of the outer ring fault of the bearing considering the UMP is carried out. Firstly, a bearing outer ring fault model is constructed based on the Hertz contact theory. Then, the air gap magnetic flux density of the generator rotor under normal and bearing fault conditions is derived, and the UMP acting on the generator rotor is obtained. Finally, the Runge-Kutta method is used to solve the model and the vibration response of the bearing fault is obtained. Experimental comparison analysis shows that the proposed dynamic model can effectively reveal the double impact phenomenon of the vibration signal of doubly-fed wind turbines with bearing faults, and the UMP excitation can affect the modulation characteristics of the vibration signal of wind turbine bearings outer ring faults. A new theoretical references is provided for fault diagnosis of wind turbine bearings.
Bearing faults can cause changes in the air gap of doubly-fed wind turbines, generating unbalanced magnetic pull (UMP). In order to accurately reveal the bearing fault vibration characteristics of doublyfed wind turbines, a study on dynamic modeling of the outer ring fault of the bearing considering the UMP is carried out. Firstly, a bearing outer ring fault model is constructed based on the Hertz contact theory. Then, the air gap magnetic flux density of the generator rotor under normal and bearing fault conditions is derived, and the UMP acting on the generator rotor is obtained. Finally, the Runge-Kutta method is used to solve the model and the vibration response of the bearing fault is obtained. Experimental comparison analysis shows that the proposed dynamic model can effectively reveal the double impact phenomenon of the vibration signal of doubly-fed wind turbines with bearing faults, and the UMP excitation can affect the modulation characteristics of the vibration signal of wind turbine bearings outer ring faults. A new theoretical references is provided for fault diagnosis of wind turbine bearings.
2024, 51(3):38-48.
DOI: 10.12177/emca.2023.195
Abstract:
The use of average flux orientation control of multiple permanent magnet synchronous wind turbines and thus the construction of fractional frequency wind power systems, is one of the potential future options for onshore and offshore wind power. Nonetheless, the study of the stability among multiple wind turbines in this mode is rarely covered in the literature. To address this problem, the stability of small disturbances among permanent magnet synchronous wind turbines with average flux orientation control is investigated based on the eigenvalue analysis method. Firstly, based on the topology of the crossover collector system of high-voltage and large-capacity direct-drive permanent magnet synchronous wind turbines, a mathematical model of the wind power system applicable to the analysis of small disturbances stability is established. Secondly, the primary factors affecting system oscillations are determined by identifying the oscillatory modes and analyzing the modal participation factors, and the impact of parameter variations on the oscillatory of the system is examined by plotting the trajectories of the roots. It is concluded that the system oscillations are most affected by the generator inductance, resistance, and direct current capacitance parameters. Finally, the correctness of the findings is verified by time domain simulations.
The use of average flux orientation control of multiple permanent magnet synchronous wind turbines and thus the construction of fractional frequency wind power systems, is one of the potential future options for onshore and offshore wind power. Nonetheless, the study of the stability among multiple wind turbines in this mode is rarely covered in the literature. To address this problem, the stability of small disturbances among permanent magnet synchronous wind turbines with average flux orientation control is investigated based on the eigenvalue analysis method. Firstly, based on the topology of the crossover collector system of high-voltage and large-capacity direct-drive permanent magnet synchronous wind turbines, a mathematical model of the wind power system applicable to the analysis of small disturbances stability is established. Secondly, the primary factors affecting system oscillations are determined by identifying the oscillatory modes and analyzing the modal participation factors, and the impact of parameter variations on the oscillatory of the system is examined by plotting the trajectories of the roots. It is concluded that the system oscillations are most affected by the generator inductance, resistance, and direct current capacitance parameters. Finally, the correctness of the findings is verified by time domain simulations.
2024, 51(3):49-59.
DOI: 10.12177/emca.2023.197
Abstract:
With the increasing installed capacity of offshore wind power in China, coastal areas with developed economy and large power load increasingly rely on and pay attention to the safe operation of offshore wind power. The problem of friendly access to offshore wind farms becomes particularly prominent in the context of declining capacity of conventional thermal units in the system and low system inertia. Especially during typhoons, offshore wind farms may be quickly disconnected from the power grid before reaching the cut-off wind speed, resulting in a large power deficit in the main network, worsening voltage frequency and other adverse effects. In order to solve the problems of large disturbance caused by wind power inherent fluctuation and typhoon, a grid-connected operation control method of offshore wind farm with hybrid electric hydrogen energy storage is proposed. During the normal operation of offshore wind farms, the method effectively smooth out the fluctuation of wind power during the normal operation of offshore wind farms by rationally arranging energy storage and charging/discharging. While during the transit of typhoons, the method alleviates the sudden drop in offshore wind power output and reduces the adverse impact on the grid at the affected end by rational use of hybrid electric hydrogen energy storage. The validity of the proposed method is verified by simulating the real data of an offshore wind farm in Guangdong.
With the increasing installed capacity of offshore wind power in China, coastal areas with developed economy and large power load increasingly rely on and pay attention to the safe operation of offshore wind power. The problem of friendly access to offshore wind farms becomes particularly prominent in the context of declining capacity of conventional thermal units in the system and low system inertia. Especially during typhoons, offshore wind farms may be quickly disconnected from the power grid before reaching the cut-off wind speed, resulting in a large power deficit in the main network, worsening voltage frequency and other adverse effects. In order to solve the problems of large disturbance caused by wind power inherent fluctuation and typhoon, a grid-connected operation control method of offshore wind farm with hybrid electric hydrogen energy storage is proposed. During the normal operation of offshore wind farms, the method effectively smooth out the fluctuation of wind power during the normal operation of offshore wind farms by rationally arranging energy storage and charging/discharging. While during the transit of typhoons, the method alleviates the sudden drop in offshore wind power output and reduces the adverse impact on the grid at the affected end by rational use of hybrid electric hydrogen energy storage. The validity of the proposed method is verified by simulating the real data of an offshore wind farm in Guangdong.
2024, 51(3):60-68.
DOI: 10.12177/emca.2023.190
Abstract:
To address the problem of uneven cathode magnetic field distribution on the target surface during the coating process of existing magnetron sputtering devices, a new type of rotating cathode magnetic field device is designed. The device drives the magnetic field through a rotating mechanism, and the cam mechanism is used to make the magnetic field to move up and down in a straight line. Firstly, a threedimensional model of the device is drawn using 3D software. Secondly, a finite element analysis of the magnetic induction intensity of the cathode magnetic field is performed. Finally, the magnetic field is optimized by adjusting the height of the yoke, the length of the extended arm, and the distance between the yoke and the target material, and the numerical simulation curves before and after optimization are compared and analyzed. The results show that the uniformity of the magnetic induction intensity curve of the cathode magnetic field is improved from 21% to 6% after optimization, which effectively improves the uniformity of the magnetic field on the target surface, and beneficial to ensure stable operation of magnetron sputtering.
To address the problem of uneven cathode magnetic field distribution on the target surface during the coating process of existing magnetron sputtering devices, a new type of rotating cathode magnetic field device is designed. The device drives the magnetic field through a rotating mechanism, and the cam mechanism is used to make the magnetic field to move up and down in a straight line. Firstly, a threedimensional model of the device is drawn using 3D software. Secondly, a finite element analysis of the magnetic induction intensity of the cathode magnetic field is performed. Finally, the magnetic field is optimized by adjusting the height of the yoke, the length of the extended arm, and the distance between the yoke and the target material, and the numerical simulation curves before and after optimization are compared and analyzed. The results show that the uniformity of the magnetic induction intensity curve of the cathode magnetic field is improved from 21% to 6% after optimization, which effectively improves the uniformity of the magnetic field on the target surface, and beneficial to ensure stable operation of magnetron sputtering.
2024, 51(3):69-78.
DOI: 10.12177/emca.2023.193
Abstract:
In view of the impact of harmonic torque on traction motors driven by frequency converters, the mechanism of harmonic torque on the copper squirrel cage rotor structure is analyzed. A combination of experimental and simulation methods is used in order to identify the characteristics at the rotor end of the squirrel cage. Firstly, modal analysis is conducted to obtain the modal parameters of the squirrel cage rotor. Then, a finite element model of the squirrel cage rotor based on the modal tests is established, and its static strength and harmonic dynamic response under 12 times of frequency-induced electromagnetic excitation are simulated and analyzed. Finally, based on the guide bar vibration test platform, the torsional vibration characteristics of the squirrel cage rotor end are investigated and the load amplification effect is verified, which provides certain theoretical support for improving the structural reliability of the copper squirrel cage rotor end.
In view of the impact of harmonic torque on traction motors driven by frequency converters, the mechanism of harmonic torque on the copper squirrel cage rotor structure is analyzed. A combination of experimental and simulation methods is used in order to identify the characteristics at the rotor end of the squirrel cage. Firstly, modal analysis is conducted to obtain the modal parameters of the squirrel cage rotor. Then, a finite element model of the squirrel cage rotor based on the modal tests is established, and its static strength and harmonic dynamic response under 12 times of frequency-induced electromagnetic excitation are simulated and analyzed. Finally, based on the guide bar vibration test platform, the torsional vibration characteristics of the squirrel cage rotor end are investigated and the load amplification effect is verified, which provides certain theoretical support for improving the structural reliability of the copper squirrel cage rotor end.
2024, 51(3):79-85.
DOI: 10.12177/emca.2023.189
Abstract:
In order to improve the estimation accuracy of rotor position and speed for sensorless control of the surface-mounted permanent magnet synchronous motor, an improved nonlinear observer is proposed. By reconstructing the mathematical model of the nonlinear observer, the error equation is constructed, and the stability of the error equation is analyzed by using Lyapunov theory. Based on the stability condition, an error step-size optimization method is proposed to realize the self-regulation of the step gain of the nonlinear observer. The simulation and experiment results show that the improved nonlinear observer has good dynamic performance, and the feasibility is verified.
In order to improve the estimation accuracy of rotor position and speed for sensorless control of the surface-mounted permanent magnet synchronous motor, an improved nonlinear observer is proposed. By reconstructing the mathematical model of the nonlinear observer, the error equation is constructed, and the stability of the error equation is analyzed by using Lyapunov theory. Based on the stability condition, an error step-size optimization method is proposed to realize the self-regulation of the step gain of the nonlinear observer. The simulation and experiment results show that the improved nonlinear observer has good dynamic performance, and the feasibility is verified.
2024, 51(3):86-94.
DOI: 10.12177/emca.2024.002
Abstract:
In order to improve anti-disturbance and control accuracy of permanent magnet direct drive wind generation system, a maximum power tracking control strategy based on non-singular fast terminal sliding mode control with disturbance observer is proposed. The torque of the wind turbine is estimated by the disturbance observer, and the feed-forward compensation of the controller is realized. The non-singular fast terminal sliding mode with improved reaching law is adopted to enhance the dynamic performance of the controller, which ensure the limited time convergence of the system and reduce the chattering infuences caused by disturbance. Simulation results show that the torque change can be accurately estimated under variable wind speed by the proposed strategy, and speed tracking accuracy and wind energy utilization can be improved during maximum power tracking.
In order to improve anti-disturbance and control accuracy of permanent magnet direct drive wind generation system, a maximum power tracking control strategy based on non-singular fast terminal sliding mode control with disturbance observer is proposed. The torque of the wind turbine is estimated by the disturbance observer, and the feed-forward compensation of the controller is realized. The non-singular fast terminal sliding mode with improved reaching law is adopted to enhance the dynamic performance of the controller, which ensure the limited time convergence of the system and reduce the chattering infuences caused by disturbance. Simulation results show that the torque change can be accurately estimated under variable wind speed by the proposed strategy, and speed tracking accuracy and wind energy utilization can be improved during maximum power tracking.
2024, 51(3):95-107.
DOI: 10.12177/emca.2024.003
Abstract:
Taking the multi-motor synchronization control of computer numerical control machine tool servo drive system as the research object, a synchronization control strategy based on multi alternating current servo motors is proposed. This strategy combines a virtual spindle and a deviation-coupled synchronous control approach with back propagation neural network proportional integral derivative control as well as adaptive robust control. The system operation state is simulated by building a Matlab/Simulink simulation platform. The simulation results show that the proposed synchronous control strategy has good synchronous performance and servo effect, and shows superiority in improving the control accuracy and response speed of the multi-motor linkage system, reducing the influence of friction and backlash, and enhancing the robustness of the system.
Taking the multi-motor synchronization control of computer numerical control machine tool servo drive system as the research object, a synchronization control strategy based on multi alternating current servo motors is proposed. This strategy combines a virtual spindle and a deviation-coupled synchronous control approach with back propagation neural network proportional integral derivative control as well as adaptive robust control. The system operation state is simulated by building a Matlab/Simulink simulation platform. The simulation results show that the proposed synchronous control strategy has good synchronous performance and servo effect, and shows superiority in improving the control accuracy and response speed of the multi-motor linkage system, reducing the influence of friction and backlash, and enhancing the robustness of the system.
2024, 51(3):108-116.
DOI: 10.12177/emca.2023.198
Abstract:
With the development of smart grid, the power consumption of each scenario becomes more diversified, and accurate station load forecasting is the key to ensure that the relevant power sector to develop appropriate maintenance tasks, while providing an important reference for orderly power consumption and economic operation. In order to mine the characteristics of the station load to improve the accuracy of the station load forecasting, a station power load forecasting based on the kernel principal components analysis combined with local preservation projection for dimensionality reduction, K-means clustering algorithm (K-means), and bi-directional long short-term memory network (BiLSTM) is proposed. Firstly, the kernel local preservation projection (KLPP) is used to reduce the dimensionality of multi-featured load data in the station area to extract the main feature information. Secondly, the K-means clustering method is adopted to classify the data with similar features into their respective cluster sets. Finally, for each typical type after clustering, BiLSTM is trained in a targeted way, and the load of a low-voltage station area of a university in China is selected as an example to be compared and analyzed with other classical forecasting methods. The proposed method is more suitable for the actual load direction and effectively improves the prediction effect.
With the development of smart grid, the power consumption of each scenario becomes more diversified, and accurate station load forecasting is the key to ensure that the relevant power sector to develop appropriate maintenance tasks, while providing an important reference for orderly power consumption and economic operation. In order to mine the characteristics of the station load to improve the accuracy of the station load forecasting, a station power load forecasting based on the kernel principal components analysis combined with local preservation projection for dimensionality reduction, K-means clustering algorithm (K-means), and bi-directional long short-term memory network (BiLSTM) is proposed. Firstly, the kernel local preservation projection (KLPP) is used to reduce the dimensionality of multi-featured load data in the station area to extract the main feature information. Secondly, the K-means clustering method is adopted to classify the data with similar features into their respective cluster sets. Finally, for each typical type after clustering, BiLSTM is trained in a targeted way, and the load of a low-voltage station area of a university in China is selected as an example to be compared and analyzed with other classical forecasting methods. The proposed method is more suitable for the actual load direction and effectively improves the prediction effect.
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Electric Machines & Control Application ® 2025
Supported by:Beijing E-Tiller Technology Development Co., Ltd.
沪ICP备16038578号-3
Electric Machines & Control Application ® 2025
Supported by:Beijing E-Tiller Technology Development Co., Ltd.
