The Proceedings of the 19th Annual Conference of China Electrotechnical Society

The AC power system used in substation plays an important role in the core of the substation. Due to the risk of loss of voltage in the whole station during the transformation of the traditional mode, the AC power system will operate safely, reliably and stably for the important equipment such as the DC system, the main transformer air cooling system and the power supply of the remote device, and even cause power outage and equipment damage in the power grid system. In view of the above problems, this paper studies a method for the original screen transformation of AC power system used in substation stations and applies it in practice, providing reference for the subsequent substation AC system transformation projects.

The standard IBIS (I/O Buffer Information Specification) model is limited by its voltage range, which cannot accurately and efficiently describe the chip-side response under large input electromagnetic conduction pulses. This paper proposes a transient impulse response behavior modeling method for IC I/O ports based on the extension of the IBIS model, which extends the range of the I/V characteristics in the IBIS model by injecting higher-level TLP (Transmission Line Pulse) pulses to enable the behavioral simulation under high-current-voltage transient pulses. The consistency between simulation and measurement is achieved under TLP pulses, and the accuracy of the extended IBIS model is verified under the excitation of EFT (Electrical Fast Transient) pulses.

As society advances and science and technology progress continuously, the requirements for electrical equipment have become increasingly stringent. Among these challenges, the optimization design of electromagnetic devices poses a complex multi-objective optimization problem due to the existence of coupled physical fields and the involvement of multiple conflicting objectives. Evolutionary-based optimization algorithms are widely employed to address such issues because of their practicality and effectiveness. However, many algorithms are prone to falling into local optima and exhibit poor stability when dealing with complex, high-dimensional, nonlinear mathematical programming problems. To address these issues, an improved multi-objective grey wolf optimization algorithm is proposed. In the improved algorithm, a good point set strategy is utilized in the population initialization; a nonlinear convergence factor is adopted to balance the algorithm’s optimization speed and accuracy; the Levy flight strategy is introduced to effectively utilize the search space, and the population updating mechanism in the beluga whale algorithm’s whale-fall behavior is introduced to further enhance the global search ability. The performance of the proposed algorithm is verified by means of the ZDT series test functions and is applied to the optimal design of a typical electromagnetic device. The numerical results manifest its accuracy and effectiveness.

The phenomenon of sulfur corrosion can badly damage the mechanical and electrical performance of insulation windings, leading to power equipment failures. So as to study the inhibitory effect of 1-bromotetradecane on sulfur corrosion of mineral insulation oil, this paper added 1-bromotetradecane to insulation oil with different degrees of aging. It can be concluded that it increased the breakdown voltage and volume resistivity of the insulating oil, reduced dielectric loss, and improved the electrical performance and operational safety of the power equipment. Adding 1-bromotetradecane to mineral insulation oil can suppress sulfur corrosion and improve its electrical performance.

Aiming at the problem of misalignment of transceiver coils under wide detection range which reduces the power and efficiency of wireless energy transmission, a coil alignment system and method based on the magnetic field coupling law is proposed. The transmitting coil moves within the detection area and generates a coupled magnetic field with the magnetic conductive plate (MCP). By analyzing the relationship between the detection voltage and the misalignment distance in detection zone, a theoretical basis is provided for the autonomous and efficient alignment of the transceiver and transmitter in electric vehicles. Then the effectiveness of the proposed method is verified with simulation experiments. Within a range of 2m, the moving coil is aligned with different sizes of MCPs under severe misalignment, and the alignment errors are all no more than 5mm.

This paper presents a wireless power transfer system with a planar runway-type transmitting coil and a circular receiving coil. The circuit topology and coupling mechanism of system are introduced. A mutual inductance calculation method based on Nieman’s formula is brought up. The coupling mechanism’s charging area are optimized and analyzed. Using this method, mutual inductance, power, and efficiency as functions of position are calculated. In-depth research is conducted on these calculations. Results from numerical calculations demonstrate that the proposed system can broaden the effective wireless energy transfer area and have the ability for multiple loads. It also improves the system’s tolerance for position deviations, maintaining load power and efficiency at 89% of the peak value even with a 20 cm displacement along the x-axis.

Inductive power transfer (IPT) technology has found its way into numerous applications, yet the necessity for supplementary communication devices has hampered its widespread adoption. In response, this study introduces an innovative control approach for the Buck-IPT system on the primary side, which can regulate and estimate the output voltage and current without needing two-way communication. While this control method may impact the robustness and dynamic responsiveness of the system, the integration of sliding mode control (SMC) is proposed as a solution to enhance overall system performance.

Sulfur hexafluoride (SF6) is a very common insulating gas in electrical insulation equipment. When carrying sulfur hexafluoride cylinders, they are generally slightly tilted. However, through force analysis, it is found that when the gravity direction of the measured object is inconsistent with the contact force direction of the weighing module, the force measured by the weighing module is not all of its gravity. The cylinder and the weighing module need to be vertical to measure the true weight of the object. In recent years, the research on weight sensing devices for sulfur hexafluoride storage cylinders has received widespread attention. This paper introduces the process of the wireless sensing system from the perspective of the initial coding and entry and exit of the cylinders, and studies the selection of key components, and finally develops a system for cylinder control and management. Improving the management efficiency of sulfur hexafluoride cylinders on the basis of accurately measuring the weight of sulfur hexafluoride cylinders is of great significance to the efficient operation of electrical systems.

Electric vehicle charging behavior is the basis for implementing friendly vehicle-grid interaction technologies. Based on the charging session data from 2021 to 2023 in a district of Beijing, this paper distinguishes the DC fast charging and AC slow charging type, and adopts a kernel density estimation probability model to probabilistically model the two features of charging behavior, including the start time and duration time. From the two features of charging behavior, we reveal the law of charging behavior on multiple time scales. The results show that the AC slow charging and DC fast charging behaviors of electric vehicles are differentiated in different time scales, and the variation of AC slow charging behavior is more significant.

Button-type metal diverter strips are commonly used for radome lightning protection, and their DC breakdown properties characterize their ionization performance in an environment adjacent to a lightning leader. In this paper, the DC breakdown voltage experiment of the diverter strip was carried out, and the ionization ability of different button-type diverter strips was analyzed. Results show that the increase of the length of the diverter strip result in larger breakdown voltages of the button-type metal diverter strip, but this increasing effect has a saturation trend. When the length of the diverter strip remains constant, an increase in the distance between the metal buttons corresponds to a higher breakdown voltage. Elliptical metal button-type diverter strips exhibit the lowest breakdown voltage, while rectangular button-type diverter strips display slightly weaker ionization capabilities compared to elliptical strips. Results here could provide a theoretical basis for the lightning protection design and optimization of button type metal diverter strips applied to radomes.

Copper wire is the most commonly material for making transformer windings. Graphene is an ideal reinforcement phase for improving the performance of copper wires, and has a hot focus in the field of new transformer materials. The hot-pressing process of graphene copper matrix composites is a method of using graphene to strengthen copper matrix. In this paper, hot pressing process of graphene/copper composites has been adopt hot at the pressure of 20, 30, 40, and 50 MPa; hot pressing temperature 700, 800,900 and 1000 ℃. The results shows that the addition of graphene has a positive effect on the electrical conductivity of the composite material. The conductivity of the graphene/copper composite material will be enhanced by this hot-pressing process. According to the Kelvin Probe Force Microscopy (KPFM) test, the interface of the graphene/copper composites is improved by hot pressing process to the benefit of the electrical conductivity of the composites.

Regarding the issue of wireless power transmission efficiency being affected by special charging structures and inevitable displacement of mobile loads. This paper establishes a wireless power transmission system based on a bilateral dispersed magnetic coupling structure. A series topology structure is adopted on two transmitting coils and a receiving coil. The transmitting coil uses LCC compensation, the receiving coil uses series capacitor compensation. Power and efficiency characteristic curves of charging system with respect to position change are studied. According to the research results, the system structure is improved, anti-offset ability of the system is enhanced. The reliability of power transmission between transmitter and receiver is improved.

In the sensorless control of aero engine starting power generation system, it is difficult for the algorithm based on the voltage fundamental model to identify the rotor position at zero low speed, so the starting system usually adopts the strategy of combining position open-loop starting and sensorless method. In this paper, the research content of motor starting control includes current-to-frequency ratio (I_F) control and switching closed-loop algorithm. In this paper, taking the traditional V_F method as a breakthrough, the I_F method is further studied, and a high-efficiency and high-stability I_F starting method is proposed, and the instantaneous power feedback adjustment algorithm is introduced on the basis of open-loop I_F control, and the current vector is adjusted through the instantaneous power feedback of the motor. The direct switching from open-loop to closed-loop introduces current and speed disturbances that affect the start-up process. Based on the PMSM mathematical model, the mathematical formula of satisfying the voltage continuity is deduced by using the current state feedback decoupling, and it is proved that maintaining the stator voltage continuity of the motor can effectively suppress the speed disturbance in the switching process. Experimental results verify the good performance of the start-up and switching control algorithms.

The battery-electric mining haul truck (MHT) enables zero tailpipe emissions and reduces operating costs if coupled with sufficient renewable energy generation. However, the quick degradation of the onboard battery energy storage system increases lifecycle operating costs. This study introduced the hybrid energy storage system (HESS) to slow down battery degradation. The design problem was formulated to minimize the life cycle cost, including the electricity consumption and the component's degradation costs. The sizing of lithium batteries and ultracapacitors was optimized, subject to the physical limitations. On the other hand, the power distribution between battery and ultracapacitors also impacts the lifecycle costs. In the design optimization problem, the power allocation between batteries and ultracapacitors was optimized by dynamic programming. The nested optimization results indicate that the lifecycle cost of HESS can be reduced by as much as 23.94 percent. The overall weight and volume of HESS is slightly less than the battery energy storage system, decreased by 1.06 percent and 2.56 percent, ensuring achievable layouts. This study introduces a feasible solution and methods to optimize the HESS mining haul truck.

Fast and accurate state of health (SOH) prediction of lithium-ion batteries is an effective guarantee for the safety and reliability of their operation process. However, the majority of existing research focuses on enhancing the SOH prediction accuracy adopting advanced algorithms, and seldom considers the improvement of the prediction efficiency. For this reason, this study first analyses and processes the acquired battery aging data. Then, the charging time of the partial charging voltage profile is treated as the health feature, which circumvents the complex and cumbersome feature extraction process. Subsequently, an efficient battery SOH prediction model is developed, which exploits adaptive learning particle swarm optimization to search for the hyperparameters of the least squares support vector machine. The validation results indicate that the proposed method enables fast training and prediction of the model in less than 1 s. Moreover, the maximum absolute error of SOH prediction on all batteries is less than 2%, which validates the feasibility and applicability of the proposed method.

At present, the data-driven based SOC estimation methods require the collection of a substantial quantity of datasets for the purpose of complex training. This paper proposes a transfer learning SOC estimation method based on Long Short Term Memory (LSTM) with self-attention mechanism. The objective is to provide accurate SOC estimation for small target sample real vehicle datasets. Firstly, learn rich voltage and current features by processing long time series with LSTM. Subsequently, the lengthy temporal span input sequences are compensated with the self-attention mechanism, which results in a global dependency model. Combine the model with transfer learning to solve problems in the target domain using knowledge learnt from the source domain. The experimental results demonstrate that the proposed method exhibits superior SOC estimation accuracy and shorter training time, and verifies the effectiveness for small sample real vehicle datasets.

As electrochemical energy storage systems occupy an increasingly significant position in worldwide new energy system, their safety garners unprecedented attention. Currently, lithium iron phosphate batteries are widely adopted as energy storage units in energy storage power stations. With their tight battery arrangements and high charge-discharge rates, heat accumulation becomes severe. If the battery temperature remains above the upper limit of the appropriate temperature range for a long time, it can easily lead to thermal runaway and cause safety accidents. Therefore, the liquid-cooled thermal management system with high heat dissipation efficiency has become an important support for the development of energy storage technology and a hot topic in both commercial and research fields. This paper focuses on the optimization of the cooling performance of liquid-cooling systems for large-capacity energy storage battery modules. Combining simulation analysis and experimental verification, a novel liquid-cooled plate that balances heat dissipation and operational energy consumption is designed. Additionally, novel ideas for performance improvement, including staggered installation of liquid-cooled plates and differentiated flow rates, are proposed in terms of the layout of the liquid-cooling system and the coolant flow rate settings. Ultimately, the effectiveness of the liquid-cooling system is verified through experiments.

With the rapid increase in the energy density of power batteries, ensuring their safety has attracted growing attention. In order to study the relationship between the safety of a power battery and its energy density, we adopt three typical triggering methods, i.e., penetration, overcharging and heating, to conduct thermal runaway (TR) tests on 13 groups of commercially available power batteries with different material systems and structural forms. The obtained TR behaviors are analyzed based on TR temperature, introduced energy, and TR outcome. The results show that the three methods have different probabilities of triggering TR, and the TR characteristics of the same samples can be different under different triggering modes. The higher the energy density of the battery, the lower the introduced energy required to trigger its TR. When the energy density reaches a certain level, the introduced energy threshold stabilizes.

Lithium-ion batteries, as the sole energy source for electric vehicles, have a significant impact on battery capacity, cycle life, and safety due to their thermal characteristics. The direct cooling plate, as the mainstream heat exchange component of the LIB cooling system, directly affects the temperature of the lithium-ion batteries. In order to improve the performance of the thermal management system, the refrigerant direct cooling thermal management system was studied. Firstly, a direct cooling simulation model was established and verified. And, the results show that the error is less than 10%, which shows that this model is reasonable and credible. Through numerical simulation, different flow channel structures were designed to compare and study. The results show that the double-snake structure direct cooling plate with refrigerant inlets on the outer side shows the better comprehensive temperature and pressure performance than other structures. This research can provide technical support for the design of direct cooling systems.

Accurate residual capacity (RC) estimation of batteries is crucial for safe operation of electric vehicles. However, current estimation method has poor generalization ability and low accuracy, which restricts the promotion and development of electric vehicles. This paper puts forward a data-driven method for accurate RC estimation of lithium batteries. Firstly, 103 LiNCM batteries are tested and analyzed under different temperatures and charging rates. Then, incremental capacity curve is obtained and smoothed thorough Kalman filtering algorithm. The aging features obtained from partial charging curves based on incremental capacity analysis is taken as the input of genetic algorithm-back propagation neural network (GA-BP) model. And the corresponding capacity is taken as the output to train estimation model. The accuracy of RC estimation under different working conditions is verified, and the effectiveness of the estimation method in LiFePO4 battery is also verified. The maximum error of the proposed estimation method is less than 2%, and the average absolute error and root mean square error are both less than 1.5%.

Insulating oil is the primary insulating medium of converter transformers, which may be subject to the influence of direct current superimposed with impulse voltage under working conditions. In this paper, a two-dimensional axisymmetric fluid simulation model of streamer discharge in mineral insulating oil is established based on the hydrodynamic drift-diffusion model. The simulation investigates the initiation and development of needle-plane streamer discharge in mineral insulating oil under short oil gap conditions. The characteristics of streamer discharge are analyzed in mineral insulating oil under various conditions, including different pulse, different voltage amplitude, and different direct current superimposed with impulse voltage conditions to provide theoretical and technical reference for the design of insulation of converter transformers.

We have conducted research on the anti-jumping methods for the 8BK30 switchgear and vacuum contactor of Tieling Power Generation Co., Ltd., which lack anti jump function. After discussing two common schemes, a new anti-jump scheme, namely time relay anti-jump, is put forward. In implementation, a setting method was designed. The new anti-jump scheme of time relay saves money and is easy to implement. The problem of anti-tump of switch is solved by innovative methods.

The application research of short-circuit test trigger device and method of high-voltage overhead line based on autonomous route flight technology of UAV is an innovative design of short-circuit test trigger device of high-voltage overhead line based on autonomous route flight technology of UAV. This device not only has high-precision positioning and autonomous flight capabilities, but also can work stably in complex environments, greatly improving the accuracy and safety of short-circuit tests. By setting up the experimental platform, we verify the effectiveness of the device in practical application, it accurately triggers the short circuit test, and provides a strong guarantee for the safe operation of power lines. Looking forward to the future, this device uses multi-rotor UAV to make test trigger device, which solves the problem that traditional ejection method is difficult to trigger accurately. At the same time, the key parameters and operation methods of the trigger device are determined to make up for the blank of the short-circuit test trigger quantitative control, and contribute to the intelligent and automated development of the power industry.

In order to enhance the economic performance of hybrid energy storage for smoothing wind power fluctuations and to solve the problem of serious modal aliasing in EMD decomposition, a optimal power distribution strategy for hybrid energy storage with maximum net benefit to smooth wind power fluctuations is proposed. Firstly, the wind storage power generation system is constructed, and adaptive sliding filter is used to suppress wind power fluctuations to obtain the total energy storage output, and then the total energy storage output is decoupled based on the two-layer CPO-VMD algorithm, which realizes the optimal allocation of power and capacity of HESS; finally, a cost-benefit model is constructed for the whole lifecycle of HESS, and the quantitative analysis is carried out to analyze the benefits and costs of HESS participation in suppressing wind power fluctuations. Finally, a cost-benefit model is constructed to quantitatively analyze the benefits and costs of HESS participation in smoothing wind power fluctuations.

To ensure the reliable and cost-effective operation of integrated energy systems, accurate multi-load forecasting is crucial. In this paper, a method that combines the Sparrow Search Algorithm with the SE-CNN-LSTM model is proposed for multi-load forecasting. Firstly, qualitative analysis was conducted to identify dynamic coupling relationships among various loads, and a data-driven approach was used to select the influencing factors of multi-loads. Secondly, Convolutional Neural Networks(CNN)were introduced to extract and merge high-dimensional features, followed by the utilization of Long Short-Term Memory networks(LSTM)to further explore the temporal characteristics of multi-load data. Simultaneously, an SE attention mechanism module was incorporated to enhance the significance of critical information between channels. Finally, the Sparrow Search Algorithm(SSA)was employed to optimize the model’s hyperparameters, further enhancing the overall predictive performance. To validate the effectiveness of the model proposed in this paper, a comparison was made with four commonly used models. The results indicate that this model provides more desirable multi-load forecasts for integrated energy systems, outperforming other comparative models, thus providing a scientific basis for subsequent energy scheduling decisions.

It is necessary to quantitatively evaluate the frequency regulation capability of wind power, so as to make the best of the frequency regulation potential and avoid excessive frequency regulation. Therefore, a method considering operating point offset of wind turbine is proposed to evaluate frequency regulation capability. Firstly, a frequency regulation model of wind turbine based on integrated virtual inertia control is constructed. According to the model, it is pointed out that the wind turbine will shift the operating point during frequency regulation. Secondly, considering the mechanical power loss caused by the wind turbine’s operating point offset, the numerical relationship between the available power and the rotor speed is derived, so as to quantify the frequency regulation ability of the wind turbine. On this basis, the variation of the available power of the wind turbine under different operating conditions is analyzed, and the influence mechanism of wind speed and other factors on it is revealed. Finally, the effectiveness is verified by simulation example.

Lithium-ion batteries have become the main energy storage carriers in new energy vehicles, energy storage power stations and other systems by virtue of their high energy density, long cycle life, low self-discharge rate and many other advantages, but the characteristics of lithium-ion batteries’ structure and principle lead to the need for good monitoring and management for their safe and reliable use. Currently, most of the traditional lithium-ion battery condition monitoring methods are based on the characteristics of the external operating parameters of the battery, while electrochemical impedance spectroscopy is a method to study the state of lithium-ion batteries from the internal characterization, this study carries out the measurement experiments of the actual batteries on a time-domain impedance spectroscopy measurement system, traces the characteristics of impedance spectroscopy changes in different SOC (State Of Charge) and temperatures, and researches the relationship of the electrochemical impedance spectroscopy with the influence of the SOC and the temperature. The equivalent circuit model of lithium-ion impedance spectrum is constructed, the model parameters are fitted to the impedance spectrum data based on the ZView tool, and the joint estimation of lithium-ion battery SOC and temperature based on the time-domain impedance spectrum is realized by using the BP neural network estimation model with the model parameters as the inputs, and the lithium-ion battery temperature and SOC as the outputs, and none of the estimation errors is greater than 5%.

This paper analyzes the fault of a rheo-changing light gas false alarm. The reason of the fault is that the insulation cover of a cable of the rheo-changing body gas relay is damaged. In the case of vibration during rheo-changing operation, the humidity in the junction box increases, etc., the alarm circuit is instantly switched on through the damaged insulation cover and other common terminals, resulting in a single set of control system reporting false alarm signals. According to the characteristics of single or multiple sets of control system alarms and whether the alarm signals return, the paper analyzes whether the alarm signals are false alarms, and puts forward the operation and maintenance improvement measures of the gas relay and the disposal methods of different fault signals, so as to avoid blind shutdown of equipment after light gas alarm.

To meet the miniaturization and reliability requirements of satellite system, a design approach on Ka-band transmitting module with a function of cross-backup was proposed. As required by the project requirements, this paper designs a transmitting module which works at Ka band. With the technology of Microwave monolithic integrated circuit (MMIC), and Micro-packaging process, this module consists of 2 channels of input, as well as 4 transmitting channels of output, each give up to 2W RF power and 15% in efficiency. The module has a dimension of 82 mm × 56 mm × 16.5 mm and the mass is less than 110 g. The component includes multiple unit circuits, such as RF/DC combiner, power amplifier unit, etc., which make a high level of integration as well as heat flux density. A lot of efforts have been put on aspects of circuit, structure, and manufacturing details. The circuit design and assemble parameters are optimized to achieve a good consistency of less than 1 dB in gain between 4 output channels. Secondly, the design of heat dissipation was optimized, to achieve the high reliable characteristic of the module. The work of the paper can provide a good reference for similar requirements of transmitting modules.

High percentage renewable energy DC feeder systems may have serious transient overvoltage problems after DC faults. The use of distributed synchronous condenser can suppress the transient overvoltage of renewable energy field station feeder and maintain the power system steady-state reactive power balance, but there is still a lack of research on the coordinated multi-resource reactive power control method of renewable energy field station with distributed synchronous condenser. To address the above problems, this paper proposes a coordinated reactive power control method for renewable energy field station with distributed synchronous condenser. First, the steady-state reactive power output range of the distributed synchronous condensers is determined under different tap positions of the distributed synchronous condensers step-up transformers, as well as their leading/late phase capability. Subsequently, considering the leading/late phase capability and steady-state operation mode of the distributed synchronous condensers, the appropriate tap position of the condenser step-up transformers is selected. Finally, based on the status of automatic voltage control communication, the steady-state reactive power output of the reactive power regulation equipment is coordinated and controlled. Experimental results indicate that the proposed method ensures the reactive power output capability of the distributed synchronous condensers, effectively suppressing transient overvoltages at the sending-end system while fulfilling the reactive power balance requirements of renewable energy generation systems.

Traditional fault analysis and prediction rely on statistical methods that have limitations. They struggle when it comes to capturing the temporal characteristics and long-term dependencies of equipment failures. Currently, a type of fault diagnosis and prediction method applied for power equipment secondary is RNN-based. To begin with, the training samples are the historical states and observations of devices collected in this paper. Then, an RNN model was established to understand and extract the temporal relationships and long-term dependencies with its cyclic structure and memory unit. Thirdly, we capture the temporal patterns and feature representations of equipment failures by use of this knowledge during training. In the end, with new observation data, the RNN model that has already been trained is presented with fault diagnosis and prediction capability. Experiments results suggest that the RNN-based fault diagnosis and prediction method outperform the power equipment secondary. Compared with traditional fault analysis and prediction methods, RNN based fault diagnosis and prediction methods can more accurately capture the time characteristics and long-term dependencies of equipment faults, which can improve the accuracy and precision of prediction.

GIS is an indispensable electrical equipment in power system, but the operation experience shows that the effectiveness of the current commonly used GIS partial discharge detection methods is obviously insufficient. Seeking a GIS defect detection method with high reliability has become a bottleneck problem affecting the long-term operation safety of GIS equipment. As a non-electrical measurement method, light measurement method has a good detection effect on discharge in the weak light environment inside GIS, and has a broad application prospect. In this paper, the photomultiplier tube is used to carry out the discharge experiment in the 110kVGIS model, and the detection effect, attenuation characteristics and anti-interference performance of the optical measurement method for five typical defects are studied respectively. The results show that the optical measurement method has the detection sensitivity which is not lost in the pulse current method and the ultra-high frequency method. It has obvious attenuation characteristics with the increase of distance, but does not affect the detection accuracy. The anti-electromagnetic interference ability is obviously stronger than the electrical detection method. The experimental results of this paper have certain engineering value and reference significance for the application of optical measurement method in GIS partial discharge detection.

In this paper, a black-start strategy is proposed for wind turbines as the main power supply, without relying on the external circuits of energy storage converters and diesel generators or energy storage equipment, without any external circuits in the main circuit, and the process of establishing AC bus is realized by adjusting the starting mode of the converter and improving the control strategy. In addition, this paper combines the virtual synchronous machine control in the network structure control strategy and improve the system stability. At the same time, the impedance model of the grid-side converter is established to analyze the stability of the system. Finally, the effectiveness of the direct black start strategy is verified in the Matlab/Simulink simulation platform.

In recent years, the development and application of high voltage cables with smooth aluminum sheath have attracted much attention in China. Compared to corrugated aluminum sheaths, the mechanical properties of smooth ones are a focal point of industry interest. The smooth aluminum sheath is manufactured either by welding plates or by melt extrusion to form a loose tube, followed by diameter reduction through drawing or rolling process. As a result, its mechanical properties may be affected by the production process. In this paper, sheet samples with and without weld seams were taken circumferentially and axially from the welded or extruded smooth sheaths, which had undergone the roller pressing process. Then, the tensile strength, yield strength and elongation at break of the samples were tested and compared to assess the impact of the production process. Simultaneously, metallographic samples were prepared by cutting and polishing the aluminum sheets. After acid etching or alkali etching, the grain morphology and microstructure defects on the sample surface could be observed, providing insights into the reasons for changes in mechanical properties. The results indicate that for the welded sheath, the argon arc welding process and the presence of weld seams have minimal impact on the mechanical strength. However, both factors will reduce the plastic deformation property, especially in the direction perpendicular to the weld seam. The subsequent rolling treatment can improve the microstructure of the aluminum material, thereby mitigating the negative effects caused by the weld seam. For the extruded sheath, although its initial mechanical properties are excellent, the rolling process can deteriorate the grain size distribution, resulting in decreased strength and toughness. In summary, both types of aluminum sheaths exhibit outstanding mechanical strength, while the extruded one is better in plastic deformation performance.

Ultra-short-term precise power prediction is crucial for achieving intelligent control of traction bidirectional converter devices in urban rail transit systems. Accurate power prediction can not only optimize energy distribution and improve system efficiency but also effectively reduce energy consumption and communication operation costs. Therefore, a power prediction method based on deep learning is proposed. This method collects information on the kilometer markers of trains, as well as the DC voltage and DC current information of traction substations, to perform ultra-short-term prediction of the active power at the station. This effectively improves the accuracy of the prediction, thereby achieving more intelligent and sustainable control. Tested with actual operating data from a metro system in China, the deep learning model developed in this paper demonstrates low error, low complexity, and prediction performance that meets engineering requirements when used for power prediction.

This paper analyzes and discusses the winding vibration characteristics of a permanent magnet synchronous generator (PMSG) before and after demagnetization fault. Firstly, the winding electromagnetic force (EF) under both normal and fault conditions is deduced, and a simple forced vibration model of the end winding is established. Then, the end winding EF and vibration characteristics are analyzed. Finally, specific working conditions are calculated and verified through finite element analysis (FEA), showing consistency with theoretical conclusions. The results show that under normal conditions, the end winding exhibits vibrations at even multiples (mainly twice) of the electrical frequency. After the demagnetization fault, the double frequency vibration of the winding persists, and the fractional frequency components of n/p electric frequency emerges. In addition, the amplitude of the double frequency decreases as the degree of demagnetization increases, while the amplitude of the fractional frequency components increases with the degree of demagnetization. When the total degree of demagnetization is the same, different demagnetization ranges and positions have no effect on the double frequency amplitude. However, a larger demagnetization range results in a smaller amplitude of the fractional frequency components. But different demagnetization positions have no significant effect on the frequency components and amplitude of winding vibration. After a uniform demagnetization fault occurs, the frequency components of the winding vibration remain largely unchanged compared to normal conditions, but the amplitude of the double frequency decreases. These results can provide a reference for the health management of permanent magnet synchronous generators, helping to ensure the safe and stable operation of wind turbines.

The PCB board of automotive circuit electromagnetic compatibility (EMC) rectification is increasingly demanding for limited space, requiring convenience and efficiency, and on-site rectification must shorten time and reduce costs. On the basis of the traditional classical LC filter commonly used in EMC rectification, the zero points of some frequency points in the stopband of the filter are obtained by transforming the capacitive or inductive components of the series branch into the LC parallel resonant circuit, and the position and depth of the stopband zero point can be adjusted by the capacitive or inductive value and Q value of the resonant circuit respectively, which greatly increases the stopband suppression, and a wide range of high stopband suppression can be realized without greatly increasing the order of the LC filter. A transformed improved LC filter is designed and debugged successfully through simulation optimization. The improved filter has the advantages of miniaturization, low loss, high rejection, adjustability and low cost. Compared with the traditional classical LC filter, the insertion loss at the cutoff frequency of the passband is only 0.79 dB worse, and the stopband suppression at the near-end frequency of the stopband is increased by 31.5 dB. The stopband suppression at the frequency of 968.4 MHz is improved by 22.4 dB, and the rectification process has the characteristics of reliability, simplicity and rapidity, which can be applied to the EMC over-standard rectification of automobile circuits in the corresponding frequency bands of common national standards GB 34660-2017 and GB/T 18387-2017.

The access of distributed power sources will change the vulnerability of the distribution network in different degrees. First, a distribution network vulnerability assessment model is proposed, and the voltage stability margin index of the system is determined based on the tidal current calculation results of the power system. On this basis, a distribution network vulnerability assessment model based on IEEE33 nodes is constructed by considering the access mode, access location and access capacity of distributed power sources to verify the reasonableness and validity of the proposed method, so as to lay a theoretical basis for reducing the vulnerability of the distribution network and optimizing the planning of distributed power sources in the distribution network.

In recent years, with the rapid increase in the penetration rate of new energy sources and the scale of direct current (DC) injection, the inertia level of the receiving-end power grid has been continuously decreasing, leading to an increasingly prominent frequency security issue. Under different types of disturbances such as DC blocking and commutation failure, the receiving-end power grid is at a high risk of frequency collapse, necessitating a clear understanding of its minimum inertia requirements. To address this, this paper proposes an assessment method for the minimum inertia requirements of the receiving-end power grid considering different types of faults. Firstly, a multi-machine frequency response model is constructed, which includes various types of units and AC interconnections in the receiving-end power grid. Subsequently, the multi-machine frequency response model is discretized, and an improved Newton-Raphson algorithm is employed to solve for the system’s minimum inertia value that ensures the frequency response curve of the receiving-end power grid is located at the critical position, based on the constraints of maximum frequency deviation and frequency rate of change. Finally, the effectiveness of the proposed method is verified through a case study of a provincial power grid. The results demonstrate the validity of the proposed method.

To address issues encountered during prolonged operation of low-voltage servo systems powered by batteries—where continuous battery discharge leads to lowered bus voltage, saturation of back electromotive force, restricted starting current and torque resulting in degraded startup performance, and overall slower system response speed; as well as problems stemming from prolonged motor operation causing changes in resistance and inductance parameters, leading to reduced system efficiency and shortened operational endurance—a control strategy is proposed. This strategy is based on an improved voltage loop Quasi-Z-source inverter adaptive PI regulator for permanent magnet synchronous motors. It integrates the Quasi-Z-source network with traditional low-voltage servo drives, incorporating the rate of change in the amplitude of the synchronous motor phase current as a compensatory factor into the Quasi-Z-source network voltage control loop. This forms a positive feedback voltage loop control structure aimed at boosting the DC bus voltage. Additionally, the strategy employs the least squares method for online identification of motor resistance and inductance parameter variations, enabling real-time adjustment of PI parameters to ensure reliable system operation while extending endurance time. The effectiveness of this control strategy has been demonstrated through MATLAB/Simulink simulations and practical experiments.

For the operation of the PMSM, when facing the conditions of high temperature, demagnetizing field or other bad conditions, the permanent magnet in motor would have irreversible demagnetization, which could affect the whole machine. So far, many analytics methods and numerical methods are used in dealing with the calculation of demagnetization field. In this paper, a hybrid model combined analytical subdomain method and FEM is proposed. The FEM is used to model the rotor part of PMSM, and the subdomain method is used to model the air gap and stator. Comparison between different models was made to estimate the accuracy and speed of the proposed model, and the result shows that while retains high calculation accuracy, the model also improves greatly the speed when calculating the demagnetizing field problem.

When the circuit breaker of the hydraulic operating mechanism is in normal operation, its pressure value will drop. If the pressure value drops, the pressing motor can not press normally because of external factors to restore the pressure value to the rated value, if it is not found and treated in time, the pressure will be further reduced, resulting in the closure of the switch, causing great harm to people, power grid and equipment. Based on the practical work, the hydraulic low-monitoring circuit of the circuit breaker of the hydraulic operating mechanism is designed and perfected, and the pressure value of the circuit breaker is effectively monitored to ensure the reliability and stability of the operation of the hydraulic circuit breaker, the paper provides a reference for the prevention and solution of the accident.

With the rapid advancement of high-integration power modules, the encapsulation structure is faced with a severe challenge of increasing electrical and thermal stress. Subjected to direct current (DC) conductions, space charge accumulation and charge transportation can cause local electric field distortion, exacerbate insulation aging, and thereby increase the risk of breakdown failure. In this paper, A heat-conducting silicone gel is taken as the research object. The space charge measurement under high-temperature DC voltages is conducted based on pulsed electro-acoustic (PEA) method. The DC conductivity and DC breakdown strength are also tested at corresponding temperatures. It is found the breakdown performance of silicone gel degrades with temperature, while the DC conductivity increases slightly. The electrode charge injection is analyzed as the main source of homocharge accumulation. Under thermal excitation, the ability of molecular chains to release electrons increases with the temperature increasing, which is reflected as an increasement of hole injection within a certain period after polarization.

The excitation generator is widely used in special vehicles, but there are shortcomings of weak low-speed load-carrying capacity and low power density. In view of the shortcomings of the regulator control excitation generator, this paper designs a higher energy density, low-speed load carrying capacity can output ± 28 V power supply of the double-winding permanent magnet synchronous generator controller, from the overall program design, the main parameters of the design, structural design of the three aspects of the design of the controller, after the performance simulation and physical performance tests can be concluded that the permanent magnet generator controller is not only After the performance simulation and physical performance test, it can be concluded that the permanent magnet generator controller not only has high power density and strong load carrying capacity, but also has high output voltage precision, strong stability and strong dynamic adjustment ability.

The position sensorless control of permanent magnet synchronous motor reduces the cost and maintenance difficulty of the system and avoids the problems arising from sensor failure, but there are some shortcomings concerning dynamic performance and robustness, etc. In view of the jitter problem inherent in the traditional sliding-mode observer, this paper will use the super-twisting algorithm to improve it, and achieve the suppression of jitter vibration and reduce the error caused by high frequency jitter vibration when obtaining the position information of the rotor by including high-frequency switching into the integral term for observing the reversed electromotive force to make the system position and speed estimation more accurate. By including the high-frequency switching in the integral term, the jitter suppression is achieved, the error caused by the high-frequency jitter is reduced when obtaining the rotor position information, and the inverse electromotive force is observed, so as to make the system position and speed estimation more accurate. And the online parameter identification method is used to improve the problems such as system performance degradation caused by parameter errors. Finally, a simulation comparison analysis is carried out on MATLAB/Simulink, and it is concluded that the use of the super-twisting sliding mode algorithm has a great degree of improvement in the elimination of jitter vibration.

In order to improve the energy efficiency of new energy vehicles, reducing the inverter loss in the motor electronic control system is a very important part. In this paper, the finite element FEA analysis method is used to build a simulation circuit using MATLAB/Simscape platform. The circuit structure includes bus DC power supply part, permanent magnet synchronous motor control circuit part, three-phase two-level inverter circuit part, permanent magnet synchronous motor module and mechanical transmission system part. The control stratagem of MTPA (Maximum Torque Per Ampere) calculates the corresponding target operating current values of Id and Iq based on different desired torques. The PWM generator is responsible for converting the target voltage, obtaining six PWM waves to control the switching devices in the inverter circuit, and then output the corresponding three-phase AC voltage at the output end. The loss of inverter power components is measured by changing different motor operating points, switching PWM control strategy and changing switching frequency. The simulation results show that the DPWM2 algorithm has less loss for the inverter in the experimental model under the condition of fixed speed and load.

Against the backdrop of the dual carbon target, China's renewable energy technology has made rapid progress and costs continue to decrease. Utilizing low-cost renewable energy to create typical zero carbon industrial parks has become a key development focus. This article is based on the planning and design of a multi energy complementary comprehensive system for renewable energy such as geothermal energy, and uses park resources to determine and solve the energy demand of industrial parks according to local conditions. We calculated the heating load of existing buildings in the park and compared and analyzed the effects before and after energy-saving renovation. This article compares the economic efficiency of various heating methods that meet the needs of park heating, such as solar energy and heat storage, geothermal utilization, and electric heating, and provides the comparison results of heating costs per kilowatt hour. Based on the situation of wind, solar, and geothermal energy resources in the park, the integrated energy system based on multi energy complementarity was designed in the practical application scenarios of industrial parks, and the economic and carbon dioxide emission reduction effects after the implementation of the solution were quantitatively calculated.

Hydrogen content is an important indicator for judging the internal fault of oil-immersed transformers. The accuracy and timeliness of the detection results of the hydrogen sensor are of great significance for the early warning of equipment failure. In this paper, a test platform was designed and built to study the performance of two types of sensors, hydrogen measurement in gas mixture and direct measurement of hydrogen in oil based on palladium alloy, and the performance of two types and three sensors were compared and tested from six aspects: response characteristics, repeatability, sensitivity, linearity, cross-interference and temperature. The results show that the sensitivity of the hydrogen sensor based on $${\text{SnO}}_{2}$$ SnO 2 reaches 0.3 V/ppm, and the response time is about 40 min considering the oil-gas separation process. The change of hydrogen concentration in oil measured by the GRIDSCAN 5000 direct detection sensor of hydrogen in oil based on palladium alloy is about 1.7 ppm per minute and the response time is about 60 min, and the change of hydrogen concentration in oil measured by the Model 3000 direct detection sensor is about 2.5 ppm per minute, and the response time is about 60 min. The sensitivity of the hydrogen sensor is better than that of the palladium alloy-based hydrogen in oil direct measurement sensor, and the response time is also shorter. However, due to the large size of the degassing module, it is extremely inconvenient for practical operation. The direct-to-oil hydrogen sensor is small in size and easy to carry, and is widely used in fault detection of electrical equipment.

The Integrated Energy System effectively leverages multiple energy sources to promote energy conservation, reduce emissions, and improve efficiency. This paper presents an optimal dispatch model that integrates the dispatchability of the heat supply pipeline network with demand response mechanisms, accounting for heat storage capabilities. Simulation results demonstrate that incorporating these storage characteristics enables seamless coordination between the electrical and heating systems across time and space. Furthermore, demand response effectively alleviates peak power supply pressures and reduces renewable energy curtailment, thereby enhancing overall system efficiency.

In this paper, turn-on and turn-off simulation experiments are carried out on a 6.8 kV super-connected device based on silicon carbide (SiC) MOSFETs using LTspice simulation software to analyze its voltage equalization performance under dynamic and static conditions. The results show that the conventional super-connect topology suffers from drain-source overvoltage phenomenon and gate oscillation problem during the turn-on process, which affects the stability and reliability of the device. In this paper, an improved superlink structure is proposed, which significantly improves the gate oscillation problem during turn-on and turn-off and optimizes the dynamic voltage equalization effect of the drain-source voltage by connecting capacitors in parallel on each MOSFET, removing the pull-down resistor, and connecting a fast recovery diode in anti-parallel on the drive resistor. Simulation results show that the optimized super-connected structure exhibits better voltage distribution equalization in both turn-on and turn-off processes, and the maximum drain-source voltage difference is significantly reduced, which improves the stability and reliability of the system. The improved scheme in this paper provides an effective solution for the design of high-voltage and high-frequency power semiconductor devices, which has important theoretical significance and practical application value.

SiC MOSFETs are key components in high-reliability, high-power-density electric drive inverters, making fast and accurate power loss calculations essential for device selection and thermal design. Current methods for determining the power loss of SiC MOSFETs using circuit simulation software have limitations, including complex debugging processes, time consumption, and incompatibility with devices lacking simulation models, which affects many domestic manufacturers. This paper proposes a fast calculation model for the power loss of SiC MOSFETs in inverters based on the power device datasheet. Simulations compared with PLECS software indicate that the maximum error in the total power loss calculated by the proposed method is approximately 5%. This level of accuracy provides valuable guidance for the preliminary screening and engineering application of SiC MOSFETs in electric drive inverters.

The coil-type electromagnetic launch technology has the remarkable characteristics of non-contact, fast launching speed, large kinetic energy, excellent controllability, high energy conversion efficiency, etc., and it is an important part of the development program of future weapon systems. This paper describes in detail the principle of coil-type electromagnetic launch technology and summarizes the main research progress in this field in recent years. The key technologies of coil-type electromagnetic launch and their development are summarized from six aspects, namely, energy storage technology, electric energy regulation technology, coil and projectile design, trigger position control, power suppression of the throwing mechanism and field coupling research, and the research history is sorted out, and the trend of the application of the coil-type electromagnetic launch technology in the field of military, civil and aerospace is also prospected. It aims to provide certain reference and guidance for the subsequent research of coil-type electromagnetic emission technology at home and abroad.

When hypersonic vehicles are flying fast, the vehicle and atmosphere are heated up by intense friction, resulting in the dissociation or ionisation of the surface atmosphere and the formation of a plasma sheath. Plasma sheath interferes with electromagnetic wave transmissions and can cause severe interruptions to vehicle communication signals, forming a “blackout”, which poses a great threat to the safety of hypersonic vehicles. Due to its high peak power, high power microwave will change its electromagnetic characteristics after irradiating the plasma sheath, and scholars have already carried out the research of mitigating the problem of blackout of the vehicle through high power microwave irradiation. However, the flight state of hypersonic vehicles will seriously affect the electromagnetic properties of the plasma sheath, which in turn affects the irradiation effect of high-power microwaves. In this paper, plasma sheaths were irradiated for a certain period of time at different flight altitudes and flight speeds using high-power microwaves, and an increase in low-frequency transmission of electromagnetic waves has been found at low altitudes and high speeds, which is helpful for the alleviation of the blackout. It is essential for alleviating the blackout of hypersonic vehicles.

Traditionally, the closed-loop controller of Buck converters is designed on the premise of ignoring the nonlinearity of the switching devices and linearizing the converter with the small signal model. As a result, when the parameters are perturbed, or the load is disturbed, the dynamic and the static performances and the disturbance rejection performance of the controller will be degraded. Therefore, the switching control based on the hybrid system theory is introduced into Buck converter control to overcome the disadvantages mentioned above. However, the algorithm of the switching control law involves many matrix operations and still inevitably requires the object parameters. Considering the powerful ability of neural networks to approximate complex nonlinear functions, and the fact that the parameters of the object model are not needed when training, a backpropagation neural network (BPNN) is designed to replace the switching control. To achieve simpler neural network structure and better learning performance, the BPNN only learns the continuous input-output parts in the switching control scheme, keeping the last part which generating discrete driving signal. The simulation results indicate that the BPNN control scheme inherits the excellent dynamic and static performances of the switching control and weakens the model parameter dependence. In addition, the generalization ability of neural networks enables the proposed BPNN control scheme to exhibit stronger parameter robustness.

Marx circuit based on avalanche transistors (ATs) is widely employed to generate high-voltage nanosecond pulses. The introduction of auxiliary triggering topology (ATT) has the potential to significantly reduce the failure rate of ATs. However, investigations into the characteristics of the auxiliary trigger pulse, the circuit operation process, and the switching mechanisms of ATs have primarily relied on theoretical analysis and simulation. Consequently, the effects of stray parameters and other practical factors are often inadequately addressed, thereby limiting the revealable advantages of Marx circuit adopting ATT. In this paper, a multi-stage Marx circuit adopting ATT based on ATs and its simulation model are proposed, and the aforementioned issues are experimentally studied. The results indicate that ATT could utilize the voltage leap generated by the conducted front stages of the Marx circuit to obtain the voltage difference between the base and emitter of ATs, allowing for the formation of auxiliary trigger pulses with distinctive characteristics. Then, the switching mechanisms of ATs in the Marx circuit could be converted from the voltage ramp mode into the base triggering mode. Additionally, the voltage leap enhances the collector-emitter voltage of ATs, so the switching speed of ATs under auxiliary triggering pulses is faster than the traditional base triggering mode. Furthermore, the typical output waveform measured on the 50 Ω load of the 5-stage Marx circuit adopting ATT approximates a double exponential pulse (rising time 2 ns). This work is expected to inspire advancements in circuit optimization, waveform adjustment, and other benefits in applications.

This article studies the implementation scheme of minute level collection of electricity information business. Firstly, the architecture of the electricity information collection system and the process of collecting electricity information data were introduced; Then, the minute level collection capabilities of the main station, concentrator, CCO, energy meter, and STA in the substation area were analyzed, and the data transmission delay of the equipment interface was quantitatively calculated to clarify the bottleneck that restricts the data exchange efficiency of the data acquisition system; Based on this, suggestions have been proposed to enhance the data processing capabilities of the data acquisition system, including improving message processing capabilities, increasing data storage capacity, improving serial communication speed, and increasing concurrency; Finally, the application prospects of minute level acquisition technology in the fields of phase recognition, anti electricity theft, photovoltaic output fitting and prediction are discussed, and the importance and practicality of this technology in power system management are elaborated.

In response to growing environmental concerns, this study proposes the use of dry air as an insulating gas in gas-insulated switchgear (GIS) to replace the traditional SF6 gas. To address the problem of gas leakage, the helium tracer method is employed to detect the leakage of insulating gas within the equipment, focusing on the impact of helium addition on the insulation performance of GIS. Electrodes and experimental chambers were designed to simulate the electric field conditions under actual operating circumstances. Breakdown voltage experiments at power frequency were conducted to study the insulation performance of mixed gases with three different concentrations of helium under two pressure conditions. The breakdown voltage values at power frequency were theoretically analyzed from the perspective of gas discharge. Additionally, the breakdown voltage dispersion of mixed gases with different concentrations of helium was analyzed, considering the operational stability of GIS equipment. The experimental results indicate that the addition of helium has a negligible effect on the insulation performance of dry air when compared to the pure dry air power frequency breakdown results. This confirms that the helium tracer method is an effective technique for detecting the leakage of insulating gas in environmentally friendly dry air GIS equipment.

Arc faults are highly harmful to power systems. Due to the expansion of transmission lines, the possibility of arc fault occurrence and the complexity of the location are further increased, so it is of great significance to locate and clear arc faults in time for the operation and safety of transmission line. Aiming at the problem that the electromagnetic time reversal (EMTR) method cannot locate the arc fault near the observation point, a two-terminal EMTR method based on the image minimum energy is proposed. The simulation results show that this method can locate the arc fault well. Through the simulation of different fault location step conditions, it is found that the maximum error of this method is 270 m when the arc fault occurs in the middle of the line.

With the expansion of transmission lines and the rise of voltage levels, the risk of arc faults increases. Furthermore, the effects of fault occurrence in a part of the system are not limited to itself and other parts are also affected during this event. Therefore, locating and repairing arc faults in time are significantly important for the operation and safety of transmission lines. This paper reviewed various fault location methods, such as impedance-based method, travelling wave-based method, time reversal theory methods, and artificial intelligence methods. Each type of fault location methods was discussed with advantages and shortcomings. The results can be helpful for the future work of arc fault location.

Wildfires present a considerable challenge to both natural ecosystems and constructed environments, as well as to the safety and economic stability of communities located in areas susceptible to such events. Among the built environments, the electric power grid is particularly vulnerable to the impacts of wildfires, both as a victim and a contributing factor. The high costs and inefficiencies associated with manual inspections of transmission lines hinder power grid companies from implementing effective preventive measures. In recent years, advancements in deep learning technology have led to significant improvements in target detection methods, which are now being widely adopted in various industries. However, the deep learning approach is not without its limitations, including issues related to interpretability. This paper proposes a detection method for wildfire threats that integrates object detection with neural-symbolic reasoning. Experimental results indicate that this approach can deliver relatively stable and efficient detection of wildfire threats within electric grid networks.

Particulate matter is common in nature and engineering applications. The fine particles deposition in the room will cause material degradation, such as damage to artworks and electronic equipment; Particles deposited on the surface of the industrial equipment will collide and accumulate, causing equipment wear, blockage, and reduced performance, resulting in potential safety hazards. In this work, taking the particle collision, rebounding, and agglomeration into consideration, the coupled computational fluid dynamics-discrete element (CFD-DEM) method was employed to study the deposition mechanisms of particles on a rib-roughened surface. The results showed that the rough structure can generate turbulent vortexes in the vicinity, enhancing the entrainment of small particles, and creating a particle deposition velocity that is significantly higher than that of a smooth surface, which can be used for significant improvement of indoor air quality. However, the larger particles were rebounded after colliding with rough structure, resulting in the deposition velocity less than that of a smooth surface. Moreover, some particles were agglomerated and chain-like structures were formed due to the inter-particle adhesion force, and thus improved the deposition capability of particles. This work provides an important theoretical basis for pipeline cleaning, design, and maintenance.

This article analyzes the energy efficiency evaluation indicators of data centers and highlights the importance of accurate measurement of electrical energy data. Based on the characteristics of online operation of power meters in data centers, a practical method for online instrument calibration and comparison is proposed. This method allows standard meters to be installed in parallel with the meters under test on the same circuit, without disrupting the normal operation of energy-consuming equipment. The timing start condition is based on the change in the last digit of the tested instrument, and the timing stop condition is based on the change in the last digit, which improves the accuracy of synchronous timing. Two practical error discrimination methods are proposed for the measurement comparison results. For instruments with large errors that cannot participate in energy efficiency calculations, a proportional correction method is adopted, and a correction coefficient is introduced. Considering the large number of meters in data centers, sampling principles were proposed, and the effectiveness of the method was verified through engineering empirical analysis.

To address the problem of small samples and unbalanced data of dissolved gas fault data in transformer oil. This paper proposes an enhancement method of dissolved gas data in transformer oil based on the Riemannian mani-fold variational autoencoder. Firstly, the one-dimensional fault samples are transformed into two-dimensional feature images by an improved Gramian Angular Field to construct the original image dataset. Based on the network framework of the variational autoencoder, the latent space is modeled as a Riemannian manifold using the Riemannian metric to capture complex data distributions better; data enhancement of all types of fault samples is realized through the Riemannian Hamiltonian dynamics using the Riemannian Hamiltonian Monte Carlo sampler. The experimental results on the dissolved gas fault dataset in transformer oil illustrate that compared with the traditional method, the approach proposed in this paper can generate more meaningful fault samples without distorting the actual data distribution under the condition of small samples and unbalanced data so that the fault identification accuracy of the deep learning model can be effectively improved.

Effective fault diagnosis in wind turbine operations is crucial for ensuring safety, reliability, and cost efficiency. This paper presents a machine learning-based approach for detecting multiple demagnetization faults including (unipolar, multi-magnets, adjacent, and uniform demagnetization) in Permanent Magnet Synchronous Generators (PMSG). The approach utilizes FEM 3D simulation models to analyze stator current and flux signals for fault detection. Discrete Wavelet Transform (DWT) is employed for feature extraction under both healthy and faulty conditions. We evaluate the performance of three primary machine learning classifiers—Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Ensemble methods—along with 17 sub-classifiers, for diagnosing faults using current and flux signals in PMSG. The results indicate that flux signals are more effective than stator current signals for detecting demagnetization faults. In the simulation, eight out of seventeen classifiers achieved 100% classification accuracy for all faults in PMSG using leakage flux signals, surpassing the accuracy obtained with current signals. However, Ensemble Bagged, Ensemble RUS, Coarse KNN, and Medium KNN classifiers demonstrated suboptimal performance.

Wireless capsule endoscope (WCE) can be used for the diagnosis and treatment of gastrointestinal diseases. Compared with MRI and CT, the magnetic inversion method is safer, more cost-effective, and efficient. The scalar triangulation and ranging (STAR) method can locate the WCE in real-time, but there is an inaccurate-positioning area in the STAR method. This paper proposes an avoidance method for the inaccurate-positioning area (AMI) by adjusting the vector angle through current vector control. When using the AMI to locate the WCE, the positioning accuracy is 0.0008 m, which induces the positioning accuracy of the STAR method by 96.7%.

With the development of power system, arc fault detection becomes particularly important. In order to improve the detection efficiency and accuracy of arc faults, this paper proposes a semi-supervised learning method combining virtual adversarial samples and boundary uncertainty sampling to solve the problem of insufficient labeled data and low cost of unlabeled data. First, the model's resistance to unfamiliar disturbance is enhanced by introducing virtual adversarial samples to enhance the training set. Secondly, the boundary uncertainty sampling is used to improve the judgment ability of the model in complex cases, so that the model can diagnose faults more accurately in practical applications. The experimental results show that the proposed method is more accurate than the traditional supervised learning method in arc fault detection. Especially in the case of incomplete data labels, the diagnostic performance of the model is significantly improved by rational use of unlabeled data. This finding validates the effectiveness and potential of semi-supervised learning in dealing with electrical fault diagnosis problems with practical application value.

Due to the lack of causality between upstream and downstream industries in the existing load forecasting research, the accuracy of load forecasting between industries is poor. Therefore, this paper proposes an HPO-BiLSTM industry load forecasting method based on causal analysis. Firstly, convergence cross-mapping algorithm is used to identify the causal relationship between ferroalloy industry and related industries, and typical industries with strong causality are selected. Secondly, the original load data is decomposed by an improved adaptive noise complete empirical mode decomposition method. Finally, the hunter and prey algorithm is used to optimize the bidirectional long and short term network, and the decomposed load data is predicted. Finally, the accuracy of the proposed method is compared with that of XGBoost and LSTM prediction models. Experiments show that the proposed method can effectively extract the relevant features of different industries in the load prediction of ferroalloy industry. The prediction accuracy is significantly improved, which provides important support for rational planning and stable operation of urban power grid.

Aiming at the high reliability requirements of the working environment of the integrated permanent magnet servo motor on its internal drive control system, this article studies the reliability of the integrated permanent magnet servo motor control system. First, complete the system hardware design, and then use component stress analysis The reliability expected method and stress data obtain the disordered data of each electronic component during the design phase, convert it into a faulty tree model of the failure of the failure and build the fault tree model of the integrated motor control control system, and conduct qualitative analysis and quantitative on this basis Analysis, and based on the results of reliability analysis, put forward some measures to improve the reliability of the integrated driving control system.

In response to the oscillation problem of traditional Sliding Mode Observer (SMO) in the sensorless control of permanent magnet synchronous motor (PMSM), this paper adopts an improved Super Twisting Algorithm Sliding Mode Observer (STA-SMO) to estimate the angle and speed of permanent magnet synchronous motors and reduce the oscillation phenomenon. The improved sliding mode observer is based on the super spiral sliding mode observer, using saturation function instead of switching function as the switching function, and using inverse tangent function to calculate the rotor position, which weakens the low-speed vibration phenomenon of the super-spiral sliding mode observer and improves the low-speed dynamic performance and steady-state performance. In order to enhance the characteristics of both low-speed and high-speed domain, a Sliding Mode Controller (SMC) instead of a PI speed loop based on the previous model is adopted, which improves the dynamic performance of both low-speed and high-speed domains in terms of speed overshoot and rise time.

Clean and low-carbon is the core task of building a new power system, and the development of an integrated energy system with multiple energy flows is the key. For the “electricity-gas-heat-cooling” integrated energy system that takes carbon trading into account, the optimized configuration strategy of the “electricity-gas-heat-cooling” inter-grated energy system that simultaneously couples five types of energy storage devices and fuel cells/electrolysis cells is studied. Considering the carbon emission characteristics of the whole life cycle of each equipment in the system, the stepped carbon trading mechanism is analyzed; the effectiveness of the joint optimization of renewable energy power generation and P2G in establishing a low-carbon system is analyzed through a multi-scenario comparison, with respect to the influence of the carbon trading mechanism on the planned output and carbon reduction of each equipment of the integrated energy system; and the three coefficients of the baseline carbon price, the length of the interval, and the growth rate of the carbon price in the stepped carbon trading mechanism are discussed. The three coefficients of benchmark carbon price, interval length and carbon price growth rate of the stepped carbon trading mechanism are discussed. The results show that by rationally setting the benchmark price of carbon trading, the carbon emission of the integrated energy system of “electricity-gas-heat-cooling” can be effectively reduced, the installed capacity of low-carbon equipment can be increased, and the power and energy enterprises can be helped to realize carbon neutrality.

Leakage current suppression is a key issue that must be addressed in non-isolated PV inverters. In this paper, a battery array neutral point grounded photovoltaic inverter topology is proposed, which consists of three parts: a boost circuit, an intermediate voltage equalization circuit, and an inverter circuit. The boost circuit maintains a constant DC bus voltage and maximum power tracking, which improves system power conversion efficiency. The intermediate voltage equalization circuit ensures that the voltages of the upper and lower bridge arms of the half-bridge inverter circuit are balanced, thereby improving the quality of output power. The connection point of the two PV arrays is grounded to clamp the common mode voltage, thereby suppressing the leakage current and improving the reliability, safety and lifetime of the PV inverter. For the proposed inverter topology, the corresponding controller is designed and the simulation is completed. The simulation results are consistent with the theoretical analysis, which verifies the correctness and the feasibility performance of the proposed inverter topology.

C3F7CN is a new green insulation gas which can reduce SF6 emission. The fault in equipment with C3F7CN insulation gas can be diagnosed by detecting decomposition components. Metal-doped MoS2 is considered to be suitable for gas sensors with good adsorption property. In this paper, the stability of Ni- MoS2 is studied and its adsorption performance and sensing characteristics for C3F7CN main products including CO and CF4 are analyzed according to the first-principle. The results show that Ni can be doped on the MoS2 stably. The adsorption energy and charge transfer of Ni-MoS2 to CO are -0.753 eV and 0.104 e with chemisorption. Meanwhile, the Sensing characteristics of Ni-MoS2 for CO are ideal, and it can be used for C3F7CN mixture decomposition detect. The adsorption properties of Ni-MoS2 for CF4 are poor. The results can provide theoretical basis for C3F7CN mixture equipment diagnostics.

The use of supercapacitors as energy storage devices in wireless power transfer (WPT) systems can significantly increase the charging speed. However, there is the problem of system transmission efficiency degradation due to the change of equivalent load impedance in the WPT system. The fuzzy PID algorithm is used to control the DC/DC duty cycle of the secondary side to realize the maximum efficiency tracking, which significantly improves the transmission efficiency compared with that of the traditional PID algorithm. First, the equivalent load impedance as a function of the system transmission efficiency in the LCC-S compensation topology is derived from circuit theory. Then, on this basis, the fuzzy control theory is utilized to regulate the output impedance of the system by controlling the DC/DC duty cycle of the secondary side to achieve maximum efficiency tracking. Finally, the simulation platform is built by MATLAB/Simulink for verification, which proves that the wireless power transmission system using fuzzy PID algorithm can realize the maximum efficiency tracking, and its maximum transmission efficiency can reach 93.10%, and the average transmission efficiency can reach more than 85%, which can realize the maximum efficiency tracking of WPT.

To address the issue of high energy storage costs in integrated energy systems (IES) and further refine the relationship between energy storage and carbon emissions, this paper focuses on retired electric vehicle batteries. It constructs a model that integrates a second-life battery energy storage system (SLBESS) into an IES to achieve low-carbon economic dispatch. Firstly, the paper establishes a charge-discharge power model for retired electric vehicle batteries. Based on this model, it further constructs an SLBESS model within the IES to fully utilize the residual value of retired batteries. Secondly, the paper traces the carbon flow distribution of the SLBESS and establishes a full life cycle carbon emission model. An economic benefit analysis of this model is conducted to evaluate its advantages in both economic and environmental aspects. Finally, a day-ahead rolling dispatch model for the IES incorporating the SLBESS is established and solved using the Model Predictive Control (MPC) method. This approach ensures the rationality of the dispatch plan and the low-carbon economic operation of the system, providing a feasible low-carbon solution for integrated energy systems. In summary, by constructing and analyzing the application model of the SLBESS in the IES, this paper not only offers new insights into addressing high energy storage costs but also contributes to achieving low-carbon economic dispatch.

To mitigate the limitations associated with traditional direct torque control for permanent magnet synchronous motor (PMSM), which include variable switching frequencies, high torque ripple, and low power factor. This paper introduces a direct torque control strategy that utilizes a variable reference magnetic flux amplitude. Building upon the foundation of three-level voltage vector modulation for direct torque control, the strategy combines the idea of zero direct-axis current in vector control of PMSMs to establish a reference stator flux assignment policy. In order to solve the problem of inaccurate flux and torque estimation caused by the change of motor parameters during operation, an estimator based on model reference adaptive system was proposed. Simulation results demonstrate that this strategy exhibits excellent dynamic and steady-state response performance, has higher efficiency compared to traditional direct torque control, and effectively mitigates neutral point potential drift in three-level inverters. The simulation results validate the effectiveness of the proposed method.

With the scale of pulse forming network expanding and the number of power modules increasing, a time sequence signal generator is limited by the number of channels, which shows the disadvantages in different application scenarios. To solve the problem of limited channel number of a signal generator, an expansion scheme is designed by adding another device to the existing generator, which realizes the cascade expansion of two signal generators and increases the maximum number of available channels. Aiming at the consistency of the integrated control and parameter setting of the two signal generators, the host computer software is developed with Qt Creator, two serial communication channels are set up to connect with the two sub-computer devices, and the output signals of the two devices are managed and controlled comprehensively. Aiming at the localization replacement of core components of time sequence signal generator, one of the devices uses domestic FPGA as the main control chip to complete the time sequence logic control design. Under the unified control of the host computer, the two time sequence signal generators can output the time sequence pulse signals according to the set parameters. When receiving software trigger signals from the host computer, the synchronization error between two devices is approximately 840 microseconds. However, establishing a hardware connection between the two devices significantly reduces this synchronization error to 20 ns when transmitting external trigger inputs from one device to another. This enhancement effectively facilitates cascading expansion of the two devices. For the discharge control of pulse forming network, the channel combinations of time sequence signal generator can be flexibly selected according to the number of power modules to ensure the normal operation of the system.

To address the issues of difficulty and low efficiency in recognizing the status of high voltage disconnectors, this study proposes a method for status recognition based on image enhancement and an improved neural network, using disconnector images obtained from video monitoring. In response to problems such as poor quality of original image, unclear features, and a lack of sample diversity, an image feature enhancement algorithm has been designed, which includes rotation and cropping, histogram equalization, bilateral filtering, and adding noise, to achieve key feature enhancement and expansion of small sample datasets. A shallow neural network has been designed with the addition of ECA (Efficient channel attention) module to construct an improved network ECA-CNN, and the impact of different parameter conditions on model performance has been studied. The experimental results show that the designed image enhancement algorithm can effectively improve image quality, highlight key features, and provide high-quality data support for the neural network model training; the proposed ECA-CNN model can further enhance the focus on key image features based on the image enhancement algorithm, achieving a recognition accuracy rate of over 97%.

The AC08 type auxiliary inverter of Shanghai metro train was made by ALSTOM. In recent years, because of long time running, failure often occurs. Therefore the AC08 type auxiliary inverter needs to be redesigned. Through the spot investigation and collecting information, AC08 type auxiliary inverter parameter is redesigned. In the end, by comparing the test data with the original machine such as slow discharge waveform, fast discharge waveform, full load voltage and current waveform, the results show that home-grown AC08 type auxiliary inverter can meet the design standards of the inverter and can achieve a good replacement for the original machine.