bluuebunny/crossref_metadata_2025_split huggingface dataset:
Facile synthesis of NiCo2 O4/rGO nanowire array electrodes for supercapacitor cathodes
Authors: Dong Chen , Wei Mingrui , Yang Lan , Liu Yihui 
Published: March 2024

Abstract
In this study, NiCo2O4/rGO nanowire arrays (NWAs) were effectively synthesized, and these arrays were subsequently employed as components in supercapacitors. The phase structure of the materials was analyzed using X-ray diffraction spectroscopy, and the morphology of the materials was observed by scanning and transmission electron microscopy. By comparing with NiCo2O4 nanowire arrays without graphene oxide, it was found that the surface of NiCo2O4 arrays grown directly on nickel foams had a large number of accumulations, whereas the surface agglomerations of NiCo2O4/rGO nanowire arrays complexed with reduced graphene oxide were significantly improved. The NiCo2O4/rGO electrode with improved agglomeration phenomenon shows better performance. The specific capacitance of NiCo2O4/rGO NWAs is 2311 F·g-1 at 1 A·g-1 and remains at 1211 F·g-1 even at 50 A·g-1. In addition, the capacitance retention of this material could reach 83.5 % after 3,000 cycles at 10 A·g-1, demonstrating excellent multiplicative performance and cycling stability.
Wind power anomaly data detection based on unsupervised methods
Authors: Zhang Hao , Tang Qingfeng , Xu Du , Li Xiaofei 
Published: March 2024

Abstract
During the actual operation of the wind turbine, a large number of abnormal data will be generated due to environmental or human factors, which will have a great impact on the condition assessment and output prediction. In order to make wind energy a reliable source of energy, it is very important to establish an efficient and accurate wind power detection model. Therefore, it becomes essential to identify abnormal data for a more precise evaluation of wind turbine performance. Based on the data mining clustering technology K-means algorithm, this paper introduces an unsupervised abnormal wind power detection algorithm combining the variational autoencoders (VAE) model. The focus of this abnormal wind power detection method is primarily on assessing the reconstruction error, which, in turn, generates an abnormality score for wind power data. This score is then used to determine the presence of abnormal wind power data. Finally, the wind power data in 2021 is tested.
Research on distributed photovoltaic power prediction method based on reinforcement learning
Authors: Wang Chengjing , Zhang Haitao , Chen Zhenxing 
Published: March 2024

Abstract
The distributed photovoltaic power prediction is of great significance for reasonably adjusting and optimizing the power generation plan in the dispatching system. When using machine learning algorithms to construct photovoltaic power prediction models, there are usually problems such as poor prediction accuracy under default hyperparameters and high cost of human experience parameter adjustment experiments. Therefore, a reinforcement learning algorithm based on the long short-term memory network model (SARSA-LSTM) is proposed. Firstly, the reinforcement learning SARSA algorithm is used to tune the hyperparameters of LSTM automatically. Then, the optimal hyperparameter combination is used for regression prediction of photovoltaic power. The experiment compared the model results under default hyperparameters, Bayesian optimization, and grid search optimization hyperparameters. The results showed that the SARSA-LSTM proposed in this paper has better training efficiency and prediction performance compared to other models, which can meet the needs of practical prediction applications.
Application of magnetic flux leakage method in the crimping inspection of carbon fiber conductor
Authors: Zhang Hang , Du Zhiye , Liu Yazhi 
Published: March 2024

Abstract
Compared with steel core aluminum strand wire, carbon fiber composite core wire has many excellent characteristics such as large flow capacity, good heat resistance, light weight, but its mechanical properties are poor, and the unqualified crimping quality is easy to lead to wire breakage accidents, which greatly affects its popularization. For this reason, a scheme for the detection of crimping defects of carbon fiber composite mandrel based on magnetic leakage method is proposed. Firstly, the finite element analysis model of the clamping fixture was established, and then the magnetic pole distance k and radial air gap n of the magnetic leakage testing device were explored. Based on the signal-to-noise ratio under the two typical defect conditions of fracture and low pressure, the most suitable excitation structure parameters of the magnetic leakage device were obtained. The results show that when k=55mm and n=3.5mm, the signal-to-noise ratio of MFL detection device reaches the best effect. The research results are of great significance to the quality inspection of compacts of carbon fiber composite mandrel.
Combined navigation system for substation inspection robot based on DGPS/DR multi-sensor fusion
Authors: Yan Yu , Yu Xi , Liao Jianbin , Liu Liangyu , Gong Jie , Yang Yingwei 
Published: March 2024

Abstract
To realize the routine inspection work of the capacitor tower inspection operation robot on the capacitor tower in the substation, and to guarantee the accuracy and safety of the robot’s movement in the substation, a multi-sensor combination navigation system and the corresponding Kalman fusion filter are designed. Combined with the overall structure of the substation and the working environment of the inspection robot, the navigation and positioning requirements of the robot are analyzed and compared, and the multi-sensor combination positioning technology using a combination of DGPS, attitude sensors and velocity sensors is determined. The Kalman fusion filter based on the constant velocity model is used to fuse the positioning information of multiple sensors, and more accurate and reliable navigation information is obtained compared with the single-sensor positioning system. According to the working environment of the substation, an outdoor planar robot mobile navigation experiment is carried out to collect the positioning information of multiple sensors and carry out data fusion processing to verify the accuracy and robustness of multi-sensor combination navigation and positioning.
Protection adaptability analysis method for photovoltaic grid-connected generating system
Authors: Chen Yongxin , Liu Zhichang , Yang Zengli , Yin Xianggen , Wang Jing , Zhang Kanjun , Li Hengxuan , Yao Wei 
Published: March 2024

Abstract
Inverter power sources such as photovoltaic inverters and SVG have unique fault characteristics compared to traditional synchronous motors due to their unique power generation methods, circuit topology, and low-voltage traversal control strategies. The power grid faces various adverse effects due to the ongoing expansion of photovoltaic power station (PV power station) capacity. How to comprehensively analyze the impact of photovoltaic power stations above 1000 MW on power grid relay protection has become a problem. Therefore, a protection adaptability analysis method for photovoltaic grid-connected generating systems is proposed, which is suitable for engineering analysis before the connection of large-capacity PV power stations to ensure the safety of the power system. And it is found that current differential protection exhibits better adaptability than distance protection.
AC-DC breakdown characteristics of oil-paper insulation at low temperature
Authors: Zhang Jinfeng , Han Guozheng , Hao Lingyan 
Published: March 2024

Abstract
New energy sources such as wind energy are mainly distributed in low temperature areas such as high altitude and high dimensionality in inland China, which has higher requirements for the low-temperature insulation characteristics of power equipment. This poses higher demands for the low-temperature insulation capabilities of power equipment. However, the existing research on the low temperature breakdown characteristics of oil-impregnated paper is limited. In this study, the authors constructed an AC-DC combined power supply and a specialized low-temperature breakdown testing platform. Various oil-impregnated paper samples with different moisture contents were prepared. The paper investigated the AC-DC breakdown characteristics of these samples under low-temperature conditions, focusing on the effects of temperature, moisture content, and DC component on the breakdown strength. The findings serve as a valuable design reference for the application of oil-impregnated power equipment in low-temperature environments.
An accelerated modelling method of full-bridge modular multilevel converter considering dead-time
Authors: Pan Keying , Jing Hang , Xu Jianzhong , Li Fucun , Zhang Yan , Sun Yuntao 
Published: March 2024

Abstract
To avoid short-circuits of the same side switching of power converters, the dead time is of significance in the pulse trigger gating signal for full bridge modular multilevel converter (FB-MMC). However, the previous equivalent models use the binary resistance switching model to equivalent the switching state which is impossible to simulate the switching with dead time, and the detailed model (DM) with higher levels is time-consuming and inefficient in electromagnetic transient (EMT) simulation. To address this problem, based on the state-space averaging method, a speed-up average value model (AVM) of FB-MMC considering dead time is proposed. Firstly, the working state of FB-MMC is obtained through analysing the switching states with dead time and is classified into three cases according to the capacitor. Secondly, derived from state-space equation, the three cases are integrated into a unified model by introducing the duty cycle, and then the equivalent controlled source is used as the interface circuit between the external grid and capacitor. Finally, a 49-level two-terminal MMC-HVDC system consisting of FB-MMC is constructed in PSCAD / EMTDC simulations, showing that the proposed AVM compared with DM has high accuracy and operation efficiency.
Fault diagnosis and analysis of a 110 kV transformer
Authors: Gao Yong , Wang Jie 
Published: March 2024

Abstract
This paper aims to provide valuable insights and assistance for ensuring the safe operation of a 110 kV main transformer by conducting an in-depth analysis of tap changer breather oil leakage defects. By employing transformer testing, disassembly analysis, and other methods, this study successfully identifies and prevents the possibility of transformer failure. The analysis reveals that the deformation of the transformer winding is caused by insufficient short-circuit resistance, which leads to the deformation of the medium-voltage windings under the continuous action of electrodynamic forces during near-area short-circuit currents. Near-area short-circuits are a significant contributing factor to transformer failures. Therefore, it is recommended to enhance operation and maintenance management for older main transformers and optimize protection settings to reduce the risk of near-area short-circuit failures, thus ensuring the safe and stable operation of the main transformer.
Finite control set model-free predictive current control of permanent magnet synchronous motor
Authors: Zou Xinhong , Yang Kai , Zhang Zhengchang , Wu Di , Zheng Licheng , Gao Yue , Luo Cheng , Xiong Fei , Luo Yixiao 
Published: March 2024

Abstract
This thesis proposes finite control set model-free predictive current control (FCSMFPCC) algorithm of permanent magnet synchronous motor (PMSM). To address issue of degraded performance during motor operation due to parameter mismatch, a model-free predictive current control arithmetic is devised, which utilizes ultra-local model (ULM) of PMSM. This proposition takes sum of known and sealed disturbances of the system as an unknown quantity, and uses sliding mode observer (SMO) to take stock of sealed quantity. To address the issue of operation delay in predictive control, a two-step method is used to make up for the system. When using price function to choose the first-rank voltage vector, vector selection optimization link is added, which effectively simplifies the algorithm while optimizing the inverter switching action. The simulation outcomes highlight the advantages of the described control algorithm in terms of better dynamic response performance and stronger robustness.
Modeling and simulation of three-level DC/DC converters of high voltage wide range PI control
Authors: Zhang Haoran , Zuo Dongsheng , Li Yang 
Published: March 2024

Abstract
The three-level DC/DC converter is widely used in various applications, including electric vehicle charging stations, portable power supplies, and photovoltaic power generation. The mathematical models of input voltage, output voltage, and duty cycle of IGBT switch tube are established by analyzing the different operating modes of IGBT switch tube under PWM control. To validate the accuracy of the mathematical models, a simulation model can be built in MATLAB virtual environment, and a proportional-integral (PI) controller can be utilized to implement a hybrid closed-loop control strategy, where the current serves as the inner loop and the voltage as the outer loop. Such a control scheme will help to verify the feasibility of the mathematical models.
Research on transformer fault intelligent diagnosis technology based on improved random forest algorithm
Authors: Zhou Linwei , Xu Ding , Yuan Yining , Wang Lingjia 
Published: March 2024

Abstract
Transformer oil can dissolve a certain amount of gas, which can provide an important basis for transformer fault diagnosis. The relationship between the characteristic amount of dissolved gas in transformers and the type of transformer fault was analyzed, and the main influencing factors were extracted. We studied a transformer fault diagnosis method based on the improved random forest algorithm and combined it with the identification requirements of abnormal data in multiple parts of transformers. We improved the random forest from four aspects: dataset construction, bootstrap sampling, decision tree generation, and multi-node voting. We established an improved random forest diagnosis model with oil chromatogram feature gas ratio as the characteristic parameter and analyzed different input parameter combinations. The effectiveness of improving the random forest diagnosis model under different training times was compared with various machine learning methods. The experimental results show that the diagnostic accuracy of the improved random forest diagnostic model is significantly improved compared to other machine learning methods.
Research on piezoelectric simulation characteristics based on ALN piezoelectric thin film structure
Authors: Zhang Jiajia , Wang Jia , Tan Wanqing , Zhang Xinru 
Published: March 2024

Abstract
AlN piezoelectric thin films possess exceptional performance and find extensive applications in the fields of underwater acoustic communication and hydroacoustic sensing. To enhance the output voltage values of AlN piezoelectric thin films and optimize their structure, comprehensive simulations and analyses were carried out by using COMSOL on both circular and square film configurations. These investigations specifically focused on examining the impact of dimensional variations on resonance frequency and output voltage, as well as exploring the relationship between vibration frequency and output voltage. The findings revealed that by employing an appropriate cavity radius, increasing the thickness of the thin film can effectively enhance the output voltage. However, if the thickness surpasses 1.5 μm, the output voltage will gradually decline. Notably, the square film exhibited a significantly higher output voltage measurement of 2158 pm compared to the circular film.
Minimum current stress control strategy for three degree of freedom three-phase dual active bridge DC-DC converter
Authors: Zhang Xin , Wang Fusheng 
Published: March 2024

Abstract
Compared to single-phase dual active bridge (1p-DAB) DC-DC converters, three-phase dual active bridge (3p-DAB) DC-DC converters have advantages such as high single machine power, high power density, small filtering capacitance, and are more suitable for high-voltage situations. Therefore, they have good application prospects in DC transmission and industrial high-power DC-DC converters. However, under traditional single-phase shift (SPS) control, especially in the low power range, there is a large reactive current and severe soft switch loss. This article adopts an asymmetric modulation strategy for its larger reactive power, which reduces its reactive power in the low power range with more degrees of freedom and improves the efficiency of power transmission. Taking current stress as the optimization objective, the KKT algorithm is used to solve, and the corresponding analytical solution is ultimately obtained. Finally, a simulation is built by using MATLAB software to verify the feasibility of the proposed solution.
Full power range DAB unified ZVS control strategy based on low current RMS
Authors: Zhang Chuanqi , Wang Fusheng , Cheng Weizheng 
Published: March 2024

Abstract
Inductive current RMS and soft switching are important performance indexes of dual active bridge DC-DC converter (DAB). This paper proposes a new optimal control strategy for the soft switching range based on the optimization of the effective value of the inductor current. This control strategy restricts the inductor current during switch action, ensuring a significant extension of the soft switching range across the entire power range, reducing switch losses, and achieving the accurate effective value of current, thereby further enhancing the efficiency of the DAB converter. Meanwhile, a new modulation method is proposed to achieve thermal balance between bridge arms. Finally, a simulation model is built and verified using Matlab.
Research on the multi-parameter-based detection scheme for current transformers
Authors: Zhang Fuzhu , Han Xiao , Liu Yu , Xu Tianshi , Zhao Zishu , Ma Weina 
Published: March 2024

Abstract
Oil-immersed current transformers are commonly used as a type of electrical equipment, but they may experience some faults and defects during actual operation. When detecting these faults and defects, the usual detection object is temperature, which is a single detection quantity and easily leads to misjudgment. This article introduces typical defects in oi-limmersed current transformers, conducts simulation analysis, studies the temperature field changes of current transformers when three typical defects occur, and studies the relationship between temperature and pressure to determine the feasibility of using temperature and pressure as the detection object, to improve the accuracy of detection. The results show that by using temperature and pressure as measurement values of a new detection method, the problem of single measurement parameters that cannot determine the internal condition of the equipment can be solved. By monitoring changes in temperature and pressure in real-time, misjudgment due to external factors can be avoided based on the relationship between temperature and pressure.
An improved soft-switching inverter to eliminate pre-charge current
Authors: Ni Hongquan , Dong Yixiang 
Published: March 2024

Abstract
To address the current stress problem brought on by the auxiliary resonant pole inverter’s pre-charge state, this paper gives an improved auxiliary circuit based on the original inverter. The improved circuit avoids a pre-charge state by adding auxiliary capacitors to form a resonant branch. In contrast to the original inverter, this inverter lowers the current stress on both the auxiliary and primary switches by resolving the pre-charge state’s current stress issue. As a result, the inverter’s losses are decreased, which raises the system’s efficiency. The working principle of this inverter is given in the paper. After a comparison and analysis of the inverter’s pre-charge state, an experiment is used to confirm the device’s viability.
Comparison and analysis of power and torque performance of PMSM with different rotor structures
Authors: Wang Hao , Tian Rixin , Li Changchao , Zhang Zongsheng 
Published: March 2024

Abstract
In this paper, according to the double reaction principle of permanent magnet synchronous motor (PMSM), the power, torque, and power angle characteristics are derived theoretically. Four motor models of tangential type, radial type, V-type, and U-type PMSM are established by finite element software. The magnetic flux density of the motor is analyzed in detail. At the same time, performance indicators such as efficiency, power factor, and air gap power of permanent magnet synchronous motors were calculated and evaluated, further improving the accuracy and credibility of the research. Based on the comparative study of the analysis results, the advantages and disadvantages of electromagnetic performance corresponding to different rotor structures are obtained, providing the design basis of PMSM.
A method for testing partial discharge characteristics of switch cabinet based on improved particle swarm algorithm
Authors: Yu Hongqi , Huang Hui , Xu Ruibo , Mo Weixin 
Published: March 2024

Abstract
In the current operational environment of the switch cabinet, the presence of mixed-frequency signals poses interference from white noise to partial discharge detection, resulting in suboptimal detection efficiency and accuracy. Therefore, this study explores a method for testing the partial discharge characteristics of switch cabinets based on an improved particle swarm algorithm. This novel approach involves signal processing of partial discharge in a switch cabinet, feature extraction based on the particle swarm algorithm, and feature output for partial discharge detection. Experimental comparisons demonstrate that the new detection method significantly enhances detection efficiency and ensures the accuracy of results, meeting the operational requirements of substations.
A load-side resource aggregation method based on Minkowski Sum
Authors: Xiao Fei , Cui Yong , Zhu Jingkai , Qiao Yining , Li Zhaoyu , Ai Qian 
Published: March 2024

Abstract
In the context of high penetration of renewable energy in new power systems, load-side resources have good regulation potential to improve system flexibility. In order to fully exploit the regulation potential of load-side resources, the power regulation range and regulation cost of load-side resources need to be aggregated first. Based on the establishment of a unified model of the scheduling feasible region of the load-side resources, the computation of the Minkowski sum of the feasible region of the load-side resources is realized through the linear superposition of the maximally inner-approximated feasible region. The decomposition scheme of the instructions of the aggregator and the computation method of the equivalent cost function of the aggregator are proposed. The effectiveness of the proposed aggregation method is verified by arithmetic simulation.