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25 February 2024, Volume 44 Issue 1

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Academician Message

CHEN Xiaohong

2024, 44(1):  0-0. 

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Researches and Tests

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Review of Key Technologies in New Power System Based on Artificial Intelligence Empowerment

DUAN Junfeng, LI Chenkun, YAO Wenxuan, GUO Siyuan

2024, 44(1):  1-10.  doi:10.3969/j.issn.1008-0198.2024.01.001

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Based on the important role of artificial intelligence technology in promoting the intelligence of new power systems, this paper summarizes the current application status, technical challenges, and future development directions of artificial intelligence in new power systems. Firstly,the paper introduce the characteristics and requirements of the new power system. Then, the paper discusses the key application areas of artificial intelligence in new power systems, including the security, stability and control of large power grids, integrated collaborative analysis of source network, load storage, intelligent operation, inspection and management of power systems, as well as active distribution networks and microgrids. Finally, the paper analyzes the technical challenges faced by artificial intelligence in the new power system and proposes relevant suggestions.

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Vibration Characteristics Analysis and Optimal Design of Oil-Immersed Transformer Based on Finite Element Method

YUAN Fating, YAN Zhiwei, CAO Hao, JI Ruiqing, TANG Bo

2024, 44(1):  11-17.  doi:10.3969/j.issn.1008-0198.2024.01.002

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According to the electrical and structural parameters of the oil-immersed transformer, the circuit magnetic field simulation model is established based on the finite element simulation software. Based on the experimental measurement results and the characteristic parameters identified by J-A hysteresis model, the magnetic property model of the material is obtained. The simulation model of transformer magnetic field-structure field is established to obtain the distribution of magnetic field and stress around the transformer. Taking the calculated core Maxwell force, magnetostrictive force and winding Lorentz force as excitation, the transformer vibration displacement considering the magnetic properties of the material is calculated. The vibration displacements at different positions of the core are extracted, and the distribution rules of the vibration characteristics of the core are obtained. On this basis, in order to reduce the vibration of the oil-immersed transformer, the finite element method is combined with the time-experimental design method, and the optimal parameters are obtained by adjusting the winding parameters of the transformer. The results show that the maximum vibration displacement of the transformer before and after optimization is 6.12 μm and 5.71 μm respectively, and the optimization method significantly reduces the vibration of the transformer, which has important guiding significance for the vibration and noise reduction of oil-immersed transformer.

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Study on Composite Silicone Rubber Aging Based on TG-FTIR

CHEN Tiantian, ZHA Fanglin, LIU Yiyi, WAN Tao, CHEN Bo

2024, 44(1):  18-23.  doi:10.3969/j.issn.1008-0198.2024.01.003

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Composite silicone rubber insulators have been widely used in overhead transmission lines, but their aging has always been an important problem. In order to investigate the aging process of the composite silicone rubber, the aging process of the composite silicone rubber samples is accelerated under the salt spraying environment. Scanning electron microscope is used to observe micro-morphology changes of the surfaces during the aging process of the samples.The thermos-gravimetric(TG) and Fourier transform infrared (FTIR) spectroscopies are used to analyze the changes of the component contents and functional groups during the aging process of the specimens.The TG-FTIR technology is used to analyze the pyrolysis products of the composite silicone rubber samples. The results show that after salt spray aging the pyrolysis products of the samples contain water vapor, CO₂ and a little organosilicon.These phenomena indicates that salt spray aging will hydrolyze the hydrophobic groups in the side chains of the samples, such as CH₃Si and (CH₃)₂Si, and produce hydroxylated groups, such as silicone hydroxyl (OHSi)and carbon hydroxyl (OHC), which will affect the hydrophobicity of the samples and reduce the pollution resistance.

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Design and Simulation of Power Supply-Traction-Hybrid Energy Storage System for Urban Rail Trains

ZHU Zhiqiang, WANG Xin, QIN Bin

2024, 44(1):  24-31.  doi:10.3969/j.issn.1008-0198.2024.01.004

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In order to further improve the recovery and utilization efficiency of urban rail train regenerative braking energy, a structure of urban rail train traction power supply system based on distributed ground hybrid energy storage is designed through the analysis of system functional requirements, and the power supply network, train traction and energy storage system models are established. Moreover, aiming at the problem that low pass filtering leads to a large amount of power exchange between lithium batteries and supercapacitors, a stepped power allocation method with supercapacitor compensation is proposed.This method has small computation and strong real-time performance,and can avoid the internal power circulation of the hybrid energy storage system. Combined with the proposed model and strategy, MATLAB Simulink is used to simulate.The results validate that the energy utilization efficiency of the hybrid energy storage system is improved by 1.39%, the voltage regulation rate is increased by 12.75% and the energy saving rate is increased by 6.72%.

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Research on Electric Shock Identification Based on Feature Overlap Analysis and Bayes-Random Forest

WU Cong, LIU Mouhai, ZHOU Can, HUANG Rui, TONG Haixin, LU Jin

2024, 44(1):  32-37.  doi:10.3969/j.issn.1008-0198.2024.01.005

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In response to the difficulty in identifying biological electric shocks caused by feature aliasing in low-voltage distribution systems, a Bayesian-random forest based method for identifying electric shock caused by characteristic overlap in low-voltage distribution systems is proposed. Firstly, the current waveforms of five types of electric shocks, including a non-living organism control group, are analyzed to study the overlap of the same shock characteristics in different categories. Secondly, the Bayesian optimization algorithm is used to optimize the hyper-parameters of the random forest model. The random forest is fitted with real samples using bagging, describing the operation of the ensemble identification mechanism and the specific implementation process of the method. Furthermore, the method is validated on 136 802 test samples containing five types, achieving an overall accuracy of 96.276%. Finally, a comparison with existing methods demonstrates the superiority of the proposed method in electric shock identification.

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Neural Network Prediction Methods of Short-Term Peak Load Based on Multi-Information Fusion

XU Shunkai, ZHU Jiran, TANG Haiguo, DENG Wei, HUANG Zhao, ZOU Changchun

2024, 44(1):  38-44.  doi:10.3969/j.issn.1008-0198.2024.01.006

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In order to reduce the complexity of load data and improve prediction accuracy, an neural network model based on multi information fusion for short-term peak load is proposed on this article. The Pearson correlation coefficient is selected to analyze the closeness between weather information such as holidays, temperature, and humidity. In proposed model considering the key weather information fusion, the input load parameters is optimized,a new dataset of the neural network model is reconstructed, and overfitting of the neural networkis avoided,and the accuracy of short-term peak load prediction is improved. A simulation example of peak load forecasting proves that the proposed method is more effective in improving the accuracy of short-term peak load forecasting compared to the single enhanced decision tree model and neural network model that do not consider multiple information fusion.

New technology and Application

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Research on Optimization Selection of Multi-Objective Control Parameters for Modular Multilevel Converter Under Asymmetric Network Voltage

ZHOU Hanliang, XIA Xiangyang, LI Runwu, GUO Yu, YI Rui

2024, 44(1):  45-52.  doi:10.3969/j.issn.1008-0198.2024.01.007

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In order to solve the problem that it is difficult to determine the adjustment parameters in the multi-objective protection control, this paper introduces the weight factors of active power fluctuation and AC current fluctuation, and constructs a linear weight expression. In order to obtain the optimal weight factor, this paper analyzes in depth the restrictions of modular multilevel converter(MMC)system safe operation conditions on weight selection,establishes a weight optimization selection model. Based on the above analysis, this paper proposes a multi-objective coordinated control strategy for MMC, which aims to suppress active power fluctuations and coordinate the imbalance of AC current. The strategy considers the maximum allowable current of the system and the maximum allowable voltage fluctuation of the bridge arm capacitor, and does not require additional control elements to suppress overcurrent and bridge arm voltage overvoltage. The simulation experiment demonstrates the feasibility and effectiveness of the proposed strategy.

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Image Classification Method Based on Deep Learning for Inspection Unmanned Aerial Vehiclesin Transmission Line

YANG Hongzhao, XI Yanhui, XIANG Sheng, XU Zhikang

2024, 44(1):  53-58.  doi:10.3969/j.issn.1008-0198.2024.01.008

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Due to the irregularity of point cloud data, the classification accuracy of point cloud data feature values is difficult to meet the requirements of transmission line inspection. Therefore,a lidar point cloud classification method based on graph signal processing is proposed. When processing irregular transmission line image signals, the method can directly generate feature values from the original point data, thereby improving classification accuracy. In order to validate the proposed method, the algorithm is validated through physical simulation, and the results show that the classification accuracy in the image could reach 90%.

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Optimal Operation Strategies of New Power System Aimed at Renewable Energy System Consumption

LIU Shuo, MA Zhaoxing, LIU Jinxin, QIAN Baoshan, WANG Ruihua

2024, 44(1):  59-66.  doi:10.3969/j.issn.1008-0198.2024.01.009

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By defining the active power flow coefficient based on the output power of traditional generators, the unified scheduling of wind farm-pumped storage stations is carried out. The power consumption strategy of wind power is determined by the ratio of this coefficient to the output power of the wind farm. A pumped storage station power generation optimization scheduling model is established with the objective function of minimizing the fluctuation of traditional generator output power. The system is optimized using the African wild dog algorithm with Gaussian mutation operator, and a dynamic iteration step is added to the algorithm to accelerate the iteration speed in the early stage and enhance the calculation accuracy in the later stage. By comparing simulation results, the effectiveness and feasibility of the optimization operation strategy proposed in the article in system operation have been confirmed.

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Optimal Operation Method of Shared Energy Storage Considering Distribution Network State

YAO Jun, LU Jun, LIAO Yipu, WANG Zhenyu, LIANG Enmin, GONG Gangjun

2024, 44(1):  67-76.  doi:10.3969/j.issn.1008-0198.2024.01.010

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Considering the influence of the access of shared energy storage on the distribution network, this paper proposes an optimal operation method of shared energy storage considering the state of the distribution network. Firstly, the operation model of shared energy storage is described, and the operation model of shared energy storage power station, the stability model of distribution network and the cost model of user electricity are constructed by unifying energy storage resources through shared energy storage operators. Then, a two-objective optimization model considering the state of distribution network is constructed. The game between distribution network and shared energy storage power station is completed based on the concept of multi-objective optimization, and the power consumption expectation is met based on Euclidean distance method. Finally, simulation based on 33-node distribution system proves the superiority of this paper. The numerical example shows that the proposed method can effectively reduce the operation cost of shared energy storage power station, make the power grid operation more stable, and reduce the cost of electricity consumption.

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Press Connection Pipe Detection Method for Transmission Line in Field Complex Background Based on Improved Convolutional Network

ZOU Dehua, ZHANG Hongwei, QIAO Lei, ZHAO Liyuan, JIANG Wei

2024, 44(1):  77-84.  doi:10.3969/j.issn.1008-0198.2024.01.011

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In order to improve the detection accuracy and speed of convolutional networks, and reduce the model under miscellaneous scenes, a visual detection method of press connection pipe under complex field background based on wavelet analysis and improved lightweight neural network is proposed. The image noise is removed using wavelet analysis and the lightweight GhostNet model is used in the backbone network. In addition, omni-dimensional dynamic convolution is introduced to enhance the backbone feature extraction capability, depth separable convolution is used to reduce the model complexity, improved convolutional block attention module(CBAM)is embedded to improve the model accuracy, and K-Means ++ algorithm is used to cluster the anchor frame size and linear transformation to accelerate the convergence of the target frame. CIoU-NMS is used to improve detection speed and accuracy. The actual test results show that compared with YOLOv4 model, the improved YOLOv4 lightweight model size is significantly reduced by 199.7 MByte with the accuracy is only lost by 2.98%, the detection speed is increased by 3.4 Hz to 33.9 Hz and the edge deployment efficiency index is better. Therefore the improved lightweight network model achieves the best balance among detection accuracy, model size and detection speed. Finally, the detection results in the field with complex background and multiple scenes also show that the algorithm can well meet the detection requirements in practical engineering tasks, and has sound engineering practicability.

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Interleaved Series Solid State Circuit Breaker of DC Distribution Network

ZHOU Qianfan, WAN Dai, HE Zhixing, LI Zongjian

2024, 44(1):  85-93.  doi:10.3969/j.issn.1008-0198.2024.01.012

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Facing the fault characteristics of DC system, DC circuit breaker that can quickly and effectively cut off the fault current is of great significance to improve the power supply reliability of the DC distribution network. This paper proposes an interleaved series solid state circuit breaker. The topology interleaves multiple internal units in series is proposed to improve the overall withstand voltage capability. Each internal unit is composed of multiple normally-on SiC JFET in series. The circuit topology has strong scalability. The fast response, dynamic and static voltage balance of the series switch are effectively realized through the double-layer voltage sharing network. Based on sofware LTspice, a simulation of a 4.5 kV/20 A solid-state circuit breaker is constructed, and the simulation results show that its rated shutdown time is only 80ns, verifying the feasibility of the proposed ISSSBS topology.

Experience and Discussion

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Optimization Strategy of Electric Vehicle Charging Load Based on Stage-Sharing Tariff Response

XU Wenzhe, FANG Baling, ZHANG Qifei, LI Wei, LIU Hao

2024, 44(1):  94-100.  doi:10.3969/j.issn.1008-0198.2024.01.013

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Aiming at the charging load optimization problem of electric vehicles, this paper proposes a charging load optimization strategy for electric vehicles based on stage-sharing tariff response. The strategy establishes an electric vehicle charging load model and simulates the load variation of uncontrolled charging of electric vehicles by Monte Carlo algorithm, taking into account the electric vehicle load factor. On the basis of the elasticity matrix of peak-valley leveling tariffs, the stage time-sharing tariff model is established by subdividing different equal time periods, and the optimization model of time-sharing tariffs for electric vehicles is constructed with the optimization objectives of minimizing the mean square deviation of the total charging costs of the users and the total load of the system, and the improved chaotic multi-objective genetic algorithm is used to solve and optimize the model. Finally, the effectiveness and economy of the strategy are verified by the experimental comparison results, where the total user charging cost and the total system load mean squared deviation are reduced by 4091 yuan and 37.151 MW respectively, compared with the traditional time-sharing tariff scheme under the given data conditions.

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Research on Hoisting Scheme of Special-Shaped Components in UHV Tower Assembly Process

JIN Yuzhu, REN Caiheng, GUI Hehuai, ZHU Guanmin, WANG Shuang, MA Tianyuan, TANG Bo

2024, 44(1):  101-105.  doi:10.3969/j.issn.1008-0198.2024.01.014

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In order to provide technical support for the formulation of the hoisting scheme of special shaped components in the erection of UHV transmission towers, this paper takes a large-span single circuit cup-shaped spanning tower as the research object, and uses the structural analysis software Tekla Structure to model some special-shaped components of the tower. The gravity center position of the special-shaped component is calculated, and the hoisting scheme of the special-shaped component is proposed. In order to verify the feasibility of the scheme, the finite element analysis is carried out by using ANSYS software. The analysis results show that the strength of the steel pipe at the counterweight after the component is split meets the requirements, and the hoisting scheme is safe and feasible. It can improve the efficiency of the tower construction ,ensure the safety of the construction,and provide reference for the formulation of the hoisting scheme of the special-shaped components of the UHV transmission tower.

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Study on Core Component Selection of Smart Meter Metering Module Based on TOPSIS of Combination Weighting of Criteria Importance Though Intercrieria Correlation and Coefficient of Variation

SHEN Liman, CHEN Hao, ZENG Weijie, CHEN Hong, WANG Zhi

2024, 44(1):  106-112.  doi:10.3969/j.issn.1008-0198.2024.01.015

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Smart energy meter is the core metering terminal in smart grid, and the stability of its performance is determined by the performance of its internal core components. However, the current option methods for core components are based on subjective experience selection, and the selection results lack objectivity. Therefore, this paper proposes a technique for order preference by similarity to ideal solution selection method based on the combination weighting of criteria importance though intercrieria correlation (CRITIC)and coefficient of variation (CoV) method, which reduces the influence of the CRITIC method on the comparative strength of indicators by introducing the CoV method to represent the comparative strength of indicators, and improves the objectivity and accuracy of the selection results. At the same time, considering the functional attributes of the three core components of the smart energy meter metering module, namely, high-precision analog-to-digital converter, high-speed microcontroller unit processor and voltage reference chip, corresponding functional selection indexes are proposed. By comparing with the results based on the electrical parameter test, the feasibility of the proposed method and indexes applied to the selection of core components for smart energy meter metering module is proved.

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Study on Effect of Typical Seasonal Variation on Grounding Impedance of Ground Network in Mengxi Region

WU Yanbin, CHE Chuanqiang, QIN Chunxu, YANG Wenliang

2024, 44(1):  113-118.  doi:10.3969/j.issn.1008-0198.2024.01.016

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The seasonal change will change the soil resistivity value, and the change of soil resistivity will have an impact on the impedance value of the grounding device. On the basis of soil resistivity monitoring of a certain region, the impedance changes of different types of grounding earthing devices buried in this field area are studied. The results show that the correlation analysis, throughout the year soil resistivity and temperature changes in the region are strongly negatively correlated, showing obvious seasonal changes in characteristics. When designing regional grounding network greatly affected by seasonal change,the methods can be used increasing the area of the ground network, ground network depth and the use of small permeability, good flexibility of the graphite grounding device to reduce the seasonal changes in the value of the impact of the grounding impedance,to provide reference for the design of grounding grids in areas greatly affected by seasonal changes.

Faults and Analysis

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Research on Deep Auto Encoding Support Vector Data Description Model for Power Equipment Anomaly Detection

GENG Bo, PAN Shuhui, DONG Xiaoxu

2024, 44(1):  119-127.  doi:10.3969/j.issn.1008-0198.2024.01.017

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In response to the problem of insufficient ability of deep auto encoding support vector data description model to distinguish some anomalies of power equipment, this paper proposes deep auto encoding support vector data description model with self-supervised and mixture-of-experts.The multiple self-supervised transformation datasets is constructed to simulate potential unknown anomalies, and the self-supervised classification and mask reconstruction tasks is introduced to learn more discriminative representations. In addition, the encoder is transformed into a mixture-of-experts structure, and the data is allocated to different expert sub-modules for professional learning, making the abnormal decision boundary clearer. Experimental results from four public data sets and three power plant equipment data sets prove the effectiveness of self-supervised learning and mixture-of-experts.

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Fault Diagnosis of High Voltage Circuit Breakers Based on Support Vector Machine of Improverd Sand Cat Swarm Optimization Algorithm

HUANG Wei, ZHANG Lian, WANG Shibin, ZHAO Na, JI Hongyu

2024, 44(1):  128-135.  doi:10.3969/j.issn.1008-0198.2024.01.018

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In order to analyze and diagnose the status of high-voltage circuit breakers more accurately, a multi-strategy improved sand cat swarm optimization (ISCSO) algorithm is proposed to optimize the fault diagnosis method of support vector machine (SVM). Firstly, sand cat swarm optimization(SCSO) algorithm is improved through various improvement strategies to enhance the algorithm's global search ability, local search ability, and global balance ability. Two different types of test functions are used to test the performance of ISCSO, verifying its stronger convergence and optimization ability. Then, ISCSO is used to optimize SVM and establish a fault diagnosis model. Next,complete ensemble empirical mode decompasition with adaptive noise energy entropy is used to extract features from vibration signals and construct a feature sample set. Finally, the extracted feature sample set is input into the ISCSO-SVM model for fault diagnosis of high-voltage circuit breakers. The experimental results show that the diagnostic accuracy of this method reaches 96.29%. Compared with the other three models, it has been proven that this method has higher accuracy, and better stability.

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Analysis and Discussion on Ground Wire Icing Disaster for a Certain UHV DC Line

CHAO Rui, ZHANG Wei, LI Yangyang, CUI Hanjun

2024, 44(1):  136-139.  doi:10.3969/j.issn.1008-0198.2024.01.019

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In view of the shortage of icing observation data at the location of transmission line ice disaster, taking the typical fault of ground wire icing and disconnection of a ±800 kV UHV DC line as an example, this paper attempts to comprehensively analyze the meteorological elements, on-site survey, image data and on-site icing investigation, and select the appropriate calculation method to estimate the icing magnitude in combination with the icing shape, so as to provide a simple calculation method for the rapid determination of icing magnitude in the area with insufficient icing data. The feasibility of this estimation method is verified by the inverse calculation of icing magnitude by using the sag gap between conductor and ground wire under different icing conditions.

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Optimization of Cold End System Operation for 1 000 MW Ultra Supercritical Unit

MEI Hailong, ZENG Haibo, DUAN Wangquan, LI Ming, DU Bingqiang

2024, 44(1):  140-144.  doi:10.3969/j.issn.1008-0198.2024.01.020

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In order to balance the influence of the cold end system on the generating power and plant consumption rate of the thermal power unit and improve the economy of the unit, a circulating pump operation optimization method based on real-time regulation is proposed. The influence of circulating cooling water flow on condenser pressure is analyzed, and the power consumption change of circulating water pump under different operation modes and the slight power increase curve of unit under 950MW, 750MW and 500MW load are obtained through field test. By actively changing the frequency of variable frequency pump, the change of condenser pressure is monitored in real-time.Combined with the change of circulating pump power consumption and the unit's slightly increased power curve to calculate the unit's net output change, the best operating frequency of variable frequency pump is found through the circulating pump operation optimization test of the unit. The test results show that the method can obtain the optimal operating frequency of the variable frequency pump under different operating loads of the unit. It shows that the proposed method can effectively improve the economy of the unit.