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Table of Content

    30 June 2024, Volume 0 Issue 6
    Overview
    New Energy Transformer Standardization System Status and Suggestions and Measures
    HE Dongsheng, YANG Haijiang, HE Fawu, LUO Haiao, LU Jianjun, WANG Jixiang
    2024, 0(6):  1-7.  doi:10.16628/j.cnki.2095-8188.2024.06.001
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    The current situation of China’s new energy transformer standard system is systematically analyzed. The suggestions for further development are put forward. By investigating the database of national standard information public service platform, the standardization system status of photovoltaic, wind power and power electronic transformer are introduced in detail. The study found that despite the rapid development of new energy power generation, the standardization construction of transformers is relatively lagging behind, facing challenges such as lack of standards, slow updating and insufficient international integration. In order to deal with these problems, it is recommended to strengthen the work of multi-party participation in the formulation of standards, promote the docking of domestic and foreign standards, regularly update existing standards, and strengthen the training of standardization talents. These measures will help promote the standardization process of new energy transformers, promote technological progress and industrial upgrading, and provide support for China's green energy transition.

    Research & Analysis
    Research on Characteristics of AC Series Fault Arcs Based on Holo-Hilbert Spectral Analysis
    WU Ziran, HAN Yan, CHEN Chong
    2024, 0(6):  8-16.  doi:10.16628/j.cnki.2095-8188.2024.06.002
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    To solve the problem of extraction and analysis of alternative-current series arc fault characteristics, an analysis methodology that applies iterated masking empirical mode decomposition (itEMD) for current signal decomposition to obtain multi-layer intrinsic mode functions (IMFs) is proposed, and Holo-Hilbert transform(HHT) is utilized to represent high-dimensional amplitude-modulation-and-frequency-modulation (AM-FM) spectra, so that the high discriminative characteristic spectra of series arc faults can be achieved. The arc fault current signals are acquired under seven masking load modes in accordance with GB/T 31143—2014, and arc fault characteristics under different conditions are investigated by the proposed methodology. The presented study is of significant theoretical importance to the development of arc fault detection techniques.

    Influence Analysis of Temperature on Transient Electric Field of Converter Transformer
    LI Qian, GAO Youhua, FENG Xiaoxue, ZHANG Mingyang
    2024, 0(6):  17-24.  doi:10.16628/j.cnki.2095-8188.2024.06.003
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    The nonlinear characteristics of oil-paper insulation are not considered in the traditional transformer insulation design. The finite element method is used to couple electromagnetic field, temperature field and other multi-physical fields for the simulation calculation, focusing on the study of the conductivity of oil-paper composite insulation with the temperature nonlinear changes in the transient electric field distribution of the converter transformer valve-side winding end of the law and features.The effect of oil and insulating pressboard conductivity ratio on the valve-side electric field is studied. The results show that when considering the temperature-conductivity nonlinear characteristics, the electric field distribution at the valve-side terminal of the converter transformer is more concentrated, the distortion phenomenon is significant. And with the increase of the conductivity ratio, the electric field distribution on the valve side terminal is becoming increasingly concentrated. The high field strength values are distributed in the oil gap of the insulating pressboard at the terminal of the valve-side winding. The proposed research provides the reference for transformer insulation design.

    Research on Collaborative Optimization Method of Hot,Cold,Gas and Electric Loads in Multi-source Microgrid System
    HU Min, ZHANG Yuewei
    2024, 0(6):  25-30.  doi:10.16628/j.cnki.2095-8188.2024.06.004
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    For multi-load multi-source microgrid systems, energy management and collaborative control are one of the keys to ensuring reliable operation of the system. A collaborative optimization method with the minimum operating cost and minimum carbon emission of the system as joint optimization goals is proposed. The mathematical model for the working characteristics of each key equipment in the system is establised,and the Yalmip optimization toolbox in MATLAB is used to calculate the operation status of each key equipment. Typical load data in winter are used as model input for the simulation example. The simulation results show that the constructed collaborative optimization model can meet the optimal operation of the microgrid in a demand response environment. The simulation results verify the accuracy and effectiveness of the model.

    Electrical Design & Discussion
    Design of Miniaturized Magnetic Coupled VRM Based on Magnetic Powder Core
    ZHANG Binyi, YANG Qixin, MAO Xingkui
    2024, 0(6):  31-36.  doi:10.16628/j.cnki.2095-8188.2024.06.005
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    In response to the large volume problem of the traditional voltage regulation modules (VRM)coupling inductance using ferrite magnetic cores, the magnetic powder cores with higher saturation magnetic density are used as the magnetic core materials to reduce the volume of magnetic components. The design scheme and process for VRM coupling inductance based on magnetic particle cores are proposed. Finally, based on the design parameters, a magnetic coupled VRM prototype is built. The current density of the prototype module reached 0.5 A/mm2, the total height of the inductor is only 5 mm, and the performance is good. The proposed scheme and design process are verified to be correct and effective through the practical examples. The miniaturization and low cross-section of VRM coupled inductors can be achieved.

    Comparative Study on Single Pole Arc Extinguishing Capacity of Isolation Switches Under Different Usage Categories
    CHEN Xianzhuo, SUN Jiankun, ZHANG Senlin, ZHOU Yingzi, YAN hua
    2024, 0(6):  37-41.  doi:10.16628/j.cnki.2095-8188.2024.06.006
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    With the continuous advancement of photovoltaic and energy storage system technology, the voltage has been raised to the mainstream of 1 500 V, and the multi pole series connection is usually used to meet the demand for continuous voltage increase, resulting high cost, large volume, and certain limitations in the use category of existing DC isolation switch products. Therefore, a discussion is conducted on the operating conditions of DC isolation switch products, analyzing the differences in expected current waveforms under different time constants, proposing an improved arc extinguishing chamber structure, and analyzing the experimental results caused by the differences in arc extinguishing capacity of isolation switch products under different usage categories, providing new insights for enhancing the applicability of switch products in voltage systems that are continuously being upgraded.

    Evaluation & Prediction Technology
    Research on SOC Estimation of Lithium Battery Based on PSO-BP-UKF Algorithm
    LI Yang, SHI Zhengang
    2024, 0(6):  42-48.  doi:10.16628/j.cnki.2095-8188.2024.06.007
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    The state of charge (SOC) of lithium batteries is one of the core of quality management of lithium batteries. Based on effective SOC estimation is also necessary to ensure the safe and efficient operation of lithium batteries, A method for estimating the SOC of lithium batteries is proposed, which uses particle swarm algorithm (PSO) to optimize the backpropagation(BP) neural network as the observed value of the unscented Kalman filter(UKF). The proposed PSO-BP-UKF algorithm is compared with the GA-BP-UKF algorithm and the BP algorithm using FUDS operating condition battery test data from the University of Maryland. Taking the test results in 25 ℃ environment, the maximum deviation of PSO-BP-UKF algorithm is within 3.17%, the average error is within 6.44%, and the root-mean-square deviation is within 0.002 5, which is significantly improved than both GA-BP-UKF algorithm and BP method, and shows that the proposed algorithm is the effective and practical.

    Online State of Charge Estimation of Lithium-ion Battery Based on Improved Extended Kalman Filter Algorithm
    CUI Xiaodan, WU Jialong, DENG Kui, WANG Yanpin, FENG Jiaqi, LI Yajie
    2024, 0(6):  49-58.  doi:10.16628/j.cnki.2095-8188.2024.06.008
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    Lithium-ion batteries have been widely used in the field of energy storage power stations due to their high energy density, low self-discharge rate and low pollution. To solve the accurate prediction of various states of lithium-ion batteries, a second-order RC equivalent circuit model is first built, and then the parameters of the model are identified by using the forgetting factor recursive least squares (FFRLS) method. A joint SOC-SOH estimation method based on adaptive extended Kalman filtering (AEKF) algorithm is proposed, and the method is compared and verified under different battery conditions. Experimental results show that compared with the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), the proposed method can improve the accuracy and computational efficiency of SOC and SOH prediction, and has certain practical value.

    Research on Reliability Evaluation Method for Safety Related Relays of Urban Rail Vehicles Without Failure Data
    DUAN hongliang
    2024, 0(6):  59-63.  doi:10.16628/j.cnki.2095-8188.2024.06.009
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    In practical application, the safety-related relays for urban rail vehicles generally do not fail, making it difficult to analyze and evaluate the distribution of their life using common methods. Two methods are proposed for estimating the reliability of relays in the absence of failure data. One method involves using non-parametric methods to transform the problem of estimating the distribution parameters into a binomial distribution under unknown distribution conditions, in order to estimate the lower confidence limit of reliability. The other method assumes unknown shape parameters of the Weibull distribution and uses engineering experience to estimate the lower confidence limit of reliability. The feasibility and effectiveness of the proposed methods are demonstrated through example calculations, and the calculation errors are compared and analyzed. The application of this approach can effectively evaluate the reliability level of relays under actual operating conditions, providing the assurance for the safe and reliable operation of vehicles.

    Feature Selection Method Based on VarianceThreshold-GARFECV
    MA Jiachen, GAO Song, WANG Lei
    2024, 0(6):  64-69.  doi:10.16628/j.cnki.2095-8188.2024.06.010
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    In view of the existence of redundant fault characteristic variables and non-strongly correlated variables in the initial feature subset of active distribution network risk, a feature selection method based on VarianceThreshold-GARFECV is proposed. The proposed method combines the variance threshold and the recursive feature cancellation cross-validation(RFECV) technology based on genetic algorithm, which can effectively select the optimal feature set. Experimental results show that the proposed method can screen and select the initial feature set of distribution network fault risk, and eliminate the characteristic variables with weak correlation and redundancy, so as to reduce the complexity of distribution network data, avoid overfitting, and increase the interpretability of the model, with high accuracy and stability.

    Application
    Research and Application of Intelligent Anti-Misoperation Technolgy for Substation Switching Operation Based on Artificial Intelligence
    HU Xinyu, YU Haipeng, HE Zhi, ZHAO Miaomin, XING Songyao, ZHANG Jinwei
    2024, 0(6):  70-79.  doi:10.16628/j.cnki.2095-8188.2024.06.011
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    In response to the current lack of effective error prevention verification methods and low level of intelligence in operation tickets, a knowledge graph based intelligent error prevention technology for substation switching is proposed by combining deep reinforcement learning algorithms. Firstly, the data such as power grid equipment topology and scheduling error prevention regulations is utilized to constructe a physical entity graph and an error prevention semantic graph of the equipment, and a scheduling knowledge graph is automatically fused to form. Then, based on intelligent error prevention algorithms, a graph of error prevention regulations is constructed to automatically generate the optimal switching operation sequence that complies with the error prevention regulations, and the intelligent error prevention verification is achieved. Finally, the practicality of knowledge graph intelligent error prevention, the performance of deep reinforcement learning, and the efficiency of intelligent error prevention are analyzed through examples. The results show that the proposed method has certain advantages in improving the efficiency and accuracy of intelligent error prevention for switching.