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3rd IEEE China International Youth Conference on Electrical engineering, CIYCEE 2022

作者： Zhao, Sifeng Ye, Caiyong Wan, Shanming State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China Dunshi Magnetic Energy Technology Co. Ltd. Shijiazhuang050000 China

ISBN: (数字)9781665477321

ISBN: (纸本)9781665477321

The low switching-to-fundamental frequency ratio (SFFR) control strategy is adopted when the high-speed flywheel energy storage system (FESS) is used in urban rail transit system to provide network stability and regenerative braking energy recovery. The performance of the current control will be deteriorated or even the system instability may occur under low SFFR strategy. In this paper, a Low SFFR based direct voltage control strategy is proposed according to the unique characteristics of the high-speed FESS. The feasibility of the proposed method is analyzed, and the control parameters and the midpoint voltage balance method are designed. The effectiveness of the current stability and midpoint voltage balance is verified through simulations and experiments. © 2022 IEEE.

关键词： Light rail transit

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L-arginine loading porous PEEK promotes percutaneous tissue repairthrough macrophage orchestration

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Bioactive Materials 2024年第10期40卷 19-33页

作者： Tong Zhao Xingdan Liu Zhuangzhuang Chu Jing Zhao Dongya Jiang Xiaohua Dong Ziyi Lu Kelvin WKYeung Xuanyong Liu Liping Ouyang Laboratory of Key Technology and Materials in Minimally Invasive Spine Surgery Tongren HospitalShanghai JiaoTong University School of MedicineChina Hongqiao International Institute of Medicine Tongren HospitalShanghai Jiao Tong University School of MedicineShanghai200336China State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai200050China School of Chemistry and Materials Science Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of Sciences1 Sub-lane XiangshanHangzhou310024China Shenzhen Key Laboratory for Innovative Technology in Orthopaedic Traum1 Guangdong Engineering TechnologyResearch Center for Orthopaedic Trauma RepairDepartment of Orthopaedics and TraumatologyThe University of Hong Kong Shenzhen HospitalShenzhenChina

Infection and poor tissue repair are the key causes of percutaneous implantation failure. However, there is a lackof effective strategies to cope with due to its high requirements of sterilization, soft tissue healing, andosseointegration. In this work, L-arginine (L-Arg) was loaded onto a sulfonated polyetheretherketone (PEEK)surface to solve this issue. Under the infection condition, nitric oxide (NO) and reactive oxygen species (ROS) areproduced through catalyzing L-Arg by inducible nitric oxide synthase (iNOS) and thus play a role in bacteriasterilization. Under the tissue repair condition, L-Arg is catalyzed to ornithine by Arginase-1 (Arg-1), whichpromotes the proliferation and collagen secretion of L929 and rBMSCs. Notably, L-Arg loading samples couldpolarize macrophages to M1 and M2 in infection and tissue repair conditions, respectively. The results in vivoshow that the L-Arg loading samples could enhance infected soft tissue sealing and bone regeneration. Insummary, L-Arg loading sulfonated PEEK could polarize macrophage through metabolic reprogramming,providing multi-functions of antibacterial abilities, soft tissue repair, and bone regeneration, which gives a newidea to design percutaneous implantation materials.

关键词： Polyetheretherketone Macrophage orchestration Sterilization Tissue repair

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Inverse Design of electromagnetic Induced Transparency Metamaterials Based on Generative Adversarial Network

Inverse Design of Electromagnetic Induced Transparency Metam...

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Electrical engineering (CIYCEE), IEEE China International Youth Conference on

作者： Xingyu Zhou Peishuai Tian Yanqi Hu Qitai Sun Yongqian Xiong State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

The unique properties of electromagnetic induced transparency (EIT) metamaterials have caused a lot of concern in the field of terahertz wave regulation, but the traditional design methods of metamaterials have the problems of long design cycle and high trial and error cost. Applying deep learning method to the inverse design process of terahertz metamaterials can greatly reduce the design complexity, so that the EIT metamaterial structure can be quickly designed according to the requirements. In this paper, a generative adversarial network (GAN) model for EIT metamaterial structure design is constructed, which realizes the mapping relationship between target spectrum and metamaterial structure parameters. The proposed GAN model can accurately predict structure parameters of the EIT metamaterial according to the target spectrum, and the error between the generated and the real parameters is less than 1μm. Moreover, by introducing the fuzzy processing, the proposed GAN model can accurately generate multiple sets of metamaterial structure according to the same target spectrum, which provides more options for designers. This model offers a novel and efficient design method for EIT metamaterials.

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Fault Current Analysis of DFIG Considering Multi-time Scale Protection and Control under Asymmetrical Voltage Dips

Fault Current Analysis of DFIG Considering Multi-time Scale ...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Ziyu Yang Yingbiao Li Jiabing Hu State Key Laboratory of Advanced Electromagnetic and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

The characteristics of asymmetrical short-circuit current of doubly fed induction generators (DFIGs) are different from those of synchronous generators (SGs). With the increase in the quantity and capacity of DFIGs, the analysis and calculation of the asymmetrical short-circuit current of DFIGs are vitally important for the safe and stable operation of modern power systems. Under asymmetrical fault conditions, protection circuits and control strategies of DFIGs have multi-time scale characteristics and the equivalent circuit will change accordingly. Moreover, the negative-sequence internal voltage of DFIG is controllable, which makes the analysis more complex. This paper proposed an analytical calculation method of the asymmetrical short-circuit fault current and the characteristics of fault current are analyzed considering the multi-time scale control and protection. Finally, the proposed expression is validated in MATLAB/Simulink.

关键词： Voltage fluctuations Short-circuit currents Doubly fed induction generators Protective relaying Stators Synchronous generators Power systems

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Lifecycle Synergistic Prelithiation Strategy of Both Anode and Cathode for High-Performance Lithium-Ion Batteries

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advanced Energy Materials 2025年第0期

作者： Zhong, Wei He, Renjie Peng, Linfeng Liu, Wei Peng, Jiayue Zhu, Haolin Xiang, Jingyu Cheng, Shijie Xie, Jia State Key Laboratory of Materials Processing and Die & Mould Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China School of Chemistry and Chemical Engineering Huazhong University of Science and Technology Wuhan430074 China

Prelithiation is recognized as an effective technology for addressing the depletion of active lithium, but conventional methods are constrained by their reliance on singular lithium replenishment mechanisms and limited functionality. Herein, a synergistic and comprehensive lifecycle prelithiation technology is introduced as applicable to both anode and cathode. For anode prelithiation, highly reactive biphenyl lithium is leveraged as a lithium replenishing agent, supplemented by functional additives, ethoxy(pentafluoro)cyclotriphosphazene (PFPN) and fluoroethylene carbonate (FEC), to generate a robust SEI enriched with Li3N, LiF, Li3P and Li2O. This approach not only compensates for the initial active lithium loss but also fortifies the structural integrity of the SEI. For cathode prelithiation, the high-capacity lithium replenisher Li2C2O4 and Li2C4O4 comprising B, N double-doped carbon loaded Mo2C-W2C (Mo-W@BNC) heterogeneous catalysts is employed, which exhibits superior catalytic performance in facilitating the release of lithium. The exceptional efficient liberations of lithium are achieved at discharge voltages of 3.78 V and 4.14 V for Li2C2O4 and Li2C2O4, respectively. The prelithiation for both anode and cathode mitigates the initial active lithium loss by 22.6%. Moreover, a singular activation during subsequent usage contributes an additional 0.8 mAh cm−2 of active lithium, achieving a capacity retention of 99.3% after 250 cycles at 0.5C. © 2025 Wiley-VCH GmbH.

关键词： Lithium-ion batteries

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Simulation analysis on the capacity occupancy of reactive power equipment under dc bias of transformers 11

Simulation analysis on the capacity occupancy of reactive po...

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11th Annual Meeting of CSEE Study Committee of HVDC and Power Electronics, HVDC 2022

作者： Xie, Zhicheng Deng, Jun Zhou, Haibin Lin, Xiangning Zhang, Jinyin Li, Zhengtian Wei, Fanrong Extra-High-Voltage Power Transmission Company of China Southern Power Grid Guangzhou China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781839538568

When the high voltage direct current (HVDC) system operates in ground-return-mode (GRM), ground return current with high amplitude up to several thousand amperes will penetrate into the earth. Such DC current will flow through AC lines with star-connecting and grounding at both ends, and intrude the neutral point of the transformers of the line in turn. Therefore, it will increase the reactive power consumption of the transformer and occupy the capacity of reactive power compensation equipment, as well as threaten the security and stability of the power grid. A simulation model of typical substation system operating under DC bias is established, based on which the quantitative analysis of the variation of the excitation current and the condition of reactive power consumption for transformers under different bias current is carried out. The analysis results show that the excitation current is seriously distorted and the reactive power consumed increases sharply under DC bias current with high amplitude, which occupies a large amount of reactive power compensation equipment capacity. Therefore, extremely adverse impact can be brought out on the reactive power balance and the voltage regulation of the power grid. In addition, the results of this paper are of significant reference value for researches on the reactive power characteristics of DC bias as well as the support capability of short-circuit voltage under DC bias. © 2222 IET Conference Proceedings

关键词： Reactive power

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Machine learning application to predict the electron temperature on the J-TEXT tokamak

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Plasma Science and technology 2021年第8期23卷 47-52页

作者： Jiaolong DONG Jianchao LI Yonghua DING Xiaoqing ZHANG Nengchao WANG Da LI Wei YAN Chengshuo SHEN Ying HE Xiehang REN Donghui XIA International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics State Key Laboratory of Advanced Electromagnetic Engineering and TechnologySchool of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074People's Republic of China Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205People's Republic of China

The reliability of diagnostic systems in tokamak plasma is of great significance for physics researches or fusion *** some diagnostics fail to detect information about the plasma status,such as electron temperature,they can also be obtained by another method:fitted by other diagnostic signals through machine *** paper herein is based on a machine learning method to predict electron temperature,in case the diagnostic systems fail to detect plasma *** fully-connected neural network,utilizing back propagation with two hidden layers,is utilized to estimate plasma electron temperature approximately on the *** input parameters consist of soft x-ray emission intensity,electron density,plasma current,loop voltage,and toroidal magnetic field,while the targets are signals of electron temperature from electron cyclotron emission and x-ray imaging crystal ***,the temperature profile is reconstructed by other diagnostic signals,and the average errors are within 5%.In addition,generalized regression neural network can also achieve this function to estimate the temperature profile with similar *** electron temperature by neural network reveals that machine learning can be used as backup means for plasma information so as to enhance the reliability of diagnostics.

关键词： neural network plasma electron temperature J-TEXT tokamak

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Optimal Real-time Operation Strategy of Microgrid with Power-to-Hydrogen Device: An ADP Approach 5

Optimal Real-time Operation Strategy of Microgrid with Power...

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5th International Conference on Energy, Electrical and Power engineering, CEEPE 2022

作者： Lu, Xun Zhong, Zhiyao Xue, Xizhen Wu, Yunyun Ai, Xiaomeng Fang, Jiakun China Southern Power Grid Company Limited Guangdong Power Grid Corporation Guangzhou China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan China

ISBN: (纸本)9781665479059

This paper proposes an Approximate Dynamic Programming (ADP) approach for obtaining the optimal real-time operation strategy of microgrid with power-to-hydrogen (P2H) device. Firstly, the real-time operation model of microgrid with P2H is established, then a piece-wise linear function based approximate dynamic programming is proposed to solve the operation model. With the direction of the slope update and training policies under various training scenarios, the proposed ADP approach can obtain the approximate optimal real-time operation strategies to cope with uncertainties. Case studies verify the superiority of the proposed ADP approach compared with Model Predictive Control approach (MPC). © 2022 IEEE.

关键词： Training Power engineering Uncertainty Simulation Microgrids Linear programming Real-time systems

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Inverse design of electromagnetically induced transparency (EIT) metamaterials based on autoencoder with reconstruction error

Inverse design of electromagnetically induced transparency (...

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Electrical engineering (CIYCEE), IEEE China International Youth Conference on

作者： Peishuai Tian Xingyu Zhou Yanqi Hu Yongqian Xiong State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

In the paper, we design a new deep learning (DL) network to analysis and design the electromagnetically induced transparency (EIT) metamaterials. The network is divided into two parts: dimensionality reduction reconstruction network and inverse design. The dimensionality reduction reconstruction network mainly deals with high-dimensional input data. In the inverse design, we combine the convolutional neural network (CNN) and long short-term memory (LSTM) to predict the EIT metamaterial structure. The inverse design has reduced the mean square errors (MSE) on the validation set to 0.0032 and predict the structure parameters within the error of 0.26 µm, which are better than other reports. Besides, we avoid the overfitting problem and one-to-many problem to some extent. By comparing the spectra of real and predicted parameters on the validation set, we are confident that the network will pave a new path for designing EIT metamaterials.

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Assessment on Flexibility Demand of Grid-Connected Wind Farms Based on Copula Analysis 3

Assessment on Flexibility Demand of Grid-Connected Wind Farm...

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3rd IEEE China International Youth Conference on Electrical engineering, CIYCEE 2022

作者： Yuan, Wang Suhua, Lou Meng, Zhang Guojun, Bao Huiyu, Zhang Mingshan, Mo State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China State Grid Fujian Electric Power Co. LTD. Fuzhou350003 China

ISBN: (数字)9781665477321

ISBN: (纸本)9781665477321

According to the characteristics of large-scale wind power cluster access, this article establishes an assessment method on flexibility demand of grid-connected wind farms based on correlation analysis. Firstly, considering that the meteorological conditions of adjacent new energy stations are similar, and the wind speed and solar intensity have strong correlation characteristics, the cluster correlation of new energy sources is analyzed. Then, based on the Copula theory, the analysis method of the nonlinear correlation of new energy output considering the effect of new energy cluster is studied, and the output of new energy cluster is modeled. Finally, based on the output model of the new energy cluster, the flexibility demand of large-scale grid-connected new energy is modeled, and the flexibility demand of power system is analyzed. © 2022 IEEE.

关键词： Correlation methods

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