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Optimal Scheduling of Battery Charging-Swapping Systems for Distribution Network Resilience Enhancement

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SSRN 2022年

作者： Sui, Quan Li, Feiyu Wu, Chuantao Feng, Zhongnan Lin, Xiangning Li, Zhengtian Wei, Fanrong State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Hubei Wuhan430074 China

When offshore-island renewable distribution system (OIRDS) encounters multiple failures in case of extreme weather, battery charging-swapping system (BCSS) is a promising solution to reduce the power outage loss and enhance resilience of the OIRDS. However, extreme weather (such as heavy rain) may affect the logistic speed, resulting in a non-integer-hour battery schedule time among stations. Although rounding the time as integer hours could match the scheduling step size, result errors would be caused. To solve the problem, a novel OIRDS resilience enhancement strategy is proposed. First, the impacts of the rainfall, solar radiation, and wind speed on the renewable generation and battery transfer time are analyzed. On this basis, a dual unit commitment method is presented to coordinate the scheduling step and non-integer-hour battery transfer time. Moreover, an optimal OIRDS resilience enhancement model integrating decisions of the battery schedule and network reconfiguration is presented based on a 1-hour scheduling step. This model is converted into a mixed-integer linear programming (MILP) problem and solved efficiently. Simulation studies on an IEEE-11 node distribution network indicate the proposed strategy is effective and beneficial. © 2022, The Authors. All rights reserved.

关键词： Charging (batteries)

Faraday Angle Prediction Based on 1-D Cnn on the J-Text Tokamak

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SSRN 2023年

作者： Chen, Yanqiu Gao, Li Shen, Chengshuo Chen, Zhongyong Tao, Qinlin Wang, Yuhan Lin, Weijie Zheng, Wei Yang, Zhoujun Chen, Zhipeng Pan, Yuan International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

The Faraday angle is an indispensable physical parameter to evaluate and reconstruct the current density profile which is imperative for advanced tokamak operation and physics study. The POLARIS system has been implemented on J-TEXT since 2012 for the measurement of the Faraday angle, this system occasionally encounters operational failures that result in the inability to provide measurements. So a deep learning model is trained to predict the Faraday angle when the POLARIS is unable to provide the measurement. The model is primarily based on a 1-D convolutional neural network (CNN) and is equipped with multiple convolutional paths that can accommodate various lengths of diagnostic data. The data of 100 shots were used to train the 1-D CNN model, and 30 shots were used to optimize the hyperparameters and select the model which performs best during the training process. The results on a test set of 30 shots show that the model obtains a satisfactory fitting effect. © 2023, The Authors. All rights reserved.

关键词： Neural network models

Low-temperature superplasticity of β-stabilized Ti-43Al-9V-Y alloy sheet with bimodalγ-grain-size distribution

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Journal of Materials Science & technology 2021年第36期95卷 225-236页

作者： Yu Zhang Shuai Chang Yuyong Chen Yuchao Bai Cuiling Zhao Xiaopeng Wang Jun Min Xue Hao Wang Department of Mechanical Engineering Faculty of EngineeringNational University of Singapore9 Engineering Drive 1Singapore 117575Singapore Department of Materials Science and Engineering Faculty of EngineeringNational University of Singapore9 Engineering Drive 1Singapore 117576Singapore State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin 150001China National Key Laboratory for Precision Hot Processing of Metals Harbin Institute of TechnologyHarbin 150001China

The superplasticity of Ti-43Al-9V-0.2Y alloy sheet hot-rolled at 1100℃was systematically investigated in the temperature range of 750-900℃under an initial strain rate of 10^(-4)s^(-1).A bimodalγgraindistribution microstructure of Ti Al alloy sheet,with abundant nano-scale or sub-micronγlaths embedded insideβmatrix,exhibits an impressive superplastic *** inhomogeneous microstructure shows low-temperature superplasticity with a strain-rate sensitivity exponent of m=0.27 at 800℃,which is the lowest temperature of superplastic deformation for Ti Al alloys attained so *** maximum elongation reaches~360%at 900℃with an initial strain rate of 2.0×10^(-4)s^(-1).To elucidate the softening mechanism of the disorderedβphase during superplastic deformation,the changes of phase composition were investigated up to 1000℃using in situ high-temperature X-ray diffraction(XRD)in this *** results indicate thatβphase does not undergo the transformation from an ordered L2;structure to a disordered A2 structure and cannot coordinate superplastic deformation as a *** on the microstructural evolution and occurrence of bothγandβdynamic recrystallization(DR)after tensile tests as characterized with electron backscatter diffraction(EBSD),the superplastic deformation mechanism can be explained by the combination of DR and grain boundary slipping(GBS).In the early stage of superplastic deformation,DR is an important coordination mechanism as associated with the reduced cavitation and dislocation density with increasing tensile *** DR can relieve stress concentration arising from dislocation piling-up at grain boundaries through the fragmentation from the original coarse structures into the fine equiaxed ones due to recrystallization,which further effectively suppresses apparent grain growth during superplastic *** the late stage of superplastic deformation,these equiaxed grains make GBS prevalent,which can effectively avoid intergranu

关键词： Titanium aluminides Hot-rolled alloy sheet Bimodal microstructure In situ high-temperature XRD Superplasticity

A Composite Current-Fed LLC Resonant Converter for Wide Input Voltage

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A Composite Current-Fed LLC Resonant Converter for Wide Inpu...

Smart Power & Internet Energy Systems (SPIES), International Conference on

作者： Caifeng Liu Shuang Liu Donghai Zhu Xu Yan Xudong Zou State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China State Key Laboratory of Advanced Electromagnetic Engineering and Technology China-EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan China

The LLC resonant converter is the most commonly used unidirectional isolated DC/DC converter. However, the gain adjustment range of conventional LLC resonant converters is limited and not suitable for applications with wide input voltage. In this paper, a C-LLC resonant converter topology suitable for wide input voltage range is obtained by improving the current-fed LLC resonant converter. The operational modes and stages of the C-LLC resonant converter employing the basic pulse width modulated + double phase shift modulation (PWM+DPS) are analyzed. Then an optimized modulation strategy for efficiency improvement is proposed by optimizing the soft switching range and current RMS values. Finally, a prototype is built to verify the analysis. The efficiency is improved by up to 5% when the optimized modulation strategy is adopted compared to the conventional LLC resonant conversion at voltage mismatch condition.

关键词： Phase modulation Energy Soft switching Prototypes Resonant converters Voltage Switches

A Positive and Negative-Sequence Equivalent Circuit Model for Linear Induction Machine Adapted to Urban Rail Transit

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IEEE Transactions on Transportation Electrification 2025年

作者： Guo, Yingcong Xu, Wei Ge, Jian Shangguan, Yongdao Xiao, Han Tang, Yirong Southwest Jiaotong University School of Electrical Engineering Chengdu610031 China Beijing100190 China University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing101408 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China

The equivalent circuit model is a crucial tool for estimating the performance of linear induction machines (LIMs), and it is widely used in design, optimization, etc. However, the conventional model which does not account for the asymmetrical current is not as precise in certain scenarios. Such asymmetrical current is caused by the inherent end effect in LIMs, which persists even when the machine is powered by a symmetrical voltage source. In this paper, a novel equivalent circuit model is proposed to enhance the precision of analyzing LIMs performance under asymmetrical current. Firstly, the relationship between current, back electro-motive force (EMF) and voltage is established by analyzing the positive and negative-sequence airgap magnetic field. Secondly, the excitation source is converted from symmetrical phase voltage to positive and negative-sequence current by solving the circuit constraint equation. Finally, a positive and negative-sequence equivalent circuit model is constructed and the LIM performance is further analyzed. The proposed model is thoroughly validated through comparison with other methods and experimental data. © 2015 IEEE.

关键词： Urban transportation

A Modular Multilevel Dc Active Power Filter Based on Optimal Parameter Design for the Cfetr N-Nbi Accelerator Grid Power Supply

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SSRN 2023年

作者： Zhang, Hongqi Ma, Shaoxiang Zhu, Bangyou Li, Zhiheng Du, Zhenchang Zhang, Ming Pan, Yuan International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

A DC active power filter (DAPF) based on modular multilevel converter scheme for the accelerator grid power supply (AGPS) in neutral beam injector system is proposed to reduce the DC bus voltage ripple of AGPS. This will help reduce the output voltage ripple of the AGPS at rated operating conditions, improve the focus state of the extraction beam, and reduce the occurrence of breakdown conditions. The scheme is special in that each module can compensate one frequency component of the ripple current, and the maximum switching frequency is not more than 4 times the ripple frequency. The electrical parameters of all DAPF modules (switching states and module capacitor voltages) are optimal values obtained through an optimal parameter design algorithm. In the process of applying the algorithm, two types of APF modules are distinguished. They have different switching frequencies and ripple suppression effects to adapt to different occasions. The simulation results show that each module can reduce the relative frequency component of the ripple by about 80% under the optimal parameters. Similar results are obtained by the 400V AGPS prototype and 20 V DAPF prototype. © 2023, The Authors. All rights reserved.

关键词： Power converters

Complex Power Quality Disturbance Classification Based on Fuzzy Transfer Field and DPN-17

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Complex Power Quality Disturbance Classification Based on Fu...

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

作者： Wu Jieting Huang Zhiwei Yuan Miao Xie Weilun Lu Zifeng Li Kaicheng Luo Yi Dongguan Power Supply Bureau of Guangdong Power Grid Co. Ltd. Dongguan China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798331530174

ISBN: (纸本)9798331530181

Disturbances of power quality in modern power systems tend to be complicated due to the diversification of electrical equipment and the complexity of equipment working conditions. Traditional classification methods are difficult to meet the classification requirement of multiple power quality disturbances (PQDs). In this paper, a hybrid power quality disturbance classification method based on fuzzy transfer field and DPN-17 is proposed. Fuzzy transfer field is a conversion scheme proposed to solve the confusion problem in the process of amplitude-dependent signal transformation in the existing mainstream dimension conversion methods. Fuzzy idea is used to blur the specific coordinates of signal points, and precisely encode the timing relationship and distribution of signal points, so that it can effectively encode the timing relationship and distribution information of signals. It can retain the features well in the process of downsampling; DPN-17 is implemented by referring to the shallow residual network model and using dual-path neural network modular fast combination stack. Simulation and experiments show that the proposed method can effectively solve the confusion problem of dimension conversion schemes, and can achieve accurate and rapid identification of complex power quality disturbances with an accuracy rate of 97.40%.

关键词： Employee welfare Accuracy Power quality Noise Neural networks Interference Mathematical models Robustness Timing Complexity theory

Fast Shapelet Learning for Power System Dominant Instability Mode Identification

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Fast Shapelet Learning for Power System Dominant Instability...

2021 International Conference on Power System technology, POWERCON 2021

作者： Zhang, Runfeng Shi, Zhongtuo Yao, Wei Huang, Yanhao Tang, Yong Wen, Jinyu Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan China China Electric Power Research Institute State Key Laboratory of Power Grid Safety and Energy Conservation Beijing China

ISBN: (纸本)9781665407373

Digital simulation is an essential part of supporting the safe and stable operation of power systems. One of the most crucial processes is to make the control decision table after a large amount of transient stability simulation. This process requires to be able to accurately distinguish between the transient (rotor angle) instability and short-term voltage instability. This paper proposes a fast shapelet learning method to extract features from the original voltage and rotor angle curves and then classify them through a machine learning (ML) model. Shapelet learning is a powerful data mining method, which can be used to extract hidden explainable information from power system time-domain simulation data. To overcome the huge time complexity of the shapelet transformation method, a genetic algorithm is applied to speed up the solution procedure. A case study is conducted on an 8-machine 36-bus system, and the simulation result indicates that the proposed method is with high explainability and fast learning speed. © 2021 IEEE.

关键词： Genetic algorithms

Iron Electrodeposition-Induced Yearly Degradation on Industrial Alkaline Water Electrolysis: Multiphysics Model and Economic Analysis

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SSRN 2024年

作者： Huang, Danji Xiong, Binyu Lu, Ang Ai, Xiaomeng Hu, Kewei Zhong, Zhiyao Fang, Jiakun Wen, Qunlei State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China School of Automation Wuhan University of Technology 122 Luoshi Road Hongshan District Hubei Wuhan430070 China

This paper quantifies the yearly performance degradation in industrial Alkaline Water Electrolysis (AWE), focusing on iron electrodeposition reaction (IER) as the primary degradation mechanism throughout the AWE lifecycle. The IER-induced degradation mechanism impacts hydrogen evolution reaction (HER) materials and membrane porosity, resulting in increased HER activation and membrane ohmic overpotential. To quantitatively assess the effects of IER on AWE performance, a multiphysics model is developed and experimentally validated, demonstrating a predictive accuracy within ±3% relative error. Notably, the model calculations highlight the initial linear slow growth of IER-induced performance degradation, followed by rapid voltage increase due to accumulated iron deposition in the later stages. The findings suggest that timely replacement of affected electrode material and membrane, along with optimized electrolyte management and lifecycle current density operation strategies, can enhance the economic viability of AWE systems. Additionally, the paper includes an economic analysis of operational and maintenance strategies, contributing valuable insights into optimizing the sustainability of industrial hydrogen production. This comprehensive approach offers valuable guidance for optimizing AWE systems in industrial applications. © 2024, The Authors. All rights reserved.

关键词： Economic analysis