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Annual IEEE Conference on Applied power Electronics Conference and Exposition (APEC)

作者： Fei Zhou D. Brian Ma Department of Electrical and Computer Engineering Integrated Power Electronics System Laboratory The University of Texas at Dallas Richardson TX USA

Monolithic GaN power IC has been regarded as the ultimate solution to unlock the full potential of the wide bandgap GaN technology for next-generation high-speed, high-efficiency and high-density power circuits. However, with scarce power device options, the current development of monolithic GaN power ICs faces severe design challenges. A critical example can be found in the design of one of the most important circuit modules – the voltage level shifter, which is the enabler to drive any kind of high-side power switch in a power circuit. To overcome this challenge, this paper proposes a new circuit structure and a novel operation concept of a dynamic floating voltage level shifter to reduce propagation delays, improve dynamic slew rates and attain superb dv⁄dt noise immunity for both speed and reliability improvements. Implemented on a 200V, 180nm, n-type only, GaN-on-SOI process, the proposed voltage level shifter only occupies a die area of 0.12mm 2 and achieves 2.81ns rising and 3.44ns falling propagation delays at room temperature with a slew rate of 100V/ ns.

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Analytic Mechanism for the Cumulative Effect of Wind power Fluctuations from Single Wind Farm to Wind Farm Cluster

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CSEE Journal of power and Energy systems 2022年第5期8卷 1290-1301页

作者： Gang Mu Fangze Wu Xiaoping Zhang Ziheng Fu Bai Xiao Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China Department of Electronic Electrical and Systems EngineeringSchool of EngineeringUniversity of BirminghamBirmingham B152TTU.K

The use of wind power is rapidly growing worldwide as a means of reducing carbon emissions for the energy *** has the world’s largest wind power installation and multiple large-scale wind farm clusters,each comprising dozens of wind *** the planning and operation of the power system,it is important to understand the power fluctuation characteristics of wind farm *** studies demonstrate that the relative power fluctuation of a wind farm cluster is less than that of a single wind *** this decreasing trend a random occurrence or does it have a regular pattern?This scientific question is addressed by investigating the mechanism of the cumulative effect of a wind farm *** this study,a cumulative model is proposed by examining the spatiotemporal relationships of wind power variations and wind farm *** gain function and critical cumulative frequency are defined as the foundations to analytically describing the cumulative *** investigating the cumulative effect mechanism,the relationship between power fluctuation and spatiotemporal parameters of the wind farm cluster are *** power fluctuation of a cluster can be predicted using the cumulative model even before it is completely *** mechanism of the cumulative effect is validated on the basis of the data of two actual wind farm clusters.

关键词： Analytic mechanism cumulative effect evolution regularity wind farm cluster wind power fluctuation

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A Conduction-Loss-Conscious 4-Level power Converter with Tri-Path Synchronous Rectification for High Step-Down DC-DC Conversion

A Conduction-Loss-Conscious 4-Level Power Converter with Tri...

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Annual IEEE Conference on Applied power Electronics Conference and Exposition (APEC)

作者： Jin Woong Kwak D. Brian Ma Department of Electrical and Computer Engineering Integrated Power Electronics System Laboratory The University of Texas at Dallas Richardson TX USA

Multi-level power converters today are highly desirable for high step-down DC-DC conversions but face a serious challenge due to the inherent limitations of topology and operation, which severely impacts efficiency. To combat this challenge, this paper proposes a new operation strategy - tri-path synchronous rectification (TSR) to reduce conduction loss in each discharge phase significantly, which is regarded as a dominant factor to efficiency. The TSR strategy is non-intrusive and can be virtually applied to any multi-level converters without interrupting the original converter operation. To demonstrate the design ideas, a 4-level TSR converter prototype is designed and tested. It down-converts a 48V power source to an output voltage programmable from 1V to 2V with a maximum load of 25A and a peak efficiency of 90.8%.

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A ΔIIN Self-Canceled SEPIC power Converter for EMI CISPR 25 Compliance

A ΔIIN Self-Canceled SEPIC Power Converter for EMI CISPR 25...

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Annual IEEE Conference on Applied power Electronics Conference and Exposition (APEC)

作者： Zhenda Fu Lixiong Du Jin Woong Kwak Fei Zhou D. Brian Ma Department of Electrical and Computer Engineering Integrated Power Electronics System Laboratory The University of Texas at Dallas Richardson TX USA

In an effort to comply with stringent electromagnetic interference (EMI) standards for automotive electronics applications, this paper introduces a new SEPIC converter topology with significantly reduced di/dt switching dynamics for conducted EMI suppression. The converter employs a unique T circuit network, consisting of a coupled inductor and an auxiliary LC branch, to self-cancel its input current ripple ΔI IN , thus minimizing associated di/dt. By doing so, the converter incurs no significant power density and efficiency penalties. Meanwhile, the converter requires no active control circuitry to ensure accurate ΔI IN cancelation, simplifying the design complexity. To demonstrate the converter topology and design ideas, a converter prototype is designed, which accommodates a wide input supply voltage range of 4.5V to 40V and delivers an output of 12V, with seamless buck-boost conversion operation. Operating at 400kHz, it delivers a maximum power of 42W and achieves a peak efficiency of 86.8%. For the step-up conversion with 5V V IN and 500mA load, the ΔI IN self-canceled SEPIC topology achieves 9.6dB peak EMI reduction at the fundamental frequency. For the step-down conversion with 1.5A load, it reduces the peak EMI by 20.4dB and 13.9dB at V IN of 24V and 40V, respectively, satisfying the CISPR25 Class 2 Standards.

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Development of Vehicle-to-Grid systemto Regulate the system Parameters of Microgrid

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Energy engineering 2022年第4期119卷 1261-1298页

作者： Om PrakashMahela Baseem Khan Rupendra Kumar Pachauri Power System Planning Division Rajasthan Rajya Vidyut Prasaran NigamLtd.Vidyut BhawanJapurIndia Department of Electrical and Computer Engineering Hawassa UniversityHawassaEthiopia Electrical Engineering Department School of EngineeringUniversity of Petroleum and Energy StudiesDehradunIndia

This paper proposes a vehicle-to-grid(V2G)system interfaced with a microgrid that is effective at regulating frequency on a microgrid over a 24-h cycle.A microgrid is designed and divided into four *** first component is a diesel generator,which is used to act as the base power *** second component consists of renewable energy(RE)power plants,which include solar photovoltaic(PV)and wind *** third component is a V2G *** last component is the load connected to the microgrid.A microgrid is designed to be of sufficient size to represent a community of one thousand households during the day period of low consumption in the spring or fall seasons.A hundred electric vehicles(EVs)are modeled as base models to realize a 1:10 ratio for cars to households,which indicates a possible scenario in the near *** analysis of the active power,reactive power,voltage,frequency,and current is carried *** is established that the proposed design of the V2G andmicrogrid effectivelymaintains systemparameters such as frequency and voltage within permissible limits with an error of less than 1%.Further,transient deviations in these parameters are limited to within 5%.A microgrid with V2G devices regulates the system frequency by mitigating load demand through coordinated control of conventional generation,solar PV plant generation,wind plant generation,power exchange with the microgrid network,and electric *** proposed microgrid and V2G are efficient for energy management and mitigation of intermittency and variability of RE power with improved *** in system parameters have been investigated by changing the operating scenario,and it has been determined that the error is limited to less than 5%.The study is effectively realized in the MATLAB/Simulink environment.

关键词： Microgrid electric vehicles vehicle-to-grid renewable energy PV wind

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Optimal Allocation of Distributed Synchronous Condenser for SSO Mitigation 12

Optimal Allocation of Distributed Synchronous Condenser for ...

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12th International Conference on Renewable power Generation, RPG 2023

作者： Han, Zijiao Jia, Qi Dong, Wenkai Na, Guangyu Su, Yuze Xie, Xiaorong State Grid Liaoning Electric Power Supply Co. Ltd. Shenyang China State Key Laboratory of Power System Department of Electrical Engineering Tsinghua University Beijing China

Weak grid connection is one of the main causes for the sub-synchronous oscillations (SSOs) of renewable power generation systems (RPGSs). In this paper, the allocation of distributed synchronous condensers (DSCs) is optimized to mitigate this kind of SSO. First, impedance model of the RPGS with DSCs integrated is established. Second, an optimization model for the allocation of DSCs to mitigate SSO is established. The objective function is to minimize the cost of the DSCs. The constraints include: 1) the satisfaction of the generalized Nyquist criterion under different operating conditions, and 2) the limitation on the capacity of the condenser. Finally, the optimal allocation problem for an example RPGS is solved by using the particle swarm optimization. The effectiveness of the optimized deployment of DSCs in mitigating SSO is verified with electromagnetic simulations. © The Institution of engineering & Technology 2023.

关键词： Electromagnetic simulation

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Data-driven Robust State Estimation Through Off-line Learning and On-line Matching

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Journal of Modern power systems and Clean Energy 2021年第4期9卷 897-909页

作者： Yanbo Chen Hao Chen Yang Jiao Jin Ma Yuzhang Lin State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electrical&Electronic EngineeringNorth China Electric Power UniversityBeijing 102206China School of Electrical and Information Engineering University of SydneySydney 2006Australia Department of Electrical and Computer Engineering University of MassachusettsLowellMA 01852USA

To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust state estimation (DDSE) method through off-line learning and on-line matching. At the off-line learning stage, a linear regression equation is presented by clustering historical data from supervisory control and data acquisition (SCADA), which provides a guarantee for solving the over-learning problem of the existing DDSE methods;then a novel robust state estimation method that can be transformed into quadratic programming (QP) models is proposed to obtain the mapping relationship between the measurements and the state variables (MRBMS). The proposed QP models can well solve the problem of collinearity in historical data. Furthermore, the off-line learning stage is greatly accelerated from three aspects including reducing historical categories, constructing tree retrieval structure for known topologies, and using sensitivity analysis when solving QP models. At the on-line matching stage, by quickly matching the current snapshot with the historical ones, the corresponding MRBMS can be obtained, and then the estimation values of the state variables can be obtained. Simulations demonstrate that the proposed DDSE method has obvious advantages in terms of suppressing over-learning problems, dealing with collinearity problems, robustness, and computation efficiency.

关键词： Robust state estimation historical snapshot off-line learning on-line matching collinearity

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Optimal Allocation of Synchronous Condensers in Renewable power Grids 7

Optimal Allocation of Synchronous Condensers in Renewable Po...

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7th IEEE Conference on Energy Internet and Energy system Integration, EI2 2023

作者： Han, Zijiao Na, Guangyu Dong, Wenkai Xie, Xiaorong Jia, Qi Su, Yuze State Grid Liaoning Electric Power Supply Co. Ltd. Shenyang China Tsinghua University State Key Laboratory of Power System Department of Electrical Engineering Beijing China

ISBN: (纸本)9798350345094

Optimal allocation of synchronous condensers is one of the most-commonly-used ways to improve the operation performance of renewable power generators in weak grid. However, except for optimality, equity of the allocation should also be taken seriously to ensure the acceptability of the scheme. To do so, in this paper, an optimization model for the allocation of synchronous condensers considering equity is established at first. By inducing a penalty term which measures equity of the allocation, scheme with the lowest investment and the best equity can be selected. Besides, the main constraint is to ensure that short circuit ratios seen by the renewable power generators are no less than the required level. Second, since the optimal allocation of synchronous condensers is a problem of non-linear integer programming, an improved genetic algorithm is utilized for the solution of the optimization. Finally, effectiveness of the optimization model proposed is validated via study cases. The results indicate that the method proposed can ensure equity of the allocation scheme while maintaining the lowest cost. © 2023 IEEE.

关键词： Genetic algorithms

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Renewable Energy Penetration Improving Method in Distribution Network based on Dynamic Reconfigurable Battery Network 4

Renewable Energy Penetration Improving Method in Distributio...

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4th International Conference on Smart Grid and Energy Internet, SGEI 2024

作者： Xiong, Ziyi Yang, Yi Zhou, Yanglin Zhou, Qi Ci, Song Department of Electrical Engineering Tsinghua University Beijing China State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China State Grid Jiangsu Electric Power Co. Ltd. Electric Power Research Institute Nanjing China

ISBN: (纸本)9798350368314

High proportion of renewable energy brings great challenges to the stable operation of the distribution network. Distributed energy storage (DES), as an interactive Lithium-ion battery energy storage system, can effectively improve the grid connection and serve as a backup power source. Aiming at the DES system supporting the flexibility of distribution network, this paper proposes a new type of dynamic reconfigurable battery (DRBN) system and its efficient collaborative optimization control method with the power converter system, clarifies the operation control mechanism of the DRBN system of the CPS architecture, proposes a multi-objective optimization control strategy for the DRBN system based on the CPS architecture, and formulates a demonstration application and verification plan. ©2024 IEEE.

关键词： DC distribution systems

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Fault diagnosis of PEMFC based on fatal and recoverable failures using multi-scale convolutional neural networks

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International Journal of Hydrogen Energy 2024年 80卷 916-925页

作者： Xu, Jiang-Hai Zhang, Ben-Xi Zhu, Kai-Qi Zheng, Xiu-Yan Zhang, Cong-Lei Chen, Zhang-Liang Yang, Yan-Ru Huang, Tai-Ming Bo, Zheng Wan, Zhong-Min Hsu, Shu-Han Yan, Wei-Mon Wang, Xiao-Dong State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Research Center of Engineering Thermophysics North China Electric Power University Beijing102206 China College of Mechanical Engineering Hunan Institute of Science and Technology Yueyang414006 China State Key Laboratory of Clean Energy Utilization College of Energy Engineering Zhejiang University Zhejiang Province Hangzhou310027 China Department of Mechanical Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Energy and Refrigerating Air-Conditioning Engineering National Taipei University of Technology Taipei10608 Taiwan

This study introduces a multi-scale convolutional neural network (MCNN) for diagnosing various faults in proton exchange membrane fuel cell (PEMFC) systems. Using simulated fault data from a 240 kW PEMFC stack, the MCNN method is validated. Compared to traditional methods like backpropagation neural network (BP), support vector machine (SVM), and temporal convolutional neural network (TCNN), MCNN achieves an average accuracy of 96.31%, outperforming BP (88.88%), SVM (90.67%), and TCNN (93.80%). The study demonstrates MCNN's effectiveness in diagnosing recoverable faults, fatal faults, and multiple faults in PEMFC systems, achieving fault diagnosis accuracies of over 97%. By leveraging its inherent advantages such as multi-channel processing, automatic feature learning, and parameter sharing, MCNN provides an effective solution for accurately diagnosing faults in PEMFC. The utilization of these advantages has enabled MCNN to perform efficient and accurate fault diagnosis in PEMFC systems. © 2024 Hydrogen Energy Publications LLC

关键词： Failure analysis

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