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7th International Youth Conference on Radio Electronics, electrical and Power engineering, REEPE 2025

作者： Pham, Nam H. Kuznetsov, Oleg N. Doan, Canh T. Electrical Power Systems Department National Research University 'MPEI' Moscow Russian Federation Department of Relay Protection and Automation of Energy Systems National Research University 'MPEI' Moscow Russian Federation Institute of Engineering and Technology Vinh University Department of Electrical and Electronic Engineering Technology Viet Nam Hong Duc University Faculty of Engineering and Technology Viet Nam

ISBN: (纸本)9798331531836

As global energy demand continues to rise, concerns about climate change, environmental issues, and the depletion of fossil fuel resources require a careful consideration of the use of renewable energy, including solar energy. Vietnam's solar power plant (SPP) capacity has expanded considerably in recent years. However, technical and economic calculations for large-scale solar power plants and comparisons with other power plants are still limited. In this paper, the technical and economic aspects of solar power plants will be evaluated, with key economic indicators such as net present value (NPV), levelized cost of energy (LCOE), internal rate of return (IRR), benefit-cost ratio (BCR), and payback period (PB) being analyzed for both current and future scenarios. The results show that all power plants are economically effective. Furthermore, with investment costs for solar power plants decreasing rapidly, solar power plants will have high economic efficiency in the future. The useful information for investing and developing renewable energy policies in Vietnam is also presented in this paper. © 2025 IEEE.

关键词： economic analysis energy analysis levelized cost of energy renewable energy solar power plants

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Discharge image reconstruction and frequency domain analysis based on event data

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High Voltage 2024年第6期9卷 1195-1201页

作者： Quan Yuan Lei Deng Hao Guo Qishen Lyu Xin Zhang Jibin Wu Yu Deng Hongyang Zhou Xilin Wang Zhidong Jia Engineering Laboratory of Power Equipment Reliability in Complicated Coastal Environments Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenGuangdongChina Department of Precision Instrument Center for Brain Inspired Computing ResearchTsinghua UniversityBeijingChina College of Information and Computer Taiyuan University of TechnologyTaiyuanChina Shenzhen Power Supply Corporation China Southern Power Grid CorporationShenzhenChina Department of Computing The Hong Kong Polytechnic UniversityHong KongChina China Electric Power Research Institute BeijingChina School of Electrical Engineering and Automation Xiamen University of TechnologyXiamenChina

Optical image method has been the earliest and most used direct method for observing gas ***,research on gas discharge monitoring based on visible light mainly relies on high-speed cameras,but the large size,significant data storage requirements,and susceptibility to interference from complex backgrounds and lighting conditions limit their further *** vision sensing(DVS)technology is a neuromorphic sensing technology that asynchronously measures the luminance changes at each *** offers advantages such as a large dynamic range(>120 dB),high temporal resolution(up to 1µs),and small data volume(MB level).In this study,dynamic vision sensing technology was employed to monitor both 30 mm short-gaps and 1080 mm long-gaps discharge processes *** study developed the CountImage encoding method for event data and conducted image reconstruction,time-domain analysis,and frequency-domain charac-teristic analysis based on the event *** results show that the event-reconstructed images are highly consistent with the high-speed camera images,and the arc develop-ment process and its path can also be clearly ***,this study discovered a correlation between the electrical characteristics and event information during the discharge *** the time domain,the duration of the maximum DVS event count closely matches the duration during which the voltage drops to zero during *** the frequency domain,the Pearson correlation coefficient between the event stream spectrum and the voltage signal spectrum is greater than *** the maximum number of brightening events(ONmax)and the maximum number of darkening events(OFFmax)are positively correlated with the voltage applied between the *** study demonstrates that,compared to the GB/s data rate of high-speed cameras,this approach can record the discharge process and accurately reconstruct the discharge process,arc morphology,and discharge path at M

关键词： image analysis holds

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Generalization-Enhanced Few-Shot Object Detection in Remote Sensing

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IEEE Transactions on Circuits and Systems for Video Technology 2025年第6期35卷 5445-5460页

作者： Lin, Hui Li, Nan Yao, Pengjuan Dong, Kexin Guo, Yuhan Hong, Danfeng Zhang, Ying Wen, Congcong China Academy of Electronics and Information Technology Beijing100846 China China Meteorological Administration National Satellite Meteorological Center Innovation Center for FengYun Meteorological Satellite Beijing100081 China Tsinghua University State Key Laboratory of Hydroscience and Engineering Department of Hydraulic Engineering Beijing100084 China Chinese Academy of Sciences Aerospace Information Research Institute Beijing100094 China University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100049 China University of Science and Technology Beijing School of Automation and Electrical Engineering Beijing100083 China New York University Abu Dhabi Department of Electrical and Computer Engineering Abu Dhabi United Arab Emirates University of Science and Technology of China Anhui China

Object detection is a fundamental task in computer vision that involves accurately locating and classifying objects within images or video frames. In remote sensing, this task is particularly challenging due to the high resolution, multi-scale features, and diverse ground object characteristics inherent in satellite and UAV imagery. These challenges necessitate more advanced approaches for effective object detection in such environments. While deep learning methods have achieved remarkable success in remote sensing object detection, they typically rely on large amounts of labeled data. Acquiring sufficient labeled data, particularly for novel or rare objects, is both challenging and time-consuming in remote sensing scenarios, limiting the generalization capabilities of existing models. To address these challenges, few-shot learning (FSL) has emerged as a promising approach, aiming to enable models to learn new classes from limited labeled examples. Building on this concept, few-shot object detection (FSOD) specifically targets object detection challenges in data-limited conditions. However, the generalization capability of FSOD models, particularly in remote sensing, is often constrained by the complex and diverse characteristics of the objects present in such environments. In this paper, we propose the Generalization-Enhanced Few-Shot Object Detection (GE-FSOD) model to improve the generalization capability in remote sensing FSOD tasks. Our model introduces three key innovations: the Cross-Level Fusion Pyramid Attention Network (CFPAN) for enhanced multi-scale feature representation, the Multi-Stage Refinement Region Proposal Network (MRRPN) for more accurate region proposals, and the Generalized Classification Loss (GCL) for improved classification performance in few-shot scenarios. GE-FSOD demonstrates superior robustness and accuracy in remote sensing FSOD tasks through these enhancements. Extensive experiments on the DIOR and NWPU VHR-10 datasets show that our

关键词： Labeled data

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Impact of High Photovoltaic Penetration on the Voltage Stability of Vietnam's Power System 7

Impact of High Photovoltaic Penetration on the Voltage Stabi...

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7th International Youth Conference on Radio Electronics, electrical and Power engineering, REEPE 2025

作者： Pham, Nam H. Kuzetsov, Oleg N. Doan, Canh T. National Research University 'MPEI' Electrical Power Systems Department Moscow Russian Federation Institute of Engineering and Technology Vinh University Department of Electrical and Electronic Engineering Technology Viet Nam National Research University 'MPEI' Department of Relay Protection and Automation of Energy Systems Moscow Russian Federation Hong Duc University Faculty of Engineering and Technology Viet Nam

ISBN: (纸本)9798331531836

Photovoltaics (PV) play an essential role in energy networks by promoting clean, sustainable energy and reducing reliance on fossil fuels. However, their operational characteristics introduce new challenges, particularly concerning grid reliability and voltage stability. In this paper, the impact of solar photovoltaic plant (SPP) penetration on voltage behavior in the central region of Vietnam is examined using dynamic models at different integration levels, ranging from 0% to 40%. The results reveal that while low SPP penetration has minimal effects, high penetration levels (30% and 40%) significantly reduce reactive power support, exacerbating voltage collapse risks. These findings underscore the necessity for advanced voltage and reactive power control strategies to ensure grid stability in high-SPP scenarios. © 2025 IEEE.

关键词： solar photovoltaic plant penetration voltage collapse Voltage Stability voltage stability margin

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MSMB-GCN: Multi-scale Multi-branch Fusion Graph Convolutional Networks for 3D Human Pose Estimation

MSMB-GCN: Multi-scale Multi-branch Fusion Graph Convolutiona...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Ji, Shanshan Meng, Qiwei Wang, Wen Lin, Zheyuan Li, Te Wan, Minhong Zhang, Chunlong Gu, Jason Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9798350325706

In human-robot interaction (HRI), human pose estimation is a necessary technology for the robot to perceive the dynamic environment and make interactive actions. Recently, graph convolutional networks (GCNs) have been increasingly used for 2D to 3D pose estimation tasks since the skeleton topologies can be viewed as graph structures. In this paper, we propose a novel graph convolutional network architecture, Multi-scale Multi-branch Fusion Graph Convolutional Networks (MSMB-GCN), for 3D Human Pose Estimation(3D HPE) task. The proposed model consists of multiple GCN blocks with a multi-branch architecture. This multi-branch architecture enables the model to get multi-scale features for human skeletal representations. The group of GCN blocks, which has strong multi-level feature extraction capabilities, allows the model to learn global and local features, lower-level and higher-level features. Experiment results on the HumanPose benchmark demonstrate that our model outperforms the state-of-the-art and ablation studies validate the effectiveness of our approach. © 2023 IEEE.

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Real-Time Motion Generation and Data Augmentation for Grasping Moving Objects with Dynamic Speed and Position Changes

Real-Time Motion Generation and Data Augmentation for Graspi...

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IEEE/SICE International Symposium on System Integration

作者： Kenjiro Yamamoto Hiroshi Ito Hideyuki Ichiwara Hiroki Mori Tetsuya Ogata Robotics Research Department Connective Automation Innovation Center R&D Group Hitachi Ltd. Institute for AI and Robotics Future Robotics Organization Faculty of Science and Engineering Waseda University

While deep learning enables real robots to perform complex tasks had been difficult to implement in the past, the challenge is the enormous amount of trial-and-error and motion teaching in a real environment. The manipulation of moving objects, due to their dynamic properties, requires learning a wide range of factors such as the object's position, movement speed, and grasping timing. We propose a data augmentation method for enabling a robot to grasp moving objects with different speeds and grasping timings at low cost. Specifically, the robot is taught to grasp an object moving at low speed using teleoperation, and multiple data with different speeds and grasping timings are generated by down-sampling and padding the robot sensor data in the time-series direction. By learning multiple sensor data in a time series, the robot can generate motions while adjusting the grasping timing for unlearned movement speeds and sudden speed changes. We have shown using a real robot that this data augmentation method facilitates learning the relationship between object position and velocity and enables the robot to perform robust grasping motions for unlearned positions and objects with dynamically changing positions and velocities.

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Additional Charge Throughput Reduction Method Based on Circulating Current Injection for the MMC Battery Energy Storage System 5th

Additional Charge Throughput Reduction Method Based on Circu...

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5th International Conference on Energy Storage and Intelligent Vehicles, ICEIV 2022

作者： Yu, Haolin Xiao, Qian Jin, Yu Mu, Yunfei Ma, Shiqian Jia, Hongjie Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin China Department of Electrical Engineering and Automation Harbin Institute of Technology Harbin China State Grid Tianjin Electric Power Research Institute Tianjin China

ISBN: (纸本)9789819910267

The battery packs experience alternate current in the modular multilevel converter battery energy storage system (MMC-BESS), which can cause additional charge throughput and shorten the lifetime of the battery. Therefore, an additional charge throughput reduction method has been proposed for the MMC-BESS based on the second-order circulating current injection. Firstly, the principle of the MMC-BESS is introduced. Then, the additional charge throughput is analyzed by the instantaneous power fluctuation in the arms of the MMC-BESS. Afterwards, a second-order circulating current is injected to adjust the power in the arms of the MMC-BESS. As a result, the additional charge and discharge of the battery packs can be reduced in each fundamental cycle. Finally, comparative experiments are conducted and the results show that compared with the conventional methods, the proposed method can effectively reduce the additional charge throughput of the battery packs in the MMC-BESS. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Power converters

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research on the Establishment and Simulation of High-accuracy Digital Model of Railway Signal Relay

Research on the Establishment and Simulation of High-accurac...

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System Reliability and Safety engineering (SRSE), International Conference on

作者： Xinghai Zhao Qian Wang Zhanghongda Ke Jie Deng Electrical Apparatus Research and Development Department School of Electrical Engineering and Automation Harbin Institute of Technology Shenyang Railway Signal Co. Ltd Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China

ISBN: (数字)9798350356083

ISBN: (纸本)9798350356090

Digital-twin technology is continuous developing and applicating in equipment manufacturing industry. High-accuracy digital model is the basis of digital-twin, and its importance is becoming increasingly prominent. The current relay modeling and simulation research is mostly based on the design size, without considering the influence of manufacturing process parameters on product performance, and the accuracy is not high. In this paper, a certain type of railway signal relay is taken as the research object, and the high-accuracy digital model of the relay and its simulation technology are studied. The digital model is established include the static electromagnetic simulation model of the relay, the simulation model of the contact spring system and the simulation model of the dynamic characteristics. In the model, process dimension parameters and adjustment parameters are introduced into the model. So that the digital model can accurately reflect the actual state of the product. The characteristic parameters of the digital model are simulated and calculated, and the accuracy of the simulation results is verified by oscilloscope and high-speed camera technology.

关键词： Accuracy Oscilloscopes Rail transportation Data models Systems simulation Safety Reliability Relays Springs Electromagnetics

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Permanent Magnet Shape Optimization Method for PMSM Air Gap Flux Density Harmonics Reduction

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CES Transactions on electrical Machines and Systems 2021年第4期5卷 284-290页

作者： Chengsi Liu Yongxiang Xu Jibin Zou Guodong Yu Liang Zhuo School of Electrical Engineering and Automation of HIT Department of Electrical Engineering Harbin Institute of Technology the State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Institute of Technology and National Engineering Research Center for Small and Special Precision Motors Guizhou Aerospace Linquan Motor Co.Ltd

This paper proposed a permanent magnet optimization method to suppress the air gap flux density harmonic of permanent magnet synchronous motor(PMSM).The method corrected the effective air gap length of the motor,calculated the magnetization length of the permanent in the case of parallel magnetization,and took the influence of the permanent magnet relative permeability into *** on these works,for a given sinusoidal air gap flux density waveform,the corresponding structural parameters can be calculated,so as to achieve the optimization of the permanent *** using this method to optimize the shape of the magnet,the fundamental wave of the air gap flux density can be retained to the greatest extent,so as to eliminate harmonics and maintain the output capacity at the same *** feasibility and accuracy of the method have been verified by finite element analysis(FEA)and prototype machine *** method is simple and time-saving,and has a satisfactory accuracy,which provides a reference method for permanent magnet optimization of PMSM.

关键词： Permanent magnet synchronous motor(PMSM) analytical method finite element analysis(FEA) magnet shape optimization.

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Ethical Decision-making for Autonomous Driving based on LSTM Trajectory Prediction Network

Ethical Decision-making for Autonomous Driving based on LSTM...

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2023 International Conference on Biomimetic Intelligence and robotics

作者： Wei, Wen Wang, Jiankun Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China

The development of autonomous vehicles has brought a great impact and changes to the transportation industry, offering numerous benefits i n t erms o f s afety a nd e fficiency. How ever, one of the key cha llenges tha t aut onomous dri ving fac es is how to make ethical decisions in complex situations. To address this issue, in this article, a novel trajectory prediction method is proposed to achieve ethical decision-making for autonomous driving. Ethical considerations are integrated into the decision-making process of autonomous vehicles by quantifying the utility principle and incorporating them into mathematical formulas. Furthermore, trajectory prediction is optimized using LSTM network with an attention module, resulting in improved accuracy and reliability in trajectory planning and selection. Through extensive simulation experiments, we demonstrate the effectiveness of the proposed method in making ethical decisions and selecting optimal trajectories. © 2023 The Authors. Published by Elsevier B.V.

关键词： Decision making

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