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检索条件"任意字段=IEEE International Conference on e-Science and Grid Computing"

共 17242 条记录，以下是421-430 订阅

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Development of Linearized Direct Power Control for Three-Phase Rectifiers under Unbalanced Power grid 10

Development of Linearized Direct Power Control for Three-Pha...

引用

10th ieee international Power electronics and Motion Control conference, IPeMC 2024 eCCe Asia

作者： Liao, Yi-Hung Kuo, Wei-Lun Yeh, Cheng-Wei Liu, Jia-Sheng National Central University Department of Electrical Engineering Taiwan

ISBN: (纸本)9798350351330

This paper proposes a custom Clarke transformation applied to linearized voltage modulated direct power sliding mode control of three-phase rectifiers in unbalanced power grids to improve the three-phase current distortion caused by unbalanced power grids. Linearized voltage modulated direct power control uses algebraic transformation to convert the power inner loop of the original stationary frame from a linear time-varying system to a linear time-invariant system, which simplifies the controller design. The existing literature on linearized voltage modulated direct power control does not utilize in the unbalanced power grid. In this paper, a new type of custom Clarke transformation is developed in the unbalanced power grid. The user can define the Clarke matrix coefficients to fit for unbalanced power grid condition. The stationary frame α and β components can be derived through the custom Clarke transformation under unbalanced power gird and the input current distortion can be reduced. In addition, a sliding mode controller is added into the output voltage control loop to enhance dc-bus dynamic performance. © 2024 ieee.

关键词： Controllers

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Lightweight Blockchain-based Identity Authentication Scheme for Power Terminal 3

Lightweight Blockchain-based Identity Authentication Scheme ...

引用

3rd international conference on electrical engineering and Control science, IC2eCS 2023

作者： Chen, Lu Zhang, Tao Ma, Yuanyuan Dai, Zaojian State Grid Smart Grid Research Institute Co. Ltd Nanjing210003 China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing210003 China

ISBN: (纸本)9798350382426

In recent years, the construction of the power Internet of Things continues to advance, and the number of power terminal equipment is growing. However, the computing power and storage capacity of these terminal devices are limited, and the current blockchain-based identity authentication scheme has high requirements for computing and storage resources, limiting the participation of power terminal equipment with weak computing power and small storage space. Aiming at the problem that resource-limited power terminal equipment cannot join the blockchain, a lightweight consensus algorithm for power terminals is proposed, and a power terminal authentication scheme based on the lightweight consensus algorithm is designed to make up for the defect that resource-limited power terminal equipment does not support the use of blockchain. The security analysis shows that the scheme can effectively resist many kinds of network attacks and meet the security requirements of power terminal equipment. Performance analysis shows that the scheme has low computation cost and conforms to the principle of lightweight. © 2023 ieee.

关键词： Blockchain Identity Authentication Power Terminal

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Temporal Action Detection with Frequency Attention Mechanism 7

Temporal Action Detection with Frequency Attention Mechanism

引用

7th international conference on Mechatronics, Robotics and Automation

作者： Wu, Wanghui Lu, Tao Wang, Jiaming Tang, Pan Gao, Fangqun Wuhan Inst Technol Hubei Key Lab Intelligent Robot Wuhan Peoples R China Wuhan Inst Technol Wuhan Peoples R China China Elect Power Res Inst State Key Lab Power Grid Environm Protect Wuhan Peoples R China

ISBN: (纸本)9798350352481;9798350352474

Due to the variability of video length and action duration, the temporal action detection task faces the problem of blurred action boundaries that are difficult to capture accurately. To alleviate this problem, this paper proposes a Frequency Attention Mechanism (FAM) that adaptively models the frequency dependencies between video signal channels, enabling the model to better understand the frequency variations in the video and to handle the complexity of different action durations, thus enhancing the sensitivity and discriminative power of the action boundaries, and still providing powerful action recognition even in long video sequences Capabilities. Through comprehensive experimental validation on a series of representative benchmark datasets (e.g. THUMOS14 and ActivityNet1.3), our approach demonstrates significant performance improvement.

关键词： temporal action detection action recognition Transformer frequency attention mechanism video understanding

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Power quality challenges and urban microgrid based grid resiliency: Case of Niamey City electrical grid 12

Power quality challenges and urban microgrid based grid resi...

引用

12th international conference on Renewable energy Research and Applications (ICReRA)

作者： Abdou-Tankari, Mahamadou Arkhangelski, Jura Garba, Marou Lefebvre, Gilles Drame, Aboubacar Abdourahimou, Daouda Univ Paris Est Creteil CERTES Lab Creteil France EMIG High Sch Dept Elect Engn Tacoma WA USA Univ Abdou Moumouni Fac Sci & Tech Niamey Niger

ISBN: (纸本)9798350337938

In general cases, the weakness of the national electric grid is due to overloading, infrastructures aging, high temperatures, bad weather and cyber risks. In such systems, the interruptions of electricity supply can take several hours to days. The smartness of the Modern electrical networks and the using of grid-tied microgrids are an important means to improve their resilience. But, to perform strong and powerful resiliency of the grid, it is necessary to develop strong background and experiences of the weakness analyzing and detection. The development of real time analyzing tools based on deep learning and data science can help for more security and savings of the power supply. In this paper, a methodology of grid weakness analyzing is presented. It is based on long term real data collected, more than ten years, from the electrical company of Niger (Nigelec). The ieee Std 1366 (TM)-2012 indexes and the statistical based methodology called "Beta Method" are applied to the data to identify the outlying performance of the utility. Then, the interest of the Deep learning for real-time weakness analysis and resiliency improving is introduced. Also, thanks to the laboratory experimental tests, a methodological approach of the training algorithm criteria and decision laws estimation is presented. These tests consider the main defaults that can induce a loss of power supply and the grid disconnection. The data driven models, based on informational and analytical methods, are necessary for real time assessment and improving of the grid resiliency.

关键词： Weakness of the grid Resiliency of the grid Microgrid, Deep Learning, LSTM

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ONLINe PeDeSTRIAN TRACKING USING A DeNSe FISHeYe CAMeRA NeTWORK WITH eDGe computing 30

ONLINE PEDESTRIAN TRACKING USING A DENSE FISHEYE CAMERA NETW...

引用

30th ieee international conference on Image Processing (ICIP)

作者： Wang, Tsaipei Chiang, Sheng-Ho Natl Yang Ming Chiao Tung Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9781728198354

This paper describes a dense fisheye camera network for pedestrian tracking in an indoor environment, with the target scenario being an unmanned store. each fisheye camera is connected to a single-board computer for local tracking using its own images. The local tracks are integrated and global tracks generated at a central computer in an online manner. The local trackers are based on the popular DeepSORT algorithm, and the global tracker combines distance and novel specialization based factors to update global tracks from local tracks, avoiding the need of matching local tracks. experiments on a self-collected dataset demonstrate highly accurate tracking over several minutes of videos.

关键词： Multi-object tracking multi-camera tracking fisheye camera camera network edge computing

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Comparison of Different Machine Learning Algorithms in the Parameterization of Near-Surface Turbulent Fluxes 9

Comparison of Different Machine Learning Algorithms in the P...

引用

9th international conference on Cloud computing and Big Data Analytics, ICCCBDA 2024

作者： Fan, Qiang Gong, Bo Zhang, Qili Zhang, Hourong Mao, Xianyin Zhang, Haipeng Wu, Jianrong Zhang, Lusong Electric Power Research Institute of Guizhou Power Grid Co. Ltd Southern Power Grid Co. Ltd Key Laboratory of Ice Prevention & Disater Reducing of China Guiyang China Electric Power Research Institute of China Southern Power Grid Co. Ltd Guangzhou China

ISBN: (纸本)9798350373554

The study of non-iterative schemes for near-surface tu rbulent flux parameterization is significant for model forecasting and climate prediction. In this paper, four machine learning algorithms (Random Forest, CatBoost, XGBoost and LightGBM) are used to design non-iterative schemes for near-surface turbulent flux parameterization. Through comparison, we find that the results obtained by XGBoost and LightGBM exhibit significant fluctuations, sensitivity to minor data changes, and poor stability, with lower accuracy compared to the BH&H scheme, making them unsuitable to design the parameterization model. While CatBoost shows less fluctuation, its results still possess minor irregularities compared to the Random Forest model. The results of Random Forest are smooth, stable, and highly accurate, making it the most suitable algorithm among the four algorithms for application in the parameterization of near-surface turbulent fluxes. © 2024 ieee.

关键词： Parameterization

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Federated Data Augmentation Algorithm based on Heterogeneity Assessment 2

Federated Data Augmentation Algorithm based on Heterogeneity...

引用

2nd international conference on Cloud computing, Big Data Application and Software engineering, CBASe 2023

作者： Hu, Bang Zhang, Mingming Liu, Kai Li, Xianhui Wang, Yongli Nanjing University of Science and Technology School of Cyber Science and Engineering Nanjing China State Grid Jiangsu Electric Power Co. Ltd. Information and Communication Branch Nanjing China State Grid Electric Power Research Institute Co. Ltd Jiangsu Ruizhong Data Co. Ltd Nanjing China Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China

ISBN: (纸本)9798350331448

In order to solve the problem of poor learning effect caused by data heterogeneity among different participants in the existing federated learning methods, this paper proposes a federated data augmentation algorithm based on heterogeneity assessment (FDA-HA) from the perspective of mitigating the effect of heterogeneity and protecting user data privacy, which mitigates the degree of data heterogeneity among participants by generating adversarial networks for data augmentation and at the same time safeguards fairness in the data augmentation process under the premise of protecting data privacy while guaranteeing fairness in the data enhancement process. experimental results on MNIST, FashionMNIST, and Cifar10 datasets show that compared with mainstream federated learning algorithms, this algorithm improves the accuracy by 7.96% and 13.44% in data scenarios with different degrees of heterogeneity, and at the same time, it has a certain degree of fairness. © 2023 ieee.

关键词： Data privacy

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Optimization for Penalty Cost in electricity Trading Using energy Dispatching between Aggregators 8

Optimization for Penalty Cost in Electricity Trading Using E...

引用

8th international conference on Smart grid and Smart Cities, ICSGSC 2024

作者： Gui, Junping Liu, Zheng Cheng, Xueting Wen, Haoran Zhou, Botao Bao, Yueshuang Song, He State Grid Electric Power Research Institute State Grid Electric Power Research Institute Wuhan Efficiency Evaluation Company Limited Nanjing China State Grid Shanxi Electric Power Company Electric Power Research Institute State Grid Shanxi Electric Power Company Taiyuan China PKU-Changsha Institute for Computing and Digital Economy Changsha China

ISBN: (纸本)9798350377408

In the future retail electricity market, deviation penalties will be one of the largest challenges faced by energy aggregators, directly impacting their profitability. With the objective of minimizing the penalty cost, an energy deviation optimization method is proposed to optimize the assessed energy deviation amount with a mutual energy dispatching strategy among energy aggregators. The model considers the status of interruptible loads, expected interruption upper limits, interruption quantities, and the transfer of electricity of the aggregators under both day-ahead and real-time scenarios. Simulations conducted with different energy aggregators, representing different load types, demonstrate that the proposed method can effectively reduce energy deviations and associated penalty costs, with an average reduction of 16.6% in total costs compared to that without mutual energy dispatching. © 2024 ieee.

关键词： cost optimization electricity trading energy aggregator energy dispatching

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Improving the Reliability in Smart grid Neighbourhood Area Networks by Avoiding Frequent Path Selection 6

Improving the Reliability in Smart Grid Neighbourhood Area N...

引用

6th international conference on Contemporary computing and Informatics, IC3I 2023

作者： Singh, Vishal Singh, Dhanpratap Lovely Professional University Computer Science and Engineering Punjab Phagwara India Lovely Professional University Department of Computer Science and Engineering Punjab Phagwara India

ISBN: (纸本)9798350304480

In order to address the issue of Smart grid Communication's inability to quickly recover from congestion that causes the original path forwarding of traffic. The self-healing, self-organizing, and self-configuring networks are considered in the WMN during packet transmission, a new technology known as Wireless Mesh Networks (WMN) that has gained the interest of customers. The traffic is timely transmitted to the crowded path, as well as the length of the routers'packet queues and the congested path's available bandwidth, in addition to the periodic sending of probing packets. In this paper, the new model of Smart grid Neighborhood-Area Network (NAN), the Congestion Control Notification Frame (CCNF) is developed to manage the congestion by sending the notification message during packet transmission in the Mesh Network (MN), and also the effective route is predicted through Waggle-Sparrow Optimization (WSO). In addition, the research presented the comparison opposed to HWMP under NS2 for the proposed design justification to improve the performance of ieee ***. The proposed CCNF can allow the portable deployment of low cost and is designed to prevent congestion while transferring packets through the issuance of notification alerts that arise in the WMN. As a result, the new method produces better comparable results than the ones now in use. © 2023 ieee.

关键词： Congestion Control Notification Frame Route flapping Smart grid Waggle-Sparrow Optimization Wireless Mesh Networks

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efficient energy Management in Photovoltaic System Using grid Interconnected Solar System Compared with Battery energy Storage System by Limiting the Panel Array Losses 6

Efficient Energy Management in Photovoltaic System Using Gri...

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6th international conference on Contemporary computing and Informatics, IC3I 2023

作者： Subashini, B.R. Geetha, R. Saveetha School of Engineering Saveetha Institute of Medical and Technical Science Saveetha University Department of Electrical and Electronics Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350304480

The main research work is to enhance the energy generation through photovoltaic systems by comparing two PV methods-grid interconnected solar system(GISS) and Battery energy storage system (BeSS) by reducing the array losses. Two sets of samples are collected from each group, group 1 grid interconnected solar system has 12 samples and group 2 Battery energy storage system contains 12 samples. The total sample size is 24 with the G power set at 80%. By using grid interconnected solar system energy generation is 4540.7 kWh/year, and the same for Battery energy storage system energy generation is 4282.5 kWh/year. The significance is 0.037 (p © 2023 ieee.

关键词： Battery energy Storage System energy Generation Novel grid Interconnected Solar System Panel Array Losses Photovoltaic System PV Arrays Solar

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