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arXiv 2024年

作者： Zhuang, Yingrui Cheng, Lin Qi, Ning Wang, Xinyi Chen, Yue State Key Laboratory of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China Department of Earth and Environmental Engineering Columbia University New York10027 United States Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

Hosting capacity (HC) assessment for electric vehicles (EVs) is crucial for EV secure integration and reliable power system operation. Existing methods primarily focus on a long-term perspective (e.g., system planning), and consider the EV charging demands as scalar values, which introduces inaccuracies in real-time operations due to the inherently stochastic nature of EVs. In this regard, this paper proposes a real-time HC assessment method for EVs through a three-step process, involving real-time probabilistic forecasting, risk analysis and probabilistic optimization. Specifically, we conduct real-time probabilistic forecasting to capture the stochastic nature of EV charging demands across multiple charging stations by performing deterministic forecasting and fitting the distribution of forecasting errors. The deterministic forecasting is conducted using an adaptive spatio-temporal graph convolutional network (ASTGCN). ASTGCN leverages adaptive spatial feature extraction, attention-based temporal feature extraction, and second-order graph representation to improve the forecasting performance. Subsequently, based on the probabilistic forecasting of EV charging demands, we conduct real-time risk analysis and operational boundary identification by utilizing probabilistic power flow calculations to assess potential violations of secure operation constraints. Furthermore, we present the formulation of real-time HC of EVs considering expected satisfaction of stochastic EV charging demands, and propose an optimization model for real-time HC assessment of EVs. Numerical experiments on a real-world dataset demonstrate that the proposed ASTGCN model outperforms state-of-the-art forecasting models by achieving the lowest root mean square error of 0.0442, and the real-time HC is improved by 64% compared to long-term HC assessment. © 2024, CC BY.

关键词： Risk analysis

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IEEE T-BIOM Editorial Board Changes

IEEE Transactions on Biometrics, Behavior, and Identity Scie...

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IEEE Transactions on Biometrics, Behavior, and Identity Science 2024年第1期7卷 1-2页

作者： Naser Damer Weihong Deng Jianjiang Feng Vishal M. Patel Ajita Rattani Mark Nixon Smart Living & Biometric Technologies Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China Department of Automation Tsinghua University Beijing China Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA Department of Computer Science and Engineering College of Engineering University of North Texas Denton TX USA

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Spatio-Temporal Correlation-Based Surface Solar Irradiance Retrieval Approach Using Satellite Data Under Different Weather Conditions

SSRN

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SSRN 2024年

作者： Li, Na Zhen, Zhao Wang, Fei Department of Electrical Engineering North China Electric Power University Baoding071003 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Hebei Key Laboratory of Distributed Energy Storage and Microgrid North China Electric Power University Baoding071003 China Department of Automation Taiyuan Institute of Technology Taiyuan030008 China

Wide-area, high temporal-spatial resolution surface solar irradiance data (SSI) is critical for solar energy resource assessment, PV power station site selection, and PV power forecasting. However, it is evidently impractical to obtain the aforementioned irradiance data by deploying a large number of high-density observation devices on the ground. Satellite remote sensing, with global coverage and high spatio-temporal resolution, provides detailed surface information, widely applied in the retrieval of meteorological parameters and surface irradiance studies. Currently, most satellite data-based SSI retrieval studies only consider satellite cloud images as a representation of cloud cover, without fully utilizing the multi-channel spectral information from satellite. Furthermore, these studies not only overlook the impact of satellite cloud image spatial scale under different weather conditions on SSI retrieval but also neglect the correlation between pixels of satellite cloud images. To solve the above problems, this study proposes a spatio-temporal correlation-based SSI retrieval approach using satellite data under different weather conditions. The SSI retrieval approach mainly consists of three parts: weather classification and feature selection, SSI retrieval based on satellite single-pixel data, and SSI retrieval based on spatial correlation. The experiments not only confirm the feasibility of the proposed satellite single-pixel data-based SSI retrieval in this study but also validate the necessity of considering weather types in establishing spatio-temporal correlations for SSI retrieval. © 2024, The Authors. All rights reserved.

关键词： Solar energy

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Reduced-Order Consensus Protocols with Pure Relative Output: Design, Existence, and Dual Results

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IEEE Transactions on Automatic Control 2025年

作者： Ma, Yuwen Li, Xianwei Li, Shaoyuan Lin, Zongli Shanghai Jiao Tong University Department of Automation Shanghai200240 China State Key Laboratory of Submarine Geoscience China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China University of Virginia Charles L. Brown Department of Electrical and Computer Engineering CharlottesvilleVA22904 United States

This paper studies reduced-order dynamic consensus protocols for homogeneous linear multi-agent systems using pure relative output information. By applying H∞ control theory, a separation principle-like method with an additional small-gain constraint is proposed for designing an (nx-nu)th order protocol, where nx and nu are the numbers of states and inputs of each agent, respectively. Existence conditions for the protocol are then systematically discussed from the graph, low gain and high gain perspectives, respectively. It is revealed that the protocol always exists and can be found by the proposed design method for three cases: 1) directed acyclic networks, 2) agents with all eigenvalues in the closed left-half complex plane and 3) agents of minimum phase. Another reduced-order protocol of (nx - ny)th order is further discussed through duality. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method. © 1963-2012 IEEE.

关键词： Robust control

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The Pairing Analysis Improvement of Magnetized Structure in Electromagnetic Bulging Process in Case of Tube with Field Shaper

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Journal of Electromagnetic Analysis and Applications 2024年第4期16卷 43-67页

作者： Blaise Kevine Lenz Soronga Zhanqian Zhan Jing Liu Jonas Asamoah Mohamed Bangali Bangura Matala Makiese N’kodia Kambani Chrionie Md Jobayer Hossain Yongdong Chen Program Debugging and Design Department Guangdong Lyric Robot Automation Co. Ltd Huizhou China Electrical and Automation Department China Three Gorges University Yichang China Electronic Department Power Electronic Research Center University of Kent Giles Ln Canterbury UK Program Debugging Department Guangdong Lyric Robot Automation Co. Ltd. Huizhou China Electrical and Computer Engineering Department South China University of Technology Guangzhou China World Standardization Certification and Testing Group (Shenzhen) Co. Ltd. Shenzhen China Electrical Engineering-Power System Mapon University Kindu Democratic Republic of Congo Department of Economy Managment School of Management Computer and Telecomunication Rabbat Marocco Materials Visual Calibration Department Guangdong Lyric Robot Automation Co. Ltd. Huizhou China Program Design Department Guangdong Lyric Robot Automation Co. Ltd. Huizhou China

In the current practical science, the accuracy in the formability of metal alloys being the goal when using electromagnetic forming (EMF) technology, which is a high-speed processing technology that uses Lorentz forces to achieve plastic deformation of sheet metal;according to the previous analysis, the results have shown that in most cases, the Lorentz force acting on the workpiece (metal) is not uniform, there are uneven axial deformations of the metal plates which prevent the rapid advancement of today’s technology. In this article, we presented some advanced analyzes which will lead us to improve the technical solution for the problems of non-uniform axial deformations of the metals in the traditional tube electromagnetic forming technology (EMF). A field shaper is used as a practical forming tool to influence the magnetic field and magnetic pressure distribution, thereby improving the forming ability and result during the electromagnetic forming (EMF) process and we see that induced eddy current control is realized by changing the structural parameters of the magnetic field shaper;which improves the strength and controllability of the magnetic force that acts on the workpiece;thereby a greater radial magnetic pressure can be achieved with field shaper than the case without it;the field shaper regulates the electromagnetic force, the distribution of the magnetic pressure decreases, and the uniform force area of the tube increases which effectively enhances the uniform range of the pipe electromagnetic bulging and the electromagnetic induction coupling between the coil and the metallic workpiece is generally required to produce the Lorentz forces. Using COMSOL Multiphysics® simulation software helped us to accurately represent the real world, simulating multiple physical effects that happened in this model during the process.

关键词： Electromagnetic Forming Field Shaper Lorentz Force Magnetic Pressure Distribution

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Improved Res2Net Based on Multi-scale Attention Mechanism for Breast Cancer Image Classification 12th

Improved Res2Net Based on Multi-scale Attention Mechanism fo...

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12th International Conference on computer engineering and Networks, CENet 2022

作者： Lei, Suqin Deng, Xing Shao, Haijian Xia, Wang Department of Computer Jiangsu University of Science and Technology Jiangsu Zhenjiang212003 China College of Automation Key Laboratory of Ministry of Education of Complex Engineering System Measurement and Control Southeast University Jiangsu Nanjing210009 China School of Information Science and Technology Nantong University Nantong Jiangsu226019 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

ISBN: (纸本)9789811969003

Breast cancer is one of the most common cancers among female diseases. Since the classification accuracy of pathological images is crucial to the diagnosis of breast cancer, in order to reduce the error of manual diagnosis and improve the automatic classification accuracy of pathological images, this paper proposes a high-accuracy breast cancer classification method based on multi-scale attention mechanism enhanced Res2Net. By constructing a multi-channel residual connection in the residual block, and introducing a convolutional attention mechanism to enhance the feature extraction ability of Res2Net, and using group convolution to replace part of the ordinary convolution. In addition, since the channel information interaction across groups cannot be realized in the group convolution, which reduces the feature extraction ability. In this paper, the channel shuffling operation is used to reorganize the feature maps after the group convolution to achieve the information interaction between different groups. The evaluation results on the BreaKHis dataset show that, the accuracy and precision of the method in this paper have reached 98.5% and 98.9% respectively, in binary classification of histopathological images compared with the benchmark method, and the advantages of recall rate and F1 value are also more obvious. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image classification

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Feature Selection Based on a Modified Adaptive Human Learning Optimization Algorithm 7th

Feature Selection Based on a Modified Adaptive Human Learnin...

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7th International Conference on Life system Modeling and Simulation, LSMS 2021, and the 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021

作者： Yu, Siyue Jia, Yihao Hu, Xuelian Ni, Haoqi Wang, Ling Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics Engineering and Automation Shanghai University Shanghai200072 China Department of Electrical and Computer Engineering North Carolina State University RaleighNC27606 United States

ISBN: (纸本)9789811672125

This paper proposes a new wrapper feature selection method based on the modified adaptive Human Learning Optimization (MAHLO) algorithm and Support Vector Machine (SVM). To achieve better results, the initialization and random learning strategies are modified in MAHLO to solve the feature selection problem more efficiently and the adaptive strategies are used to enhance the performance and relieve the effort of parameter setting. Besides, a two-stage evaluation function is adopted to eliminate the useless and redundant features, which is easier to operate in applications. The simulation results indicate that MAHLO can solve high-dimensional feature selection problems more efficiently, and the classification results on the UCI benchmark problems further demonstrate the efficiency and the advantage of the proposed MAHLO-based wrapper feature selection method. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Feature Selection

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Improvement of the electrical Properties of Silicone Rubber Doped with Nano-zirconia Grafted by Voltage Stabilizer

Improvement of the Electrical Properties of Silicone Rubber ...

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International Conference on electrical Materials and power Equipment (ICEMPE)

作者： Xiaoqian Zhu Yuanxiang Zhou Yunxiao Zhang Ming Chen Xuanhao Liu State Key Lab of Control and Simulation of Power System and Generation Equipment & Department of Electrical Engineering Tsinghua University Beijing China College of Electrical Engineering and Automation Fuzhou University Fuzhou China Xiamen Power Supply Company State Grid Fujian Electric Power Company Xiamen China The Wind Solar Storage Division of State Key Laboratory of Control and Simulation of Power System and Generation Equipment School of Electrical Engineering Xinjiang University Urumqi China

Enhancing the electrical performance of silicone rubber (SiR) for cable accessories is noteworthy as they are almost the weakest parts of the cable system. Two types of voltage stabilizers were grafted onto the surface of nano-zirconia (ZrO 2 ) particles, and the grafted nanoparticles were added to the SiR. Measurements such as breakdown strength, and conductivity were carried out to evaluate the electrical performance of SiR nanocomposites. The electrical performance measurement results indicated that the breakdown strength of the nanocomposite SiR improved while the conductance current was reduced. The trap distribution showed that the improvement of the electrical performance of the nanocomposite SiR is mainly due to the decrease of the shallow trap density or the increase of the deep trap density.

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Hybrid Energy Storage Planning in Renewable-Rich Microgrids 4

Hybrid Energy Storage Planning in Renewable-Rich Microgrids

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4th Energy Conversion and Economics Annual Forum, ECE Forum 2024

作者： Bai, Mingfei Qiu, Chunmiao Long, Wangcheng Chen, Yanbo Geng, Hua State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Beijing TUSIES Technology Co. Ltd. China China Electric Power Planning & Engineering Institute China Department of Automation Tsinghua University Beijing10084 China

ISBN: (纸本)9781837242627

The stable and economical operation of renewable-rich microgrids poses unprecedented challenges for the future. Effective energy storage planning is critical for addressing the inherent volatility of renewable energy. In this context, we propose a two-stage robust planning model for hybrid energy storage systems including thermal and battery energy. Our model demonstrates that an appropriately sized battery energy storage system can provide reserve power for grid-forming converters, thereby mitigating the derating of renewable energy output and enhancing the overall economic efficiency of the energy system. We construct the uncertain set using a novel data-based methodology and develop an unnested column-and-constraint generation (C&CG) approach to achieve accurate solutions. This approach enhances computational efficiency by circumventing the complexities associated with nested structures. Case studies indicate that the average solution time for the unnested C&CG algorithm is reduced by over 20% compared to traditional nested C&CG methods. © The Institution of engineering & Technology 2024.

关键词： Battery storage

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Designing of a Solar MPPT Controller with the Technique of Differentiation Between Uniform Irradiance and Partial Shading Conditions 9

Designing of a Solar MPPT Controller with the Technique of D...

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9th IEEE International Conference on power and Energy, PECon 2022

作者： Ahmed, Sajib Mekhilef, Saad Mubin, Marizan Tey, Kok Soon Rawa, Muhyaddin University of Malaya Power Electronics and Renewable Energy Research Laboratory Faculty of Engineering Department of Electrical Engineering Kuala Lumpur50603 Malaysia School of Science Computing and Engineering Technologies Swinburne University of Technology HawthornVIC3122 Australia University of Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia King Abdulaziz University Center of Research Excellence in Renewable Energy and Power Systems Jeddah21589 Saudi Arabia

ISBN: (数字)9781665409902

ISBN: (纸本)9781665409902

Solar energy is considered one of the best essential energy sources to solve the present power crisis. The solar photovoltaic system has a low conversion efficiency that inflicts maximum power extractions. The non-linear relationship between the voltage and current insists on using a maximum power point tracking (MPPT) controller. Perturb and observe (P&O) MPPT controller is popular because of its simple design and cost-effectiveness features;nonetheless, it has drawbacks while operating under partial shading conditions (PSC). The maximum power trapezium (MPT) method modified the P&O algorithm by incorporating an appropriate scanning mechanism for PSC. Despite having good PSC performance, this method's tracking time is much longer than the conventional algorithm in both uniform irradiance conditions (UIC) and PSC. The algorithm proposed in this paper modifies the MPT method with an extra strategy to distinguish between the UIC and PSC. If the pattern is recognized as UIC, the proposed method utilizes the conventional P&O algorithm to track the MPP;otherwise, scanning techniques are being used. The proposed algorithm's operation was tested on simulation using distinct UIC and PSC patterns and worked effectively. © 2022 IEEE.

关键词： Cost effectiveness

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