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A massive grid-connected power accumulator battery testing system using hybrid AC-DC microgrid

Diangong Jishu Xuebao/Transactions of China Electrotechnical Society 2014年 29卷 449-453页

作者： Long, Bo Sun, Hongbin Wang, Bin Yao, Shuqing Fang, Xu Yao, Gaoxiang University of Electronic Science and Technology Chengdu610054 China State Key Laboratory of Control and Simulation of Power System and Generation Equipments Tsinghua University Beijing100084 China Bohai New Century Machinery Manufacturing Co. Ltd. TianJin300280 China

Nowadays, the network mode of the most energy recovery power battery testing instruments adopts AC-microgrid, which has the drawbacks of low energy recovery efficiency, complicated power circuit topology, cumbersome of the control algorithms. Aiming at these issues, a hybrid AC-DC microgrid system which is based on the power battery testing system has been put forward in this paper. The proposed scheme is composed by an energy storing system, a bidirectional DC-DC converter for test experiment, the grid-side loads, compared with conventional scheme, the proposed scheme has the merits of higher energy recovery efficiency, simplified power circuit for testing instruments. ©, 2014, Diangong Jishu Xuebao/Transactions of China Electrotechnical Society. All right reserved.

关键词： DC-DC converters

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Comparisons and discussion of three typical robot path planning approaches

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Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (science and technology) 2005年第SUPPL.期36卷 315-319页

作者： Wang, Qi-Zhi Wang, Hong-Zhi School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China Laboratory of Complex System and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 10080 China Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 China Shenyang Coking and Coal Gas Limited Company Shenyang 110026 China

Three typical path planning methods, i.e. artificial potential field, probabilistic path planning and biologically inspired neural network, were introduced. The analysis and comparisons were made in relating to genera... 详细信息

关键词： Artificial potential fields Biologically inspired neural network Obstacle avoidance Probabilistic path planning Robot path planning

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A co-evolutionary particle swarm optimization with dynamic topology for solving multi-objective optimization problems

Advances in Modelling and Analysis A

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Advances in Modelling and Analysis A 2016年第1期53卷 145-159页

作者： Wu, Daqing Tang, Lixiang Li, Haiyan Ouyang, LiJun Computer Science and Technology Institute University of South China HangyangHunan China Antai College of Economics and Management Shanghai Jiao Tong University Shanghai200240 China Zigong643000 China Key Laboratory of Guangxi High Schools for Complex System and Computational Intelligence Guangxi University for Nationalities Nanning530006 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University HefeiAnhui Province230039 China Department of Business Administration Hunan University of Finance and Economics Hunan410205 China

This paper proposes a multi-objective with dynamic topology particle swarm optimization (PSO) algorithm for solving multi-objective problems, named DTPSO. One of the main drawbacks of classical multi-objective particle swarm optimization algorithm is low diversity. To overcome this disadvantage, DTPSO uses two dynamic local best particles to lead the search particles with multiple populations to deal with multiple objectives, and maintains diversity of new found non-dominated solutions via partitioned the searching space into fixed number of cells. The proposed DTPSO is validated through comparisons with other two multi-objective algorithms using established benchmarks and metrics. simulation results demonstrated that DTPSO shows competitive, if not better, performance as compared to the other algorithms. © 2016, AMSE Press. All rights reserved.

关键词： Multiobjective optimization

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Development of a regional carbon assimilation system and its application for estimating fossil fuel carbon emissions in the Yangtze River Delta, China

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science of the Total Environment 2024年 957卷 177720页

作者： Zhang, Zhengqi Feng, Shuzhuang Chen, Yan Liu, Qiang Ju, Weimin Xiao, Wei Huang, Cheng Wang, Yanyu Wang, Hengmao Jia, Mengwei Wang, Xingyu Jiang, Fei Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System Science Nanjing University Nanjing210023 China Jiangsu Provincial Climate Center Jiangsu Meteorological Bureau Nanjing210018 China Frontiers Science Center for Critical Earth Material Cycling Nanjing University Nanjing210023 China Nanjing CLIMBLUE Technology co. LTD Nanjing211135 China Nanjing University of Information Science and Technology Nanjing210044 China Shanghai Environmental Monitoring Centre Shanghai200235 China State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex Shanghai Academy of Environmental Sciences Shanghai200233 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing210023 China Jintan National Climatic Observatory Jiangsu Meteorological Bureau Jintan213299 China

Urban areas are the largest contributors to global fossil fuel carbon emissions, and controlling urban carbon emissions is critical to addressing climate change and reducing greenhouse gas emissions. However, estimates of urban emissions remain large uncertainties, making it difficult to accurately understand changes in urban carbon emissions and to assess the effectiveness of emission controls. Atmospheric CO2 observations, through data assimilation, can objectively invert changes in urban carbon emissions. In this study, inheriting the inversion method of a global carbon assimilation system of GCASv2, we constructed a regional carbon assimilation system based on a regional 3-D atmospheric chemical transport model WRF-CMAQ, named RegGCAS. We tested the performance of the established assimilation system for winter carbon emissions in the Yangtze River Delta (YRD) by performing a 9 km × 9 km resolution inversion in December 2020, using observations from 6 ground stations and two emission inventories as a priori, respectively. The results show that after assimilating the observations in the YRD region, especially in Suzhou and Hangzhou where there are more observing sites, the two significantly different a priori emissions are effectively converged, with the relative difference being reduced from −45 % and − 36 % of the a priori emissions to −10 % and − 15 % of the a posteriori emissions. Furthermore, the daily changes of the inverted emissions clearly show that weekend emissions are lower than weekday emissions, i.e. the inversion can reveal the weekend effect of emissions changes. This suggests that our system is well established and can be used for estimating fossil fuel carbon emissions during winter. Meanwhile, these results also imply that with our system, when a city has three or more stations, its total emissions can be constrained reliably. © 2024 Elsevier B.V.

关键词： Low emission

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A more compact object detector head network with feature enhancement and relational reasoning

arXiv

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arXiv 2021年

作者： Zhang, Wenchao Fu, Chong Chang, Xiangshi Zhao, Tengfei Li, Xiang Sham, Chiu-Wing School of Computer Science and Engineering Northeastern University Shenyang110819 China Engineering Research Center of Security Technology of Complex Network System Ministry of Education China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang110819 China Baidu Smart Life Group NO. 10 Xibeiwang East Street Ke Ji Yuan Haidian District Beijing100193 China School of Computer Science University of Auckland New Zealand

Modeling implicit feature interaction patterns is of significant importance to object detection tasks. However, in the two-stage detectors, due to the excessive use of hand-crafted components, it is very difficult to reason about the implicit relationship of the instance features. To tackle this problem, we analyze three different levels of feature interaction relationships, namely, the dependency relationship between the cropped local features and global features, the feature autocorrelation within the instance, and the cross-correlation relationship between the instances. To this end, we propose a more compact object detector head network (CODH), which can not only preserve global context information and condense the information density, but also allows instance-wise feature enhancement and relational reasoning in a larger matrix space. Without bells and whistles, our method can effectively improve the detection performance while significantly reducing the parameters of the model, e.g., with our method, the parameters of the head network is 0.6× smaller than the state-of-the-art Cascade R-CNN, yet the performance boost is 1.3% on COCO test-dev. Without losing generality, we can also build a more lighter head network for other multi-stage detectors by assembling our method. Copyright © 2021, The Authors. All rights reserved.

关键词： Object detection

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Conditional Adversarial Domain Adaption based on Self-attention

Journal of Network Intelligence

引用

Journal of Network Intelligence 2022年第1期7卷 175-188页

作者： Zhao, Li-Quan Zhang, Yu-Peng Teng, Zi-Ming Jiang, Zi-Cong Cui, Ying Kan, Zhong-Feng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China College of information and communication Jilin University Changchun130012 China Graduate school of Information Science and Electrical Engineering Kyushu University Fukuoka819-0395 Japan Zhuhai Power Supply Bureau Guangdong Electric Power Corporation Zhuhai519000 China Jilin Power Supply Bureau Jilin Electric Power Corporation Jilin132012 China

Transfer learning is a deep learning method. It transforms knowledge in the source domain and feeds it to the target domain to improve the performance of the target domain model. The conditional adversarial domain adaption method is one of a number of transfer learning methods. It uses Resnet as the feature extraction network;however, Resnet can only determine the relationship between local features, and so its feature extraction accuracy is limited. To overcome this problem, a self-attention layer has been designed in order to determine the relationship among all features. This layer is added between the fourth layer and fifth layer of Resnet. Besides, a cross-entropy function is introduced into loss function, and a sigmoid layer is designed and used as the out layer in conditional adversarial domain adaption. These produce gradient disappearance in the deep network, and influence the discriminator training effect. To solve that problem, a least squares function is used as to design the loss function. The new type of loss function does not require the sigmoid function. Using theoretical analysis, we explain how this new loss function can be used to solve the gradient disappearance problem, thus rendering the network structure more stable. We compare our proposed method with other datasets, including Joint Adaptation Networks, adversarial domain adaptation, conditional adversarial domain adaption, Resnet-50, domain-adversarial neural network on imageCLEF-DA, Office-Home, and Office-31. Our simulation results show that the proposed conditional adversarial domain adaption based on self-attention method has the fastest convergence speed and highest accuracy the among different datasets. © 2022, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Computer vision

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Self adaptation of chimera states

arXiv

引用

arXiv 2018年

作者： Yao, Nan Huang, Zi-Gang Ren, Hai-Peng Grebogi, Celso Lai, Ying-Cheng Department of Applied Physics Xi’an University of Technology Xi’an710048 China School of Life Science and Technology Xi’an Jiao Tong University Xi’an710049 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Institute for Complex Systems and Mathematical Biology King’s College University of Aberdeen AberdeenAB24 3UE United Kingdom School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of "intelligence" in achieving robustness through self adaptation. The behavior can be exploited for controlled generation of chimera states with their coherent component placed in any desired spatial region of the system. Copyright © 2018, The Authors. All rights reserved.

关键词： Dynamical systems

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First Principles Calculations of Charge Shift Photocurrent in Vdws Slide Double Layered 2d H-Bn and Β-Ges Homostructures

SSRN

引用

SSRN 2022年

作者： Kaner, Ngeywo Tolbert Wei, Yadong Raza, Ali Yang, Jianqun Li, Xingji Li, Weiqi Jiang, YongYuan Wei Quan, Tian School of Physics Harbin Institute of Technology Harbin150001 China School of Materials Science and Engineering Harbin Institute of Technology Harbin150001 China Technology Innovation Center of Materials and Devices at Extreme Environment Harbin Institute of Technology Harbin150001 China 1-Km Main Daska Road Punjab Sialkot51040 Pakistan State Key Laboratory of Intense Pulsed Radiation Simulation and Effect Xi’an710024 China Key Lab of Micro-Optics and Photonic Technology of Heilongjiang Province Harbin150001 China Key Laboratory of Micro-Nano Optoelectronic Information System Ministry of Industry and Information Technology Harbin150001 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan030006 China Chongqing Key Laboratory of Theoretical and Computational Chemistry College of Chemistry and Chemical Engineering Chongqing University Chongqing401331 China

Shift photovoltaic current (SPC) in polar non-centrosymmetric materials has recently emerged as a promising candidate for the next generation photovoltaic devices in which Shockley-Queisser limits are fully overcome. Here, we apply first principles calculations to predict colossal SPC in the slide bilayers of 2D h -BN and β-GeS vdW homostructures. The large SPC in slide bilayers h -BN and β-GeS reaches 49.3 µAV-2 and 130µ µAV-2 , respectively, in the ultra-violet (UV) region. Increasing the number of layers is further implemented to tune the band structure of the two homostructures. Consequently, giant SPC peaks about 3 times larger than those of the 2-layers is predicted at photon energies 7.40 eV and 5.95 eV in the 5-layers of h -BN and β-GeS, respectively. The two homostructures may thus be promising building blocks for next-generation shift current devices. These findings also suggest layering as a possible convenient approach of enhancing and also tuning the SPC output in thin layered materials. © 2022, The Authors. All rights reserved.

关键词： Van der Waals forces

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Time-resolved ARPES of excitons in a 2D semiconductor

Time-resolved ARPES of excitons in a 2D semiconductor

引用

Conference on Lasers and Electro-Optics (CLEO)

作者： Julien Madéo Michael K. L. Man Chakradhar Sahoo Marshall Campbell Vivek Pareek E Laine Wong Abdullah Al-Mahboob Nicholas S. Chan Arka Karmakar Bala Murali Krishna Mariserla Xiaoqin Li Tony F. Heinz Ting Cao Keshav M. Dani Femtosecond Spectroscopy Unit Okinawa Institute of Science and Technology Okinawa Japan School of Physics University of Hyderabad Hyderabad Telangana India Center for Complex Quantum System the University of Texas at Austin Austin TX U.S.A Indian Institute of Technology Jodhpur Rajasthan India Stanford University Stanford California U.S.A. SLAC National Accelerator Laboratory Menlo Park California USA University of Washington Seattle WA U.S.A

We use a table-top time-resolved ARPES based on a MHz XUV source to directly observe direct and momentum-forbidden excitons in the full first Brillouin zone of WSe 2 monolayer and measure their ultrafast dynamics.

ISBN: (纸本)9781943580910

关键词： Semiconductor device measurement Excitons Semiconductor lasers Scattering Measurement by laser beam Lasers and electrooptics Laser excitation

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Vulnerability analysis of smart grid based on complex network theory

Vulnerability analysis of smart grid based on complex networ...

引用

International Conference on Information science and technology (ICIST)

作者： Xisong Dong Timo R. Nyberg Pekka Hämäläinen Gang Xiong Yuan Liu Jiachen Hou Laboratory of Complex System Intelligent Science Chinese Academy of Sciences Beijing China Department of Industrial Engineering and Management Aalto University Aalto Finland Tekla Corporations Metsänpojankuja FI-02130 Espoo FINLAND Cloud Computing Center Chinese Academy of Sciences Dongguan China Nanjing Smart Energy Information Technology Co. LTD. Nanjing China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China

Smart grid has been widely acknowledged around the world. The rapid development of complex network theory provides a new perception into the research of smart grid. Based on the latest progress in the field of complex network theory, smart grid can be treated as small world networks. This paper examines the tolerance of smart grid against attacks to analyze its vulnerability, and proposes a technique to study the relationship between the electric betweenness and the reliability of smart grid. Based on these researches, the specific concept of vulnerability investigation to indicate smart grid is clarified. Furthermore, the proposed method will be investigated by an IEEE test system in contrast with the result from actual concept in power grid to indicate its effectiveness.

关键词： Context Smart grids

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