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Modeling and Operation of the Power-to-Gas System for Renewables Integration: A Review

CSEE Journal of Power and Energy systems 2018年第2期4卷 168-178页

作者： Xuetao Xing Jin Lin Yonghua Song You Zhou Shujun Mu Qiang Hu State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Electrical and Computer Engineering University of MacaoMacaoChina Department of Electrical Engineering Tsinghua UniversityBeijing 100084China National Institute of Clean and Low Carbon Energy Beijing 102211China Tsinghua-Sichuan Energy Internet Research Institute Chengdu 610213China

Power-to-Gas(P2G)plays an important role in enhancing large-scale renewable energy integration in power *** an emerging inter-disciplinary subject,P2G technology requires knowledge in electrochemistry,electrical engineering,thermodynamic engineering,chemical engineering and system *** at P2G modeling and operational problems concerning the research field of power systems and the energy internet,this paper briefly reviews the main technologies and application potentials of the P2G system,and makes systematic summaries of major progresses related to P2G’s integration into the power grid in a bottom-top manner,including the modeling of high/room-temperature electrolysis cells,steady-state/dynamic optimization control of the P2G system,P2G’s integrated model and operational strategies at the grid *** the final part of this paper,suggestions are put forward on future research directions of P2G systems from the aspects of modeling and operational optimization.

关键词： Electrolysis cell multi-energy network modeling and operation power-to-gas

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Digitally virtualized atoms for acoustic metamaterials

arXiv

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arXiv 2019年

作者： Cho, Choonlae Wen, Xinhua Park, Namkyoo Li, Jensen Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Department of Physics Hong Kong University of Science and Technology Clear Water Bay Hong Kong Hong Kong

By designing tailor-made resonance modes with structured atoms, metamaterials allow us to obtain constitutive parameters outside their limited range from natural or composite materials. Nonetheless, tuning the constitutive parameters relies much on our capability in modifying the physical structures or media in constructing the metamaterial atoms, posing a fundamental challenge to the range of tunability in many real-time applications. Here, we propose a completely new notion of virtualized metamaterials to lift the traditional boundary inherent to the physical structure of a metamaterial atom. By replacing the resonating physical structure with a designer mathematical convolution kernel with a fast digital signal processing circuit, we show that a decoupled control of the effective bulk modulus and density of the metamaterial is possible on-demand through a software-defined frequency dispersion. Purely noninterfering to the incident wave in the off-mode operation while providing freely reconfigurable amplitude, center frequency, bandwidth, and phase delay of frequency dispersion in on-mode, our approach adds additional dimension to wave moulding and can work as an essential building block for time-varying metamaterials. Copyright © 2019, The Authors. All rights reserved.

关键词： Metamaterials

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Optical frequency microcomb distillation for super channel data transmission

TechRxiv

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TechRxiv 2021年

作者： Prayoonyong, Chawaphon Boes, Andreas Xu, Xingyuan Tan, Mengxi Chu, Sai T. Little, Brent E. Morandotti, Roberto Mitchell, Arnan Moss, David J. Corcoran, Bill Photonic Communications Laboratory Dept. Electrical and Computer Systems Engineering Monash University ClaytonVIC3800 Australia School of Engineering RMIT University MelbourneVIC3001 Australia Optical Sciences Centre Swinburne University Hawthorne VIC3122 Australia Centre for Micro-Photonics Swinburne University Hawthorne VIC3122 Australia Department of Physics City University of Hong Kong Tat Chee Ave Hong Kong Xi’an Institute of Optics and Precision Mechanics The Chinese Academy of Sciences Xi’an China INRS – EMT VarennesQCJ3X 1S2 Canada Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu610054 China

Microcombs provide a potential compact and efficient light source for multi-Terabit-per-second optical superchannels. However, as the bandwidth of these multiwavelength light sources is increased, this can result in low per-line power. Optical amplifiers can be used to overcome power limitations, but the accompanying spontaneous optical noise can degrade performance in optical systems. To overcome this issue, we propose wideband noise reduction for comb lines using a high-Q microring resonator, whose resonances align with comb lines. When applying the proposed distillation to a superchannel system with 18 Gbaud, 64-QAM sub-channels in a > 10 Tb/s optical superchannel, we find that noise-corrupted comb lines can reduce the optical signal-to-noise ratio required for the comb by ~ 9 dB when used as optical carriers at the transmitter side, and by ~ 12 dB when used as a local oscillator at the receiver side. © 2021, CC BY.

关键词： Distillation

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Mapping the lidar attenuation coefficient in Yellowstone Lake, Yellowstone National Park, USA

Mapping the lidar attenuation coefficient in Yellowstone Lak...

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Propagation Through and Characterization of Atmospheric and Oceanic Phenomena, pcAOP 2018

作者： Roddewig, Michael R. Churnside, James H. Shaw, Joseph A. Electrical and Computer Engineering Department Montana State University BozemanMT United States Earth Systems Research Laboratory National Oceanic and Atmospheric Administration BoulderCO United States

ISBN: (纸本)9781943580446

Airborne lidar study of lake ecosystems is still a relatively unexplored field. In this presentation we introduce a spatial and temporal study of the lidar attenuation coefficient from a series of flights conducted in 2015 and 2016 over Yellowstone Lake, Yellowstone National Park, Wyoming, USA. We then relate these data to the Secchi disk depth, discuss the possible impact that local weather may have had on the attenuation coefficient, and compare these data to the modeled lidar attenuation coefficient. © 2018 The Author(s).

关键词： Optical radar

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Levelized-Cost-of-Electricity-Driven Design Optimization for Medium-Voltage Transformerless Photovoltaic Converters

Levelized-Cost-of-Electricity-Driven Design Optimization for...

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IEEE Energy Conversion Congress and Exposition

作者： Gab-Su Seo Satyaki Mukherjee Jinia Roy Kyle Goodrick Rahul Mallik Branko Majmunovic Soham Dutta Dragan Maksimovic Brian Johnson Power Systems Engineering Center National Renewable Energy Laboratory Golden CO USA Colorado Power Electronics Center University of Colorado Boulder CO USA Department of Electrical and Computer Engineering University of Washington Seattle WA USA

Design approaches for power electronics are typically focused on efficiency and power density;however, these strategies do not guarantee cost optimality in any well-defined sense. To overcome this shortcoming, we propose a design framework that yields circuit parameters that minimize the levelized cost of electricity (LCOE) of a generation system. LCOE serves as a meaningful metric since it captures total lifetime costs - including hardware, balance of system, and maintenance costs - and includes the impacts of power conversion efficiency and revenue from harvested energy. To obtain a tractable design problem, we formulate an approximate LCOE improvement model that quantifies the changes in LCOE resulting from a candidate converter design. We apply this framework to a multilevel cascaded topology for low-voltage dc to medium-voltage ac conversion without line-frequency transformers. An example 200 kW commercial-scale system is studied and the solution yields a design with 15 cascaded stages, 98.01% efficiency, and an LCOE reduction of 2.0%.

关键词： levelized cost of electricity design optimization multilevel converters

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Building a quantum engineering undergraduate program

arXiv

引用

arXiv 2021年

作者： Asfaw, Abraham Blais, Alexandre Brown, Kenneth R. Candelaria, Jonathan Cantwell, Christopher Carr, Lincoln D. Combes, Joshua Debroy, Dripto M. Donohue, John M. Economou, Sophia E. Edwards, Emily Fox, Michael F.J. Girvin, Steven M. Ho, Alan Hurst, Hilary M. Jacob, Zubin Johnson, Blake R. Johnston-Halperin, Ezekiel Joynt, Robert Kapit, Eliot Klein-Seetharaman, Judith Laforest, Martin Lewandowski, H.J. Lynn, Theresa W. McRae, Corey Rae H. Merzbacher, Celia Michalakis, Spyridon Narang, Prineha Oliver, William D. Palsberg, Jens Pappas, David P. Raymer, Michael G. Reilly, David J. Saffman, Mark Searles, Thomas A. Shapiro, Jeffrey H. Singh, Chandralekha IBM Quantum IBM T. J. Watson Research Center Yorktown HeightsNY United States Institut Quantique Département de Physique Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada Canadian Institute for Advanced Research TorontoONM5G 1M1 Canada The Duke Quantum Center Department of Physics Department of Electrical and Computer Engineering Department of Chemistry Duke University DurhamNC27708 United States SystemX Program Department of Electrical Engineering Stanford University StanfordCA94305 United States Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States The Quantum Engineering Program Department of Physics Colorado School of Mines GoldenCO80401 United States The Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO80309 United States The Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada The Department of Physics Virginia Tech BlacksburgVA24061 United States The IQUIST University of Illinois Urbana-Champaign UrbanaIL61801 United States JILA National Institute of Standards and Technology The University of Colorado BoulderCO80309 United States Department of Physics University of Colorado Boulder BoulderCO80309 United States The Department of Physics Imperial College London Prince Consort Road LondonSW7 2AZ United Kingdom The Yale Quantum Institute Department of Physics Yale University New HavenCT06520 United States Google Research VeniceCA90291 United States The Department of Physics & Astronomy San José State University San JoséCA95192 United States The School of Electrical and Computer Engineering Purdue University Indiana West Lafayatte47907 United States The Department of Physics The Ohio State University ColumbusOH43210 United States The Department of Physics University of Wisconsin-Madison 1150 University Avenue MadisonWI53706 United States The Quantitative Biosciences and Engineering

The rapidly growing quantum information science and engineering (QISE) industry will require both quantum-aware and quantum-proficient engineers at the bachelor's level. We provide a roadmap for building a quantum engineering education program to satisfy this need. For quantum-aware engineers, we describe how to design a first quantum engineering course accessible to all STEM students. For the education and training of quantum-proficient engineers, we detail both a quantum engineering minor accessible to all STEM majors, and a quantum track directly integrated into individual engineering majors. We propose that such programs typically require only three or four newly developed courses that complement existing engineering and science classes available on most larger campuses. We describe a conceptual quantum information science course for implementation at any post-secondary institution, including community colleges and military schools. QISE presents extraordinary opportunities to work towards rectifying issues of inclusivity and equity that continue to be pervasive within engineering. We present a plan to do so and describe how quantum engineering education presents an excellent set of education research opportunities. Finally, we outline a hands-on training plan on quantum hardware, a key component of any quantum engineering program, with a variety of technologies including optics, atoms and ions, cryogenic and solid-state technologies, nanofabrication, and control and readout electronics. Our recommendations provide a flexible framework that can be tailored for academic institutions ranging from teaching and undergraduate-focused two- and four-year colleges to research-intensive universities. © 2021, CC BY.

关键词： engineering education

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Comparison study of deep learning and time series for bioelectric potential analysis 3

Comparison study of deep learning and time series for bioele...

引用

3rd International Conference on Information Technology, Information systems and electrical engineering, ICITISEE 2018

作者： Tahyudin, Imam Nambo, Hidetaka Artificial Intelligence Laboratory Graduate School of Natural Science and Technology Electrical Engineering and Computer Science Kanazawa University Kanazawa Japan Department of Information Systems STMIK AMIKOM Purwokerto Indonesia

ISBN: (纸本)9781538670828

The study of bioelectric potential of plant has been conducted using some methods. Such as, decision tree (J48), multilayer perceptron, ANN, CNN, and etc. However, to find the best accuracy is a seriously challenge because the previous studies did not obtain a satisfied result. Furthermore, Because the data is sequence form, it is interesting if analyzed by deep learning (LSTM) and time series method (ARIMA). Both of methods are have the same characteristics. This approach is a new contribution for this topic. Therefore, the aim of this research is to compare LSTM and ARIMA method for analyzing bioelectric potential data set. For determining the accuracy, we use root mean square error (RMSE) and mean absolute error (MAE). Finally, in this case, the ARIMA model is better than LSTM method and presented a promise result. © 2018 IEEE.

关键词： Time series

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Retraction notice to "A strategic review on sustainable approaches in municipal solid waste management and energy recovery: Role of artificial intelligence, economic stability and life cycle assessment" [Bioresour. Technol. 379 (2023) 129044]

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Bioresource technology 2025年 421卷 132185页

作者： Rajendiran Naveenkumar Jayaraj Iyyappan Ravichandran Pravin Seifedine Kadry Jeehoon Han Raveendran Sindhu Mukesh Kumar Awasthi Samuel Lalthazuala Rokhum Gurunathan Baskar Biological Systems Engineering University of Wisconsin-Madison Madison WI 53706 United States Forest Products Laboratory USDA Forest Service Madison WI 53726 United States. Department of Biotechnology Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Thandalam Chennai 602107 India. Department of Biotechnology St. Joseph's College of Engineering Chennai 600119 India. Department of Applied Data Science Noroff University College Kristiansand Norway Artificial Intelligence Research Center (AIRC) Ajman University Ajman 346 United Arab Emirates Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon. Department of Chemical Engineering Pohang University of Science and Technology Pohang 37673 Republic of Korea. Department of Food Technology TKM Institute of Technology Kollam Kerala India. College of Natural Resources and Environment Northwest A&F University Yangling Shaanxi Province 712100 China. Department of Chemistry National Institute of Technology Silchar 788010 Assam India. Department of Biotechnology St. Joseph's College of Engineering Chennai 600119 India Department of Applied Data Science Noroff University College Kristiansand Norway. Electronic address: basg2002@***.

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THz near-field imaging of extreme subwavelength metal structures

arXiv

引用

arXiv 2021年

作者： Chen, Xinzhong Liu, Xiao Guo, Xiangdong Chen, Shu Hu, Hai Nikulina, Elizaveta Yao, Ziheng Betchel, Hans Martin, Michael C. Carr, G. Lawrence Dai, Qing Zhuang, Songlin Hu, Qing Zhu, Yiming Hillenbrand, Rainer Liu, Mengkun You, Guanjun Department of Physics and Astronomy Stony Brook University Stony BrookNY11794 United States Shanghai Key Lab of Modern Optical Systems Terahertz Technology Innovation Research Institute Engineering Research Center of Optical Instrument and System Ministry of Education University of Shanghai for Science and Technology Shanghai200093 China Division of Nanophotonics CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology Beijing100190 China CIC nanoGUNE Donostia-San Sebastián20018 Spain CIC nanoGUNE UPV/EHU Donostia-San Sebastián20018 Spain IKERBARSQUE Basque Foundation of Science Bilbao48013 Spain Advanced Light Source Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States National Synchrotron Light Source II Brookhaven National Laboratory UptonNY11973 United States Department of Electrical Engineering and Computer Science Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States

Modern scattering-type scanning near-field optical microscopy (s-SNOM) has become an indispensable tool in material research. However, as the s-SNOM technique marches into the far-infrared (IR) and terahertz (THz) regimes, emerging experiments sometimes produce puzzling results. For example, "anomalies" in the near-field optical contrast have been widely reported. In this letter, we systematically investigate a series of extreme subwavelength metallic nanostructures via s-SNOM near-field imaging in the GHz to THz frequency range. We find that the near-field material contrast is greatly impacted by the lateral size of the nanostructure, while the spatial resolution is practically independent of it. The contrast is also strongly affected by the connectivity of the metallic structures to a larger metallic "ground plane". The observed effect can be largely explained by a quasi-electrostatic analysis. We also compare the THz s-SNOM results to those of the mid-IR regime, where the size-dependence becomes significant only for smaller structures. Our results reveal that the quantitative analysis of the near-field optical material contrasts in the long-wavelength regime requires a careful assessment of the size and configuration of metallic (optically conductive) structures. Copyright © 2021, The Authors. All rights reserved.

关键词： Metals

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How much information is needed in quantized nonlinear control?

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中国科学（信息科学） 2018年第9期61卷 199-211页

作者： Chuang ZHENG Lin LI Leyi WANG Chanying LI School of Mathematical Sciences Beijing Normal University Beijing 100875 China Department of Electrical and Computer Engineering Wayne State University Detroit 48202 USA Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences Beijing 100190 China

Quantization rate is a crucial measure of complexity in determining stabilizability of control systems subject to quantized state *** paper investigates quantization complexity for a class of nonlinear systems which are subjected to disturbances of unknown statistics and unknown *** class of systems includes linear stablizable systems as special *** lower bounds on the quantization rates are derived which guarantee input-to-state stabilizability for continuous-time and sampled-data feedback strategies,*** examples are provided to validate the results.

关键词： nonlinear systems disturbances input-to-state stabilizability sampled systems quantization rate

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