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Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic (vol 11, 5172, 2020)

NATURE COMMUNICATIONS 2020年第1期11卷 5172页

作者： Liu, Zhu Ciais, Philippe Deng, Zhu Lei, Ruixue Davis, Steven J. Feng, Sha Zheng, Bo Cui, Duo Dou, Xinyu Zhu, Biqing Guo, Rui Ke, Piyu Sun, Taochun Lu, Chenxi He, Pan Wang, Yuan Yue, Xu Wang, Yilong Lei, Yadong Zhou, Hao Cai, Zhaonan Wu, Yuhui Guo, Runtao Han, Tingxuan Xue, Jinjun Boucher, Olivier Boucher, Eulalie Chevallier, Frederic Tanaka, Katsumasa Wei, Yiming Zhong, Haiwang Kang, Chongqing Zhang, Ning Chen, Bin Xi, Fengming Liu, Miaomiao Breon, Francois-Marie Lu, Yonglong Zhang, Qiang Guan, Dabo Gong, Peng Kammen, Daniel M. He, Kebin Schellnhuber, Hans Joachim Department of Earth System Science Tsinghua University Beijing China. zhuliu@***. Laboratoire des Sciences du Climat et de l'Environnement LSCE CEA CNRS UVSQ Centre d'Etudes Orme de Merisiers Gif-sur-Yvette France. Department of Earth System Science Tsinghua University Beijing China. Department of Meteorology and Atmospheric Science The Pennsylvania State University University Park PA USA. Department of Earth System Science University of California Irvine 3232 Croul Hall Irvine CA USA. Division of Geological and Planetary Sciences California Institute of Technology Pasadena CA USA. Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology Nanjing China. Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China. Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. School of Environment Tsinghua University Beijing China. School of Mathematical School Tsinghua University Beijing China. Department of Mathematical Sciences Tsinghua University Beijing China. Center of Hubei Cooperative Innovation for Emissions Trading System Wuhan China. Institut Pierre-Simon Laplace Sorbonne Université / CNRS Paris France. Université Paris Dauphine Place du Maréchal de Lattre de Tassigny 75016 Paris France. Center for Energy and Environmental Policy Research Beijing Institute of Technology Beijing China. Department of Electrical Engineering the State Key Lab of Control and Simulation of Power Systems and Generation Equipment Institute for National Governance and G

A Correction to this paper has been published: https://***/10.1038/s41467-020-20254-5

关键词： Climate sciences Atmospheric science Environmental sciences Environmental social sciences

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An unsupervised hourly weather status pattern recognition and blending fitting model for PV system fault detection

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Applied Energy 2022年 319卷

作者： Jiaqi Qu Zheng Qian Yan Pei Lu Wei Hamidreza Zareipour Qiang Sun School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China School of Electronics and Information Engineering Beihang University Beijing China The Department of Electrical and Computer Engineering University of Calgary Calgary Canada State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China

Detecting PV system faults in a timely fashion is important to ensure the safe operation of equipment and reduce their impact on the economy of the PV systems. It is necessary to further improve the time-sensitive performance evaluation of the system. However, the hourly weather scenario segmentations are seldom considered during the hour-level online monitoring process. Therefore, a hybrid method based on unsupervised hourly weather status pattern recognition and blending fitting model is proposed for hourly fault detection to improve the performance evaluation of PV systems. The proposed solution includes three parts, firstly, in the data preprocessing stage, the measured power with the errors and noise under normal operation situation caused by the environment changes is corrected by monthly linear fitting. Secondly, an unsupervised hourly weather status pattern recognition method is constructed using the measured radiation data, including unsupervised clustering and the Multiclass-GBDT-LR classification process. Finally, after eliminating the anomalies and errors, the blending fitting model of the hourly sub-weather status is established. Through the analysis of power plants in Australia and China, the proposed solutions are validated and evaluated to be superior to existing data-driven solutions in terms of fitting accuracy, detection validity, and response time. Numerical results of case studies indicate that the developed methodology under sub-weather has improved the detection accuracy up to 97.71% and 99.29% compared to benchmark models.

关键词： Photovoltaic systems performance Hourly fault detection Unsupervised hourly weather status pattern recognition Blending fitting model

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Fault diagnosis for PV arrays considering dust impact based on transformed graphical features of characteristic curves and convolutional neural network with CBAM modules

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Applied Energy 2024年 355卷

作者： Jiaqi Qu Qiang Sun Zheng Qian Lu Wei Hamidreza Zareipour School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China School of Electronics and Information Engineering Beihang University Beijing China The Department of Electrical and Computer Engineering University of Calgary Calgary Canada

Various faults can occur during the operation of photovoltaic (PV) arrays, and both dust-affected operating conditions and various diode configurations complicate the faults. However, current methods for fault diagnosis based on I-V characteristic curves usually do not effectively use all the distinguishable information contained in the I-V curves or often rely on calibrating the field characteristic curves to standard test conditions (STC). It is difficult to apply these methods in practice and accurately identify multiple complex faults with similarities in different blocking diode configurations of PV arrays under the influence of dust. Therefore, a novel fault-diagnosis method for PV arrays that considers the impact of dust is proposed. In the pre-processing stage, the Isc-Voc normalized Gramian angular difference field (GADF) method is presented, which normalizes and transforms the resampled PV array characteristic curves from the field, including I-V and P-V, to obtain transformed graphical feature matrices. Subsequently, in the fault diagnosis stage, the convolutional neural network (CNN) model with convolutional block attention modules (CBAM) is designed to classify faults, which identifies complex fault types from the transformed graphical matrices containing complete discriminative fault information. In addition, the performances of different graphical feature transformation and CNN-based classification methods are compared using case studies. The results indicate that the developed method for PV arrays with different blocking diode configurations under various operating conditions has high fault diagnosis accuracy and reliability.

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Lithium Metal Anodes: A Triple-Gradient Host for Long Cycling Lithium Metal Anodes at Ultrahigh Current Density (Small 30/2020)

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Small 2020年第30期16卷

作者： TrungHieu Le Qinghua Liang Ming Chen Ciqing Yang Zhihao Yu Jie Cheng Feiyu Kang Ying Yang State Key Laboratory of Control and Simulation of Power System and Generation Equipments Tsinghua University Beijing 100084 China Department of Chemical Engineering The University of Melbourne Parkville VIC 3010 Australia Zhejiang Yuyuan Energy Storage Technology Co. Ltd. Huzhou 313100 China Laboratory of Advanced Materials Department of Materials Science and Engineering Tsinghua University Beijing 100084 China

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基于纳米金/介孔NiO/泡沫镍纳米复合材料的微型电极用于地下水重金属检测（英文）

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Engineering 2023年第8期 199-208页

作者： Boyuan Xue Qian Yang Kaidong Xia Zhihong Li George Y.Chen Dayi Zhang Xiaohong Zhou State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University National Key Laboratory of Science and Technology on Micro/Nano Fabrication Institute of Microelectronics Peking University Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things Guangdong and Hong Kong Joint Research Centre for Optical Fiber SensorsShenzhen University College of New Energy and Environment Jilin University The Research Institute of Environmental Innovation (Suzhou) Tsinghua University

Heavy metals, notably Pb2+and Cu2+, are some of the most persistent contaminants found in groundwater. Frequent monitoring of these metals, which relies on efficient, sensitive, cost-effective, and reliable methods, is a necessity. We present a nanocomposite-based miniaturized electrode for the concurrent measurement of Pb2+and Cu2+by exploiting the electroanalytical technique of square wave *** also propose a facile in situ hydrothermal calcination method to directly grow binder-free mesoporous Ni O on a three-dimensional nickel foam, which is then electrochemically seeded with gold nanoparticles（Au NPs）. The meticulous design of a low-barrier Ohmic contact between mesoporous Ni O and Au NPs facilitates target-mediated nanochannel-confined electron transfer within mesoporous Ni O. As a result, the heavy metals Pb2+(0.020 mg.L-1detection limit; 2.0–16.0 mg.L-1detection range)and Cu2+(0.013 mg.L-1detection limit; 0.4–12.8 mg.L-1detection range) can be detected simultaneously with high precision. Furthermore, other heavy metal ions and common interfering ions found in groundwater showed negligible impacts on the electrode's performance, and the recovery rate of groundwater samples varied between 96.3% ± 2.1% and 109.4% ± 0.6%. The compactness, flexible shape, low power consumption, and ability to remotely operate our electrode pave the way for onsite detection of heavy metals in groundwater, thereby demonstrating the potential to revolutionize the field of environmental monitoring.

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Magneto-Orientation of Magnetic Double Stacks for Patterned Anisotropic Hydrogels with Multiple Responses and Modulable Motions

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Angewandte Chemie 2022年第35期134卷

作者： Chen Fei Dai Olena Khoruzhenko Chengqian Zhang Qing Li Zhu Dejin Jiao Prof. Miao Du Prof. Josef Breu Prof. Peng Zhao Prof. Qiang Zheng Prof. Zi Liang Wu Ministry of Education Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and Engineering Zhejiang University Hangzhou 310027 China The State Key Laboratory of Fluid Power Transmission and Control Systems Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province School of Mechanical Engineering Zhejiang University Hangzhou 310028 China Bavarian Polymer Institute and Department of Chemistry University of Bayreuth Universitätsstrasse 30 95440 Bayreuth Germany

Reported here is a multi-response anisotropic poly( N -isopropylacrylamide) hydrogel developed by using a rotating magnetic field to align magnetic double stacks (MDSs) that are fixed by polymerization. The magneto-orientation of MDSs originates from the unique structure with γ-Fe 2 O 3 nanoparticles sandwiched by two silicate nanosheets. The resultant gels not only exhibit anisotropic optical and mechanical properties but also show anisotropic responses to temperature and light. Gels with complex ordered structures of MDSs are further devised by multi-step magnetic orientation and photolithographic polymerization. These gels show varied birefringence patterns with potentials as information materials, and can deform into specific configurations upon stimulations. Multi-gait motions are further realized in the patterned gel through dynamic deformation under spatiotemporal light and friction regulation by imposed magnetic force. The magneto-orientation assisted fabrication of hydrogels with anisotropic structures and additional functions should bring opportunities for gel materials in biomedical devices, soft actuators/robots, etc.

关键词： Anisotropic Hydrogels Ferronematic Liquid Crystals Magnetic Orientation Nanosheets Soft Robots

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Data-Dirven Method for Wake Effect Analysis on Nacelle Anemometer

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IOP Conference Series: Earth and Environmental Science 2020年第1期555卷

作者： Bo Jing Zheng Qian Tianyang Chen Yan Pei Dahai Kang School of Instrumentation and Optoelectronic Engineering Beihang University Haidian Dist. Beijing China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Haidian Dist. Beijing China CWP BLDG Haidian Dist. Beijing China

For most wind turbines, blade wakes affect the measurement of nacelle anemometer, result in the inconsistency between nacelle wind speed (NWS) and free stream wind speed, which seriously affects the power forecasting and performance evaluation of wind turbine. This paper proposes a data-driven method to analyse the wake effect on nacelle anemometer. At first, we use Relevance Vector Machine to establish a site calibration model between Lidar wind speed (LWS) and NWS. After that, we can use the calibrated LWS to replace the free stream wind speed, and wake effect on nacelle anemometer can be evaluated by comparing the calibrated LWS and NWS. Then, Wind Turbine power Curve (WTPC) is applied to make a detail analysis of wake effect on nacelle anemometer. The experimental results show that wake effect accelerates the air velocity behind the impeller. Therefore, WTPC fitted by NWS is 'lower' than the real one. However, SCADA system overcorrects the wake effect, thus WTPC fitted by SCADA data is 'higher' than the real power curve.

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state Estimation for Integrated Energy systems: Motivations, Advances, and Future Work

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IEEE Transactions on power systems 2024年

作者： Zhao, Junbo Srivastava, Ankur Guo, Ye Cetenovic, Dragan Lin, Yuzhang Levi, Victor Yin, Guanxiong Huang, Manyun Zhang, Tingting Li, Zhigang Chen, Yanbo Exposito, Antonio G. Zhang, Wen Zheng, Weiye Chakrabarti, Saikat Li, Yang Sharma, Ankush Kamwa, Innocent Guo, Qinglai Terzija, Vladimir Mili, Lamine University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States Tsinghua University Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China The University of Manchester Department of Eee ManchesterM13 9PL United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Čačak32000 Serbia New York University Department of Electrical and Computer Engineering NY11201 United States Tsinghua University Department of Electrical Engineering Beijing100084 China Hohai University College of Energy and Electrical Engineering Nanjing210098 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China The Chinese University of Hong Kong-Shenzhen School of Science and Engineering Shenzhen518172 China North China Electric Power University School of Electrical and Electronic Engineering Beijing102206 China University of Sevilla Spain Sevilla41092 Spain South China University of Technology School of Electrical Power Engineering Guangzhou510641 China Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur208016 India Northeast Electric Power University School of Electrical Engineering Jilin132012 China Laval University Department of Electrical and Computer Engineering QuebecQCG1V 0A6 Canada Tsinghua University State Key Laboratory of Power Systems Department of Electrical Engineering Beijing100084 China Newcastle University School of Engineering Newcastle upon TyneNE1 7RU United Kingdom Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering Falls ChurchVA22043 United States

This paper summarizes the technical activities of a three-year-long IEEE Task Force (TF) on state Estimation (SE) for Integrated Energy systems (IES). It presents the formal definition and characteristics of IES, along with the comprehensive discussion on Electric power systems (EPS) model, and static and dynamic models associated with heating and natural gas systems. The paper also identifies the barriers of SE for IES, such as estimation modeling, observability analysis, and measurement requirements, together with addressing multi-scale dynamics. An extensive comparative analysis between Integrated Energy systems-state Estimation (IES-SE) and more established Electric power System-state Estimation (EPS-SE) is presented. The paper also provides future research needs and directions related to IES-SE. © 1969-2012 IEEE.

关键词： power system analysis

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Research on phenol wastewater treatment by low-temperature multi-effect distillation combining with super-critical water oxidation

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IOP Conference Series: Earth and Environmental Science 2018年第1期208卷

作者： Cuijie Jia Bo Yuan Fengming Zhang Chuan He Chuangjian Su Jiulin Chen Key Laboratory of Low-grade Energy Utilization Technologies and Systems Chongqing University Ministry of Education of PRC Chongqing China Guangzhou Institutes of Advanced Technology Chinese Academy of Science Guangzhou China. State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing University Chongqing China. Postdoctoral Research Station of Power Engineering & Engineering Thermophysics Chongqing University Chongqing China.

Based on the mechanism of low-temperature multi-effect distillation combining with super-critical water oxidation (LT-MED&SCWO), a system that disposes phenol wastewater is introduced. Establishing a process of four-effect forward feed LT-MED concentrated phenol waste-water and a SCWO degradation of phenol by Aspen Plus software is essential to compare the effects of in-feed phenol mass concentration, system concentration ratio on phenol concentration ratio and mixing temperature of reaction required for degradation. The study shows that with the increase of in-feed phenol mass concentration, phenol concentration ratio keeps almost constant, 97.7%, but, preheating temperature of the concentrated water decreases when the final product mass phenol concentration is less than 0.5ppm; when system concentration ratio increases, phenol concentration ratio decreases from 99.5%to 96.7%and preheating temperature of the concentrated water also decreases when the final product mass phenol concentration is less than 0.5ppm.

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Human systems integration and advanced technology in engineering department workload and manpower reduction

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NAVAL ENGINEERS JOURNAL 2003年第1期115卷 57-65页

作者： Lively, KA Seman, AJ Kirkpatrick, M KENNETH A. LIVELY graduated from the University of Colorado with a BS in applied mathematics and an MS in mathematics in 1976 and from the Massachusetts Institute of Technology with an MS in electrical engineering and the degree ocean engineer in naval architecture and marine engineering in 1984. He retired from the U.S. Navy in 1989 after 23 years of service. Assignments included electrical officer on the USS Constellation (CV 64) project engineer for the DDG 51 machinery control system (NAVSEA) and DDG 51 Technical Director (NAVSEA). He was vice president of the PDI Division of Bird-Johnson Company from July 1989 to November 1998 where he managed various gas turbine and machinery controls related development projects. He joined Anteon Corporation's Systems Engineering Group as senior controls engineer in December 1998 where he provided technical support to the integrated power systems program (NAVSEA PMS 510) and managed the Office of Naval Research Afloat Laboratory. DR. MARK KIRKPATRICK is currently an independent consultant in human factors and work-load/manning analysis and modeling. He holds a Ph.D. degree in experimental psychology from The Ohio State University and has 34 years of experience in applied human factors. From 1982 through 2000 Dr. Kirkpatrick served as the senior vice president of Carlow International. Prior to joining Carlow in 1982 Dr. Kirkpatrick served as a member of the technical staff at North American Rockwell's Missiles Division and as a project director and vice president for Essex Corporation. His areas of expertise include workload simulation task analysis operator-in-the-loop simulation human performance experimentation statistical analysis and human factors T&E. He has directed and/or participated in human factors projects for the U.S. Navy U.S. Army NASA Department of Transportation the U.S. Nuclear Regulatory Commission and private industry. ANTHONY J. SEMAN III is the technical manager for the reduced ship's crew by virtual presence (RSVP) advanced technology d

Aboard current ships, such as the DDG 51, engineering control and damage control activities are manpower intensive. It is anticipated that, for future combatants, the workload demand arising from operation of systems under conditions of normal steaming and during casualty response will need to be markedly reduced via automated monitoring, autonomous control, and other technology initiatives. Current DDG 51 class ships can be considered as a manpower baseline and under Condition III typical engineering control involves seven to eight watchstanders at manned stations in the Central control Station, the engine rooms and other machinery spaces. In contrast to this manning level, initiatives such as DD 21 and the integrated engineering plant (IEP) envision a partnership between the operator and the automation system, with more and more of the operator's functions being shifted to the automation system as manning levels decrease. This paper describes some human systems integration studies of workload demand reduction and, consequently, manning reduction that can be achieved due to application of several advanced technology concepts. Advanced system concept studies in relation to workload demand are described and reviewed including. Piecemeal applications of diverse automation and remote control technology concepts to selected high driver tasks in current DDG 51 activities. Development of the reduced ship's crew by virtual presence system that will provide automated monitoring and display to operators of machinery health, compartment conditions, and personnel health. The IEP envisions the machinery control system as a provider of resources that are used by various consumers around the ship. Resource needs and consumer priorities are at all times dependent upon the ship's current mission and the availability of equipment pawnbrokers.

关键词： Naval warfare

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