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Multi-machine equivalent model parameter identification method for double-fed induction generator (DFIG)-based wind power plant based on measurement data

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The Journal of Engineering 2017年第13期2017卷 1550-1554页

作者： Kui Luo Wenhui Shi Jixian Qu State Key Laboratory of Operation and Control of Renewable Energy and Storage System Renewable Energy Research Center China Electric Power Research Institute (CEPRI) Beijing 100192 People's Republic of China

Dynamic equivalent modelling for wind power plant (WPP) has become an important tool to analyse the grid integration characteristics of large-scale WPPs. Owing to the large differences of operational performance between wind turbines, multi-machine equivalent model is more accurate to represent the WPP. In order to determine the generator parameters of multi-machine equivalent model, this study proposed a multi-machine equivalent model parameter identification method for DFIG-based WPP only with data measured at the point of common coupling. On the basis of established clustering model, it is explained how the measurement data are properly processed for use as the input of parameter identification considering the collecting circuit and the estimated instantaneous power of equivalent wind turbine. The developed parameter determination method is tested against a large-scale plant model, and simulation results confirm the effectiveness of the method.

关键词： wind power plants parameter estimation power grids asynchronous generators wind turbines power generation control multimachine equivalent model parameter identification method wind power plant measurement data dynamic equivalent modelling WPP established clustering model equivalent wind turbine developed parameter determination method large-scale plant model

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The Rapid Development of Three-phase Grid-forming Micro-source Inverter Based on SMC and PI control

The Rapid Development of Three-phase Grid-forming Micro-sour...

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2017 International Electrical and Energy Conference (CIEEC 2017)

作者： Jing Bian Chuanzhi Zang Xianhong Li Bo Hu Jun Liu Key Laboratory of Industrial Control Network and System Shenyang Institute of Automation Chinese Academy of Sciences State Grid Huludao Power Supply Company State Grid Anshan Power Supply Company

The rapid development process of a proposed three-phase grid-forming micro-source inverter is presented in the *** mode control(SMC) and PI control strategies are adopted synthetically to implement the dual closed-loop *** order to avoid the repeated selection of control parameters,the particle swarm optimization(PSO) algorithm is applied for parameters' *** results certificate the correctness of the proposed *** then,the automatic generation of control codes is realized based on the model design *** actual hardware experiments corresponding to the simulation ones are presented in the *** results demonstrate that the inverter based on the rapid development is effective and the proposed controller performs better robustness property over conventional PI-based control strategy.

关键词： grid-forming micro-source inverter sliding mode control PI control particle swarm optimization model design method

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Correction to: 2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales

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Archives of virology 2021年第12期166卷 3567-3579页

作者： Jens H Kuhn Scott Adkins Bernard R Agwanda Rim Al Kubrusli Sergey V Alkhovsky Gaya K Amarasinghe Tatjana Avšič-Županc María A Ayllón Justin Bahl Anne Balkema-Buschmann Matthew J Ballinger Christopher F Basler Sina Bavari Martin Beer Nicolas Bejerman Andrew J Bennett Dennis A Bente Éric Bergeron Brian H Bird Carol D Blair Kim R Blasdell Dag-Ragnar Blystad Jamie Bojko Wayne B Borth Steven Bradfute Rachel Breyta Thomas Briese Paul A Brown Judith K Brown Ursula J Buchholz Michael J Buchmeier Alexander Bukreyev Felicity Burt Carmen Büttner Charles H Calisher Mengji Cao Inmaculada Casas Kartik Chandran Rémi N Charrel Qi Cheng Yuya Chiaki Marco Chiapello Il-Ryong Choi Marina Ciuffo J Christopher S Clegg Ian Crozier Elena Dal Bó Juan Carlos de la Torre Xavier de Lamballerie Rik L de Swart Humberto Debat Nolwenn M Dheilly Emiliano Di Cicco Nicholas Di Paola Francesco Di Serio Ralf G Dietzgen Michele Digiaro Olga Dolnik Michael A Drebot J Felix Drexler William G Dundon W Paul Duprex Ralf Dürrwald John M Dye Andrew J Easton Hideki Ebihara Toufic Elbeaino Koray Ergünay Hugh W Ferguson Anthony R Fooks Marco Forgia Pierre B H Formenty Jana Fránová Juliana Freitas-Astúa Jingjing Fu Stephanie Fürl Selma Gago-Zachert George Fú Gāo María Laura García Adolfo García-Sastre Aura R Garrison Thomas Gaskin Jean-Paul J Gonzalez Anthony Griffiths Tony L Goldberg Martin H Groschup Stephan Günther Roy A Hall John Hammond Tong Han Jussi Hepojoki Roger Hewson Jiang Hong Ni Hong Seiji Hongo Masayuki Horie John S Hu Tao Hu Holly R Hughes Florian Hüttner Timothy H Hyndman M Ilyas Risto Jalkanen Dàohóng Jiāng Gilda B Jonson Sandra Junglen Fujio Kadono Karia H Kaukinen Michael Kawate Boris Klempa Jonas Klingström Gary Kobinger Igor Koloniuk Hideki Kondō Eugene V Koonin Mart Krupovic Kenji Kubota Gael Kurath Lies Laenen Amy J Lambert Stanley L Langevin Benhur Lee Elliot J Lefkowitz Eric M Leroy Shaorong Li Longhui Li Jiànróng Lǐ Huazhen Liu Igor S Lukashevich Piet Maes William Marciel de Souza Marco Marklewitz Sergio H Marshall Shin-Yi L Marzano Se Integrated Research Facility at Fort Detrick National Institute of Allergy and Infectious Diseases National Institutes of Health Frederick MD USA. kuhnjens@mail.nih.gov. United States Department of Agriculture Agricultural Research Service US Horticultural Research Laboratory Fort Pierce FL USA. Zoology Department National Museums of Kenya Nairobi Kenya. Jomo Kenyatta University of Agriculture & Technology Nairobi Kenya. Division Phytomedicine Faculty of Life Sciences Humboldt-Universität zu Berlin Berlin Germany. D.I. Ivanovsky Institute of Virology of N.F. Gamaleya National Center on Epidemiology and Microbiology of Ministry of Health of Russian Federation Moscow Russia. Department of Pathology and Immunology Washington University School of Medicine St. Louis MO USA. Faculty of Medicine University of Ljubljana Ljubljana Slovenia. Centro de Biotecnología y Genómica de Plantas Universidad Politécnica de Madrid-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria Campus de Montegancedo Pozuelo de Alarcón Madrid Spain. Departamento de Biotecnología-Biología Vegetal Escuela Técnica Superior de Ingeniería Agronómica Alimentaria y de Biosistemas Universidad Politécnica de Madrid Madrid Spain. Center for Ecology of Infectious Diseases Department of Infectious Diseases Department of Epidemiology and Biostatistics Insitute of Bioinformatics University of Georgia Athens GA USA. Institute of Novel and Emerging Infectious Diseases Friedrich-Loeffler-Institut Federal Research Institute for Animal Health Greifswald-Insel Riems Germany. Department of Biological Sciences Mississippi State University Mississippi State MS USA. Center for Microbial Pathogenesis Institute for Biomedical Sciences Georgia State University Atlanta GA USA. Edge BioInnovation Consulting and Mgt Frederick MD USA. Institute of Diagnostic Virology Friedrich-Loeffler-Institut Greifswald-Insel Riems Germany. UFyMA INTA-CONICET Cordoba Argentina. Genomics and Bioinformatics D

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Hydraulic Character Modeling and Vehicle Stability control Algorithm for EHB system of Passenger Car

Hydraulic Character Modeling and Vehicle Stability Control A...

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SAE 2016 World Congress and Exhibition

作者： Zheng, Hongyu Ma, Shenao ASCL Jilin Univ. China State Key Laboratory of Automotive Simulation and Control Jilin University Changchun130025 China

As a new braking system, EHB can significantly improve the braking performance and vehicle handling and stability. In this paper the structure of high-speed on-off valve and the valve core principle are discussed, the paper also analysis the response of the valve core under different modulation frequency, duty cycle and the change of wheel cylinder pressure. Set a proper modulation frequency to make sure that electromagnetic valve can be worked in a greater linear range. While modeling, the response time will be incorporated into the electromagnetic valve opening or closing time, through the simulation analysis of restricting the duty cycle of electromagnetic valve or not, in the spool in a certain relative displacement standard conditions, the electromagnetic valve duty cycle may not be restricted due to the spool in a certain relative displacement to amend the solenoid valve lag time because of simplifying the process of modeling electromagnetic with neglecting lag time to ensure that the duty cycle of solenoid valve is set under the conditions of not work in their death or saturation region. Based on vehicle dynamic stability control theory, a control strategies and algorithms were established combined with structural characteristics of EHB hydraulic system. Reference to vehicle linear model with vehicle model, an additional vehicle yaw torque is decided by comparing vehicle actual state to normal one. By translating to the torque into the corresponding additional wheel brake pressure, wheel cylinder pressure is controlled in closed-loop from getting pressure sensor information which provided by pressure sensor in wheel cylinder. © Copyright 2016 SAE International.

关键词： Solenoid valves

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A bi-level trading model for an active distribution company considering demand response exchange

A bi-level trading model for an active distribution company ...

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2016 IEEE PES Asia Pacific Power and Energy Engineering Conference, APPEEC 2016

作者： Cai, Yu Lin, Jin Wan, Can Song, Yonghua Department of Electrical Engineering State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Tsinghua University Beijing China

ISBN: (纸本)9781509054183

With widely utilization of distributed generations (DGs) and demand response (DR), the active distribution network (ADN) becomes a more proactive and strategic consumer in electricity markets to procure its energy needs at the minimum cost. Under this background, this paper proposes a bi-level trading model for a strategic ADN to minimize its operation cost in the day-ahead market. The upper level model represents the cost minimization of the ADN energy acquisition with consideration of DR, and the lower level model includes the day-ahead market clearing. Based on the complementarity theory and linearization techniques, the proposed bi-level model can be transformed into a mixed integer linear programming (MILP) problem. Comprehensive case studies demonstrate the efficiency and effectiveness of the proposed strategic trading model for an ADisCo with DGs and DR with respect to nonstrategic bidding approaches. © 2016 IEEE.

关键词： Distributed power generation

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Research on capacity configuration method of concentrated reactive power compensator for wind farm LVRT capability

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The Journal of Engineering 2017年第13期2017卷 2428-2432页

作者： Jing He Qing Li Jing Ma Weibo Zhang Yu Zhao State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing People's Republic of China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing People's Republic of China

In order to fulfil the requirement for low-voltage ride-through (LVRT) capability, the wind farms need to inject the reactive currents during grid fault to support voltage recovery. As the main concentrated reactive power compensator, the static var generators (SVGs) are widely employed in the wind farm for reactive current injection. This study investigates the dynamic reactive currents of the wind turbine based on the field-test data during the grid faults. Then, the scheme that taking wind turbines as main reactive current sources and SVG as compensator is adopted to realise the wind farm LVRT capability. According to this scheme, the capacity configuration method of SVG is developed, which can be used to design SVG capacity to improve the wind farm dynamic reactive current behaviour. Finally, the simulation results are provided to demonstrate the effectiveness and the availability of the proposed method.

关键词： static VAr compensators power system faults power system stability wind power plants power grids wind turbines reactive power control reactive power main concentrated reactive power compensator reactive current injection dynamic reactive currents wind turbine grid fault main reactive current sources wind farm LVRT capability capacity configuration method SVG capacity wind farm dynamic reactive current behaviour low-voltage ride-through capability voltage recovery

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Fuel Cycle Environmental Assessment for Electric Vehicles in China

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IOP Conference Series: Earth and Environmental Science 2018年第4期186卷

作者： Shuhua Li Qinxing Cao Jun Li Ying Gao Department of Vehicle Engineering Hefei University of Technology Hefei Anhui 230009 PR China State Key Laboratory of Automotive Simulation & Control Jilin University Changchun Jilin 130025 PR China

Electric vehicles (EVs) offer the potential for substantial reductions in energy consumption and emissions during the vehicle traveling stage. In considering these benefits, it is important to address concerns of environmental problem-shifting. In addition, while praise has focused on the use phase in comparing transportation options, the power source production is also significant when comparing conventional and EVs. This study develops and provides a life cycle inventory of EVs and applies the inventory to assess the fuel cycle energy consumption and greenhouse gas emissions of the EVs and the internal combustion engine vehicles (ICEVs). The results show that EVs powered by the present China electricity mix offer a 48% decrease in energy use and a 38% decrease in global warming potential (GWP) relative to conventional gasoline vehicles.

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Driver behaviour characteristics identification strategies based on the bionic intelligent algorithms

Driver behaviour characteristics identification strategies b...

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IET International Conference on Intelligent and Connected Vehicles, ICV 2016

作者： Zhu, Bing Liu, Zhipeng Zhao, Jian Chen, Yizhou Deng, Weiwen State Key Laboratory of Automotive Simulation and Control Jilin University Changchun130022 China Key Laboratory of Bionic Engineering of Ministry of Education Jilin University Changchun130022 China

ISBN: (纸本)9781785618260

The identification strategies of driver behaviour characteristics based on the bionic intelligent algorithms are introduced in this paper. First, a driver behaviour data acquisition system is established based on the dSPACE simulation platform. Then, in order to recognize the characteristics of driver behaviour, the preview optimal curvature model is chosen as the ideal driver behaviour model. This model consists of two parts as the vehicle model and the driver model. The vehicle model parameters are identified by least square method, and the driver model parameters that could represent different types of driver behaviours are identified through genetic algorithm and particle swarm optimization method. Finally, simulations are carried out to verify the identification strategies by Carsim and Matlab/Simulink. As compared the identified results with the real driver behaviour data, there is a high similarity between them, which means the driver behaviour characteristics that have been identified are very precise and reliable.

关键词： Genetic algorithms

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Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries (vol 55, pg 89, 2023)

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NATURE GENETICS 2023年第3期55卷 519-520页

作者： Fernandez-Rozadilla, Ceres Timofeeva, Maria Chen, Zhishan Law, Philip Thomas, Minta Schmit, Stephanie Diez-Obrero, Virginia Hsu, Li Fernandez-Tajes, Juan Palles, Claire Sherwood, Kitty Briggs, Sarah Svinti, Victoria Donnelly, Kevin Farrington, Susan Blackmur, James Vaughan-Shaw, Peter Shu, Xiao-ou Long, Jirong Cai, Qiuyin Guo, Xingyi Lu, Yingchang Broderick, Peter Studd, James Huyghe, Jeroen Harrison, Tabitha Conti, David Dampier, Christopher Devall, Mathew Schumacher, Fredrick Melas, Marilena Rennert, Gad Obon-Santacana, Mireia Martin-Sanchez, Vicente Moratalla-Navarro, Ferran Oh, Jae Hwan Kim, Jeongseon Jee, Sun Ha Jung, Keum Ji Kweon, Sun-Seog Shin, Min-Ho Shin, Aesun Ahn, Yoon-Ok Kim, Dong-Hyun Oze, Isao Wen, Wanqing Matsuo, Keitaro Matsuda, Koichi Tanikawa, Chizu Ren, Zefang Gao, Yu-Tang Jia, Wei-Hua Hopper, John Jenkins, Mark Win, Aung Ko Pai, Rish Figueiredo, Jane Haile, Robert Gallinger, Steven Woods, Michael Newcomb, Polly Duggan, David Cheadle, Jeremy Kaplan, Richard Maughan, Timothy Kerr, Rachel Kerr, David Kirac, Iva Bohm, Jan Mecklin, Lukka-Pekka Jousilahti, Pekka Knekt, Paul Aaltonen, Lauri Rissanen, Harri Pukkala, Eero Eriksson, Johan Cajuso, Tatiana Hanninen, Ulrika Kondelin, Johanna Palin, Kimmo Tanskanen, Tomas Renkonen-Sinisalo, Laura Zanke, Brent Mannisto, Satu Albanes, Demetrius Weinstein, Stephanie Ruiz-Narvaez, Edward Palmer, Julie Buchanan, Daniel Platz, Elizabeth Visvanathan, Kala Ulrich, Cornelia Siegel, Erin Brezina, Stefanie Gsur, Andrea Campbell, Peter Chang-Claude, Jenny Hoffmeister, Michael Brenner, Hermann Slattery, Martha Potter, John Tsilidis, Konstantinos Schulze, Matthias Gunter, Marc Murphy, Neil Castells, Antoni Castellvi-Bel, Sergi Moreira, Leticia Arndt, Volker Shcherbina, Anna Stern, Mariana Pardamean, Bens Bishop, Timothy Giles, Graham Southey, Melissa Idos, Gregory McDonnell, Kevin Abu-Ful, Zomoroda Greenson, Joel Shulman, Katerina Lejbkowicz, Flavio Offit, Kenneth Su, Yu-Ru Steinfelder, Robert Keku, Temitope van Guelpen, Bethany Hudson, Thomas Hampel, Heather Pearlman, Edinburgh Cancer Research Centre Institute of Genomics and Cancer University of Edinburgh Edinburgh UK Genomic Medicine Group Instituto de Investigacion Sanitaria de Santiago Santiago de Compostela Spain Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham UK Colon Cancer Genetics Group Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK Danish Institute for Advanced Study Department of Public Health University of Southern Denmark Odense Denmark Department of Pathology National University Hospital National University Health System Singapore Singapore Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University Medical Center Nashville TN USA Department of Biomedical Informatics Vanderbilt University School of Medicine Nashville TN USA Division of Genetics and Epidemiology Institute of Cancer Research London UK Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle WA USA Department of Biostatistics School of Public Health University of Washington Seattle WA USA School of Public Health University of Washington Seattle WA USA Research Centre for Hauora and Health Massey University Wellington New Zealand Department of Epidemiology University of Washington School of Public Health Seattle WA USA Division of Research Kaiser Permanente Northern California Oakland CA USA Department of Biostatistics University of Washington Seattle WA USA Department of Epidemiology University of Washington Seattle WA USA Genomic Medicine Institute Cleveland Clinic Cleveland OH USA Population and Cancer Prevention Program Case Comprehensive Cancer Center Cleveland OH USA Colorectal Cancer Group ONCOBELL Program Bellvitge Biomedical Research Institute Barcelona Spain Oncology Data Analytics Program Catalan Institute of Oncology Barcelona S

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.

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The Delicate Analysis of Short–Term Load Forecasting

The Delicate Analysis of Short–Term Load Forecasting

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2017 2nd Asia Conference on Power and Electrical Engineering (ACPEE2017)

作者： Changwei Song Yuan Zheng Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University State Grid Jiangxi Electric Power Company Jiujiang Electric Power Supply Company

This paper proposes a new method for short-term load forecasting based on the similar day method, correlation coefficient and Fast Fourier Transform(FFT) to achieve the precision analysis of load variation from three aspects(typical day, correlation coefficient, spectral analysis) and three dimensions(time dimension, industry dimensions, the main factors influencing the load characteristic such as national policies, regional economic, holidays, electricity and so on). First, the branch algorithm one-class-SVM is adopted to selection the typical day. Second, correlation coefficient method is used to obtain the direction and strength of the linear relationship between two random variables, which can reflect the influence caused by the customer macro policy and the scale of production to the electricity price. Third, Fourier transform residual error correction model is proposed to reflect the nature of load extracting from the residual error. Finally, simulation result indicates the validity and engineering practicability of the proposed method.

关键词： Fourier FFT Term Load Forecasting The Delicate Analysis of Short

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