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Sustainable Power and Energy Conference (iSPEC)

作者： Bin Cai Tianran Li Kui Wang Zhiyuan Li Lei Zhu Jun Wen Yusheng Xue State Key Laboratory of Smart Grid Protection and Control NARI Group Corporation/State Grid Electric Power Research Institute Nanjing China NARI School of Electrical and Automation Engineering Engineering Laboratory of Gas-Electricity Integrated Energy of Jiangsu Province Nanjing Normal University Nanjing China China Huaneng Group Co. Ltd Beijing China

ISBN: (纸本)9781665414401

The incentive policies for non-fossil energy are important factors affecting the investment behavior of generation companies (GENCOs). However, the investment behavior of different types of GENCOs in the system could be quite different, so the implementation of the policy must consider how to achieve incentive compatibility with the investment behavior of GENCOs. This article constructs a power transition simulation model that considers the investment behavior of GENCOs. Taking the wind power feed-in tariff policy as an example, it analyzes the impact of policy on the whole system’s low carbon transition pathway of the power structure and the evolution trajectory of system carbon emissions under different behavior scenarios.

关键词： Economics Analytical models Conferences Tariffs Carbon dioxide Companies Wind power generation

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Security boundaries of an optical power limiter for protecting quantum key distribution systems

arXiv

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arXiv 2023年

作者： Peng, Qingquan Gao, Binwu Zaitsev, Konstantin Wang, Dongyang Ding, Jiangfang Liu, Yingwen Liao, Qin Guo, Ying Huang, Anqi Wu, Junjie Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Automation Central South University Changsha410083 China China Greatwall Research Institute China Greatwall Technology Group Co. Ltd. Shenzhen518057 China Russian Quantum Center Skolkovo Moscow121205 Russia NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow119049 Russia Vigo Quantum Communication Center University of Vigo Vigo Spain Escuela de Ingeniería de Telecomunicación Department of Signal Theory and Communications University of Vigo Vigo Spain atlanTTic Research Center University of Vigo Vigo Spain College of Computer Science and Electronic Engineering Hunan University Changsha410082 China School of Computer Science Beijing University of Posts and Telecommunications Beijing100876 China

Unauthorized light injection has always been a vital threat to the practical security of a quantum key distribution (QKD) system. An optical power limiter (OPL) based on the thermo-optical defocusing effect has been proposed and implemented, limiting the injected hacking light. As a hardware countermeasure, the performance of the OPL under various light-injection attacks shall be tested to clarify the security boundary before being widely deployed. To investigate the OPL’s security boundary in quantum cryptography, we comprehensively test and analyse the behavior of OPL under continuous-wave (c.w.) light-injection attacks and pulse illumination attacks with pulses’ repetition rate at 0.5-Hz, 40-MHz, and 1-GHz. The testing results illuminate the security boundary of the OPL, which allows one to properly employ the OPL in the use cases. The methodology of testing and analysis proposed here is applicable to other power-limitation components in a QKD system. Copyright © 2023, The Authors. All rights reserved.

关键词： Pulse repetition rate

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Overall optimization of operation cost of the boiler and SCR in coal-fired power plants 3

Overall optimization of operation cost of the boiler and SCR...

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3rd International Conference on Energy, Electrical and Power engineering, CEEPE 2020

作者： Li, Wei Xu, Qiang Kong, Dean Zhao, Xiang Gao, Ning Lv, Xuguang Xinjiang Xinneng Group Co. LTD. Urumqi Electric Power Construction and Commissioning Institute Urumqi830013 China State Grid XinJiang Company Limited Electric Power Research Institute Urumqi830011 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China

Coal-fired power plants are usually equipped with selective catalytic reduction (SCR) systems to reduce nitrogen oxides (NOx) emissions. In this paper, we considered both the denitrification cost of the SCR system and the coal burning cost of the boiler to develop an operation cost model. Furthermore, the genetic algorithm was proposed to minimize the total operation cost by optimizing the feature parameters, including the primary air pressure, secondary air volume, overheated air volume, and NH3 injection volume. Simulation experiments were performed based on the operating data of a 1000 MW coal-fired power plant, with results showing that the total operating cost of the boiler and SCR was lowered. © Published under licence by IOP Publishing Ltd.

关键词： Coal fired power plant

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Learning Greenhouse Climate control Policy from Monitored Data

Learning Greenhouse Climate Control Policy from Monitored Da...

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Chinese automation Congress (CAC)

作者： Xiaoxuan Zhao Haoyu Wang Xiujuan Wang Udom Lewlomphaisarl Dong Li Jing Hua Mengzhen Kang The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Institute of Automation Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technologies Beijing China National Electronics and Computer Technology Center Pathum Thani Thailand Institute of Digital Agriculture Zhejiang Academy of Agricultural Sciences Hangzhou China Qingdao AgriTech Co. Ltd. Qingdao China

The knowledge of solar greenhouse growers on environment control plays an important role in greenhouse production and management. We proposed a way to extract the control strategies from the monitored data of greenhouses by building a long short-term memory (LSTM) model. The result is verified according to the real monitored data of a solar greenhouse, which shows that the model can learn the control strategy of a ventilator in the solar greenhouse. Through monitored data and models, the knowledge of greenhouse ventilation control can be learned, and automatic control can be achieved in a greenhouse with a similar configuration.

关键词： Ventilators Green buildings Buildings Production Ventilation Data models Data mining

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Risk Optimization and Sensitivity Analysis to Security and Stability control System with Routine Test Interval 5

Risk Optimization and Sensitivity Analysis to Security and S...

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5th International Conference on Power and Renewable Energy, ICPRE 2020

作者： Yan, Yunsong Sun, Ning Zhang, Nan Li, Shenghu Li, Mingying Wang, Dayang NARI Group Corporation State Grid Electric Power Research Institute Power Grid Security and Stability Control Technology Branch Nanjing China Hefei University of Technology School of Electrical Engineering and Automation Hefei China State Grid Jiangsu Electric Power Co. Ltd. Information Communication Branch Nanjing China

ISBN: (纸本)9781728190266

Interconnection of bulk power systems necessitates high reliability of Security Stability control System (SSCS). The routine test helps reduce the risk of unavailability of the SSCS. This paper newly proposed the optimization model to decide the optimal routine test interval, and the sensitivity model with respect to the upper/lower limits of the interval. At first, the fault tree and the state space models are derived for the SSCS. Then with the objective of reducing risk (and reducing economic loss), the equality constraints of the state probabilities, and the inequality constraints of the routine test interval and the cost, the optimization model to the interval is proposed. The Lagrange multipliers are found to describe the sensitivity of the objective function with respect to the limit of the intervals. Compared with repeated calculations, the proposed models are more efficient, and can deal with multiple parameters. The numerical results are given to show the application value of the proposed models. © 2020 IEEE.

关键词： Optimization

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A Learning Convolutional Neural Network Approach for Network Robustness Prediction

arXiv

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arXiv 2022年

作者： Lou, Yang Wu, Ruizi Li, Junli Wang, Lin Li, Xiang Chen, Guanrong The Department of Computing and Decision Sciences Lingnan University Hong Kong The Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The College of Computer Science Sichuan Normal University Chengdu610066 China The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201210 China The Department of Control Science and Engineering Tongji University Shanghai200240 China The Department of Electrical Engineering City University of Hong Kong Hong Kong

Network robustness is critical for various societal and industrial networks again malicious attacks. In particular, connectivity robustness and controllability robustness reflect how well a networked system can maintain its connectedness and controllability against destructive attacks, which can be quantified by a sequence of values that record the remaining connectivity and controllability of the network after a sequence of node- or edge-removal attacks. Traditionally, robustness is determined by attack simulations, which are computationally very time-consuming or even practically infeasible. In this paper, an improved method for network robustness prediction is developed based on learning feature representation using convolutional neural network (LFR-CNN). In this scheme, higher-dimensional network data are compressed to lower-dimensional representations, and then passed to a CNN to perform robustness prediction. Extensive experimental studies on both synthetic and real-world networks, both directed and undirected, demonstrate that 1) the proposed LFR-CNN performs better than other two state-of-the-art prediction methods, with significantly lower prediction errors;2) LFR-CNN is insensitive to the variation of the network size, which significantly extends its applicability;3) although LFR-CNN needs more time to perform feature learning, it can achieve accurate prediction faster than attack simulations;4) LFR-CNN not only can accurately predict network robustness, but also provides a good indicator for connectivity robustness, better than the classical spectral measures. © 2022, CC BY.

关键词： Complex networks

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What are the differences in yield formation among two cucumber (Cucumis sativus L.) cultivars and their F1 hybrid?

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Journal of Integrative Agriculture 2020年第7期19卷 1789-1801页

作者： WANG Xiu-juan KANG Meng-zhen FAN Xing-rong YANG Li-li ZHANG Bao-gui HUANG San-wen Philippe DE REFFYE WANG Fei-yue The State Key Laboratory of Management and Control for Cormplex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190P.R.China Bejjing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of SciencesBejing 100190P.R.China Innovation Center for Parallel Agriculture Qingdao Academy of Intelligent IndustriesQingdao 266109P.R.China School of Computer Science and Information Engineering Chongqing Technology and Business UniversityChongqing 400067P.R.China College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083P.R.China College of Land Science and Technology China Agricultural UniversityBeijing 100193P.R.China Agricultural Genomes Institute at Shenzhen Chinese Academy of Agricultural SciencesShenzhen 518124P.R.China AMAP University MontpellierCIRADCNRSINRAIRDMontpellier 34000France The School of Computer and Control Engineering University of Chinese Academy of SciencesBeijing 100049P.R.China

To elucidate the mechanisms underlying the differences in yield formation among two parents(P1 and P2) and their F1 hybrid of cucumber, biomass production and whole source–sink dynamics were analyzed using a functional–structural plant model(FSPM) that simulates both the number and size of individual organs. Observations of plant development and organ biomass were recorded throughout the growth periods of the plants. The GreenLab Model was used to analyze the differences in fruit setting, organ expansion, biomass production and biomass allocation. The source–sink parameters were estimated from the experimental measurements. Moreover, a particle swarm optimization algorithm(PSO) was applied to analyze whether the fruit setting is related to the source–sink ratio. The results showed that the internal source–sink ratio increased in the vegetative stage and reached a peak until the first fruit setting. The high yield of hybrid F1 is the compound result of both fruit setting and the internal source–sink ratio. The optimization results also revealed that the incremental changes in fruit weight result from the increases in sink strength and proportion of plant biomass allocation for fruits. The model-aided analysis revealed that heterosis is a result of a delicate compromise between fruit setting and fruit sink strength. The organlevel model may provide a computational approach to define the target of breeding by combination with a genetic model.

关键词： cucumber biomass production functional-structural plant model source-sink ratio fruit-setting PSO heterosis

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Simulation and analysis of high-reliability braking system of aircraft based on self-feed energy nonsimilar margin

Simulation and analysis of high-reliability braking system o...

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CSAA/IET International Conference on Aircraft Utility Systems 2020, AUS 2020

作者： Wang, Xiyu Shang, Yaoxing Hu, Haiying Qiu, Binghui Teng, Fengjian Zhang, Hao Jiao, Zongxia Liu, Xiaochao School of Automation Science and Electrical Engineering Beihang University Beijing100191 China AVIC Jiangxi Hongdu Aviation Industry Group Company Ltd Nanchang330000 China Beijing Aeronautical Technology Research Center Beijing100076 China Aerospace System Engineering Shanghai Shanghai201109 China Research Institute for Frontier Science Beihang University Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Ningbo Institute of Technology Beihang University Ningbo315800 China

ISBN: (纸本)9781839535635

As one of the key and important airborne systems, aircraft braking systems mostly use traditional centralized hydraulic sources. With the new concept of "multi-electric aircraft", the aircraft energy supply system has further branched. This article introduces an integrated hydraulic brake device. It does not require an on-board hydraulic source, and can directly convert the energy of the wheel rotation when the aircraft lands, to complete the braking function. Using Simulink/SimHydraulics module, a corresponding model of aircraft brake integrated hydraulic device was established. The function of this self-feeding hydraulic brake device was verified through simulation and analysis. This method provides a new way to further study the braking system. © 2020 Institution of engineering and Technology. All rights reserved.

关键词： Electric aircraft

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A Precise Carbon Emission Model on Electricity Consumption Side with Carbon Emission Flow Theory

A Precise Carbon Emission Model on Electricity Consumption S...

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Electrical engineering and control Technologies (CEECT), Conference on

作者： Daxin Wang Qian Zhang Huahu Cui Honghu Cheng Xuemeng Zhang Lei Fan School of Electrical Engineering and Automation Engineering Research Center of Power Quality Ministry of Education Anhui University Hefei China Anhui Key Laboratory of Industrial Energy-Saving and Safety Anhui University Hefei China Anhui Power Exchange Center Co. Ltd. Hefei China China Energy Engineering Group Anhui Electric Power Design Institute co. LTD. Hefei China Anhui Collaborative Innovation Center of Industrial Energy-Saving and Power Quality Control Anhui University Hefei China

ISBN: (纸本)9781665499002

The measurement of carbon emissions on the customer side is a prerequisite for low-carbon dispatch and carbon trading, and the calculation of carbon emissions per kWh is a necessary condition for building a low-carbon power system. In this paper, we propose a refined measurement model for customer-side carbon emissions based on the carbon emission stream theory. Firstly, the tidal flow distribution in the distribution network is calculated by using the forward-back substitution method with distributed power sources. Secondly, the carbon potential vector, carbon potential factor, and correlation matrix of carbon flow at the distribution network side are calculated. According to the obtained calculation results, a fine-grained carbon emission calculation model for distribution network side including PV and energy storage is proposed to be constructed on the bases of carbon emission flow theory. This model can delineate the correlation between the carbon emissions of the generating units and the carbon flows of each load on the user side. Finally, the IEEE33 node and a 10 kV feeder model of a station area in Anhui Province are chosen as simulation objects. The adaptability and calculation speed of the distribution-side carbon flow calculation model is analyzed. The results show that the calculation model in this paper can solve the distribution-side carbon flow with energy storage and distributed power sources quickly and accurately.

关键词： Adaptation models Correlation Power measurement Carbon dioxide Distribution networks Power systems Carbon

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A consensus protocol for functional connectivity analysis in the rat brain (vol 26, pg 673, 2023)

引用

NATURE NEUROSCIENCE 2023年第6期26卷 1127-1128页

作者： Grandjean, Joanes Desrosiers-Gregoire, Gabriel Anckaerts, Cynthia Angeles-Valdez, Diego Ayad, Fadi Barriere, David A. Blockx, Ines Bortel, Aleksandra Broadwater, Margaret Cardoso, Beatriz M. Celestine, Marina Chavez-Negrete, Jorge E. Choi, Sangcheon Christiaen, Emma Clavijo, Perrin Colon-Perez, Luis Cramer, Samuel Daniele, Tolomeo Dempsey, Elaine Diao, Yujian Doelemeyer, Arno Dopfel, David Dvorakova, Lenka Falfan-Melgoza, Claudia Fernandes, Francisca F. Fowler, Caitlin F. Fuentes-Ibanez, Antonio Garin, Clement M. Gelderman, Eveline Golden, Carla E. M. Guo, Chao C. G. Henckens, Marloes J. A. G. Hennessy, Lauren A. Herman, Peter Hofwijks, Nita Horien, Corey Ionescu, Tudor M. Jones, Jolyon Kaesser, Johannes Kim, Eugene Lambers, Henriette Lazari, Alberto Lee, Sung-Ho Lillywhite, Amanda Liu, Yikang Liu, Yanyan Y. Lopez-Castro, Alejandra Lopez-Gil, Xavier Ma, Zilu MacNicol, Eilidh Madularu, Dan Mandino, Francesca Marciano, Sabina McAuslan, Matthew J. McCunn, Patrick McIntosh, Alison Meng, Xianzong Meyer-Baese, Lisa Missault, Stephan Moro, Federico Naessens, Daphne M. P. Nava-Gomez, Laura J. Nonaka, Hiroi Ortiz, Juan J. Paasonen, Jaakko Peeters, Lore M. Pereira, Mickael Perez, Pablo D. Pompilus, Marjory Prior, Malcolm Rakhmatullin, Rustam Reimann, Henning M. Reinwald, Jonathan Del Rio, Rodrigo Triana Rivera-Olvera, Alejandro Ruiz-Perez, Daniel Russo, Gabriele Rutten, Tobias J. Ryoke, Rie Sack, Markus Salvan, Piergiorgio Sanganahalli, Basavaraju G. Schroeter, Aileen Seewoo, Bhedita J. Selingue, Erwan Seuwen, Aline Shi, Bowen Sirmpilatze, Nikoloz Smith, Joanna A. B. Smith, Corrie Sobczak, Filip Stenroos, Petteri J. Straathof, Milou Strobelt, Sandra Sumiyoshi, Akira Takahashi, Kengo Torres-Garcia, Maria E. Tudela, Raul van den Berg, Monica van der Marel, Kajo van Hout, Aran T. B. Vertullo, Roberta Vidal, Benjamin Vrooman, Roel M. Wang, Victora X. Wank, Isabel Watson, David J. G. Yin, Ting Zhang, Yongzhi Zurbruegg, Stefan Achard, Sophie Alcauter, Sarael Auer, Dorothee P. Barbier, Emmanuel L. Baudewig, Juergen Beckmann, Chri Donders Institute for Brain Behaviour and Cognition Radboud University Nijmegen The Netherlands Department for Medical Imaging Radboud University Medical Center Nijmegen The Netherlands Cerebral Imaging Centre Douglas Mental Health University Institute Verdun QC Canada Integrated Program in Neuroscience McGill University Montreal QC Canada Bio-imaging Lab University of Antwerp Antwerp Belgium µNEURO Research Centre of Excellence University of Antwerp Antwerp Belgium Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro Mexico Biological and Biomedical Engineering McGill University Montreal QC Canada McConnell Brain Imaging Centre McGill University Montreal QC Canada Montreal Neurological Institute McGill University Montreal QC Canada UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction Physiologie de la reproduction et des comportements Centre de recherche INRAE de Nouzilly Tours France Department of Neurology and Neurosurgery McGill University Montreal QC Canada Center for Animal MRI University of North Carolina at Chapel Hill Chapel Hill NC USA Department of Neurology University of North Carolina at Chapel Hill Chapel Hill NC USA Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA Preclinical MRI Champalimaud Research Champalimaud Centre for the Unknown Lisbon Portugal Laboratoire des Maladies Neurodégénératives Molecular Imaging Research Center (MIRCen) Université Paris-Saclay Commissariat à l’Énergie Atomique et aux Énergies Alternatives (CEA) CNRS Fontenay-aux-Roses France Departamento de Neurobiología Conductual y Cognitiva Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro México Translational Neuroimaging and Neural Control Group High-Field Magnetic Resonance Max Planck Institute for Biological Cybernetics Tuebingen Germany Graduate Training Centre of Neuroscience International Max

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.

关键词： Databases Neural circuits

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