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Dynamic event-triggered formation control of second-order nonholonomic systems

Journal of systems Engineering and Electronics 2023年第2期34卷 501-514页

作者： WANG Xiaoyu SUN Sijia XIAO Feng YU Mei School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China

In this paper,the formation control problem of secondorder nonholonomic mobile robot systems is investigated in a dynamic event-triggered ***-triggered control protocols combined with persistent excitation(PE)conditions are *** event-detecting processes,an inactive time is introduced after each sampling instant,which can ensure a positive minimum sampling *** increase the flexibility of the event-triggered scheme,internal dynamic variables are included in event-triggering ***,the dynamic event-triggered scheme plays an important role in increasing the lengths of time intervals between any two consecutive *** addition,event-triggered control protocols without forward and angular velocities are also presented based on approximate-differentiation(low-pass)*** asymptotic convergence results are given based on a nested Matrosov theorem and artificial sampling methods.

关键词： nonholonomic system dynamic event-triggered control consensus-based formation

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Advanced modeling of the absorption enhancement of black carbon particles in chamber experiments by considering the morphology and coating thickness

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Frontiers of Environmental Science & Engineering 2024年第9期18卷 129-142页

作者： Xiaodong Wei Jianlin Hu Chao Liu Xiaodong Xie Junjie Yin Song Guo Min Hu Jianfei Peng Huijun Wang Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science&TechnologyNanjing 210044China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Key Laboratory of Meteorological Disaster(Ministry of Education)Nanjing University of Information Science and TechnologyNanjing 210044China Nansen−Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China East China Air Traffic Management Bureau CAAC Shanghai 200335China State Key Joint Laboratory of Environmental Simulation and Pollution Control International Joint Laboratory for Regional Pollution Control(IJRC)(Ministry of Education)College of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China Tianjin Key Laboratory of Urban Transport Emission Research&State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control College of Environmental Science and EngineeringNankai UniversityTianjin 300071China

Measurements studies have shown that the absorption of radiation by black carbon(BC)increases as the particles ***,there are significant discrepancies between the measured and modeled absorption enhancement(E_(abs)),largely due to the simplifications used in modeling the mixing states and shape *** took advantage of chamber experiments on BC aging and developed an efficient method to resolve the particle shape based on the relationship between the coating fraction(ΔD_(ve)/D_(ve),0)and fractal dimension(D_(f)),which can also reflect the variations of D_(f)during the whole BC aging *** with externally and partly mixed states(0≤ΔD_(ve)/D_(ve),0≤0.5)can be considered to be uniformly distributed with the D_(f)values of 1.8–2.1,whereas the Df values are constrained in the range 2.2–2.8 for fully mixed states(ΔD_(ve)/D_(ve),0>0.5).The morphological parameters(i.e.,the effective density and the dynamic shape factor)were compared with the measured values to verify the simulated *** simulated mean deviations of morphological parameters were smaller than 8%for the method resolving the particle *** applying a realistic shape and refractive index,the mass absorption cross for fully mixed states can be improved by 11%compared with a simplified core–shell *** on our understanding of the influence of D_(f)andΔD_(ve)/D_(ve),0 on E_(abs),we propose a two-stage calibration equation to correct the E_(abs)values estimated by the core–shell model,which reduces the simulation error in the Mie calculation by 6%–14%.

关键词： Black carbon Mixing states Fractal dimension Dynamic shape factor Absorption enhancement

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The Development of simulation Mirror system and its Application in HVDC 6

The Development of Simulation Mirror System and its Applicat...

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6th International Conference on HVDC, HVDC 2024

作者： Ou, Kaijian Wu, Wencong Cai, Haiqing State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&d Centre. Guangzhou China Guangdong Prov. Key Laboratory of Intelligent Operation and Control for New Energy Power System. Guangzhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798350387759

The testing of HVDC new control function and training of HVDC operation personnel require the integration of power system simulation and dispatching automation. This paper presents and builds AC&DC power system simulation mirror system, which is the closed-loop of real-time digital simulation and dispatching automation. Moreover, the applications of simulation mirror system on HVDC new control function testing and HVDC simulation training cabinet are also introduced in this paper. © 2024 IEEE.

关键词： automatic generation control (A GC) automatic HVDC control (ADC) dispatching automation high voltage direct curren t(HVD C) real-time digital simulator(RTDS)

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Application of deep reinforcement learning in power system scheduling strategy simulation 4

Application of deep reinforcement learning in power system s...

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4th International Conference on Energy, Power and Electrical Engineering, EPEE 2024

作者： Hu, Binjiang Huang, Libin Hu, Yufeng Zhang, Jie Guo, Haiping Lu, Yuanhong Hong, Zeqi Zhang, Jingyue Luo, Hui Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Electric Power Research Institute China Southern Power Grid State Key Laboratory of Hvdc Guangzhou China National Energy Power Grid Technology R&d Centre Guangzhou China Electric Power Research Institute China Southern Power Grid Csg Key Laboratory for Power System Simulation Guangzhou China

ISBN: (纸本)9798331518066

With the increasing scale and complexity of power system, the current scheduling strategy methods often have the problems of limited adaptability and unsatisfactory results. Therefore, a power system scheduling method using DQN (Deep Q Network) is introduced in this study. This method uses neural network model to learn and optimize scheduling strategy, and has strong adaptability and enhanced global optimization ability. Comparative evaluations with genetic algorithms and particle swarm algorithms on IEEE-118 and SG-126 datasets show that the proposed method has significant advantages in terms of cumulative reward and stable runtime. © 2024 IEEE.

关键词： Deep reinforcement learning

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A Joint Estimation Method of SOC and SOH for Lithium-ion Battery Considering Cyber-Attacks Based on GA-BP

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Computers, Materials & Continua 2024年第9期80卷 4497-4512页

作者： Tianqing Yuan Na Li Hao Sun Sen Tan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Department of Electrical Engineering Northeast Electric Power UniversityJilin132012China College of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin132022China Center for Research on Microgrids Department of EnergyAalborg UniversityAalborg9220Denmark

To improve the estimation accuracy of state of charge(SOC)and state of health(SOH)for lithium-ion batteries,in this paper,a joint estimation method of SOC and SOH at charging cut-off voltage based on genetic algorithm(GA)combined with back propagation(BP)neural network is proposed,the research addresses the issue of data manipulation resulting ***,anomalous data stemming fromcyber-attacks are identified and eliminated using the isolated forest algorithm,followed by data ***,the incremental capacity(IC)curve is derived fromthe restored data using theKalman filtering algorithm,with the peak of the ICcurve(ICP)and its corresponding voltage serving as the health factor(HF).Thirdly,the GA-BP neural network is applied to map the relationship between HF,constant current charging time,and SOH,facilitating the estimation of SOH based on ***,SOC estimation at the charging cut-off voltage is calculated by inputting the SOH estimation value into the trained model to determine the constant current charging time,and by updating the maximum available *** show that the root mean squared error of the joint estimation results does not exceed 1%,which proves that the proposed method can estimate the SOC and SOH accurately and stably even in the presence of false data injection attacks.

关键词： Lithium-ion batteries state of charge state of health cyber-attacks genetic algorithm back propagation neural network

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A Grad-CAM and capsule network hybrid method for remote sensing image scene classification

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Frontiers of Earth Science 2024年第3期18卷 538-553页

作者： Zhan HE Chunju ZHANG Shu WANG Jianwei HUANG Xiaoyun ZHENG Weijie JIANG Jiachen BO Yucheng YANG Shenzhen Data Management Center of Planning and Natural Resources Key Laboratory of Urban Land Resources Monitoring and Simulation(Ministry of Natural Resources)Shenzhen 518000China Key Laboratory of Jianghuai Arable Land Resources Protection and Eco-restoration(Ministry of Natural Resources) Hefei 230088China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China School of Civil Engineering Hefei University of TechnologyHefei 230009China

Remote sensing image scene classification and remote sensing technology applications are hot research *** CNN-based models have reached high average accuracy,some classes are still misclassified,such as“freeway,”“spare residential,”and“commercial_area.”These classes contain typical decisive features,spatial-relation features,and mixed decisive and spatial-relation features,which limit high-quality image scene *** address this issue,this paper proposes a Grad-CAM and capsule network hybrid method for image scene *** Grad-CAM and capsule network structures have the potential to recognize decisive features and spatial-relation features,*** using a pre-trained model,hybrid structure,and structure adjustment,the proposed model can recognize both decisive and spatial-relation features.A group of experiments is designed on three popular data sets with increasing classification *** the most advanced experiment,92.67%average accuracy is ***,83%,75%,and 86%accuracies are obtained in the classes of“church,”“palace,”and“commercial_area,”*** research demonstrates that the hybrid structure can effectively improve performance by considering both decisive and spatial-relation ***,Grad-CAM-CapsNet is a promising and powerful structure for image scene classification.

关键词： image scene classification CNN Grad-CAM CapsNet DenseNet

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Research on Distributed Photovoltaic Marketization Trading Model Considering Auxiliary Services 4

Research on Distributed Photovoltaic Marketization Trading M...

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4th International Conference on Energy Engineering and Power systems, EEPS 2024

作者： Meng, Tao Li, Dexin Li, Chenggang Wang, Wei Electric Power Research Institute State Grid Jilin Electric Power Co. Ltd. Jilin Province Changchun130000 China The Key Laboratory of Modern Power System Simulation and Control Ministry of Education Jilin Province Jilin132012 China

ISBN: (纸本)9798350366914

Constrained by the features of distributed photovoltaic (PV) power generation, as more distributed photovoltaic systems connect to the power grid, the demand for auxiliary services resulting from PV integration into the distribution network will significantly increase. Thus, when conducting market-oriented transactions, it becomes essential to consider not only the electricity market but also the auxiliary services required for distributed photovoltaics. This paper discusses the future distributed photovoltaic trading platform, price models, and the pricing and allocation of auxiliary services, aiming to achieve a virtuous cycle in distributed photovoltaic market-oriented trading. Furthermore, an example of distributed photovoltaic auxiliary services is provided, demonstrating that neglecting auxiliary services may allow distributed photovoltaic transactions to proceed, but they may fail to cover the cost of auxiliary services. Hence, the consideration of auxiliary services for distributed photovoltaics is crucial when organizing market-oriented transactions. © 2024 IEEE.

关键词： DC distribution systems

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Design and Implementation of Power system simulation Platform Based on Cloud Computing 4

Design and Implementation of Power System Simulation Platfor...

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4th International Conference on Energy, Power and Electrical Engineering, EPEE 2024

作者： Lu, Yuanhong Guo, Haiping Zhao, Yanjun Huang, Libin Hu, Binjiang Luo, Hui Zhang, Jingyue National Energy Power Grid Technology R&d Centre Guangzhou China State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798331518066

Power system simulation involves simulating the operating states and dynamic processes of power systems using mathematical models and computer technology to analyze and predict system behavior. Traditional simulation methods struggle to meet the needs of large-scale, complex power grids due to significant demands for computational resources. Cloud computing, with its high scalability, resource pooling, and on-demand services, is ideally suited for the extensive simulation calculations required by modern power systems. Despite its advantages, the application of cloud computing in power system simulation poses challenges related to data security and privacy, particularly in collaborative simulations involving multiple power entities. This paper presents the design and implementation of a cloud computing-based power system simulation platform. The proposed platform leverages the distributed computing capabilities of cloud computing, integrates federated learning to ensure data privacy, and utilizes advanced power system simulation technologies. This approach significantly enhances simulation efficiency and accuracy while providing data security and privacy protection. The platform offers reliable decision support for power system planning, operation, and control. © 2024 IEEE.

关键词： Cloud platforms

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Effect of Positive Temperature Coefficient Materials on the AC Breakdown Strength and Dielectric Properties of Epoxy Composites 4th

Effect of Positive Temperature Coefficient Materials on the ...

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4th International Symposium on Insulation and Discharge Computation for Power Equipment, IDCOMPU 2023

作者： Teng, Chenyuan Li, Shuo Zhou, Yuanxiang Zhang, Ling Zhang, Yunxiao Huang, Meng College of Information Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819974122

In operation, the negative temperature coefficient (NTC) electrical resistivity characteristics of polymeric insulating materials causes DC electric field distortion within power equipment insulation and lead to the failure. The doping of positive temperature coefficient (PTC) ceramic particles can suppress the NTC characteristics of the composites, but the electrical properties under AC voltages are unrevealed. In this paper, epoxy composites (0–20 wt%) doped with polydopamine-coated PTC particles were prepared, whose AC breakdown strength and dielectric properties were tested. The results shows that the decrease of AC dielectric strength is smaller than that under DC voltages after the doping PTC particles, and the coating of polydopamine can enhance the AC dielectric strength. As the doping content increases, the dielectric constant and tanδ of the epoxy composites increases, and the maximum increase of dielectric loss power is about 2% of the loss power caused by the current-carrying conductor. The research provides a theoretical basis for the optimization of the insulating performance of the equipment under the AC-DC composite voltages. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Epoxy resins

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A Disturbance Localization Method for Power system Based on Group Sparse Representation and Entropy Weight Method

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Energy Engineering 2024年第8期121卷 2275-2291页

作者： Zeyi Wang Mingxi Jiao Daliang Wang Minxu Liu Minglei Jiang He Wang Shiqiang Li Changchun Power Supply Company State Grid Jilin Electric Power Co.Ltd.Changchun130021China Economic and Technical Research Institute State Grid Jilin Electric Power Co.Ltd.Changchun130022China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Northeast Electric Power UniversityJilin132012China

This paper addresses the problem of complex and challenging disturbance localization in the current power system operation environment by proposing a disturbance localization method for power systems based on group sparse representation and entropy weight *** different electrical quantities are selected as observations in the compressed sensing *** entropy weighting method is employed to calculate the weights of different observations based on their relative disturbance ***,by leveraging the topological information of the power system and pre-designing an overcomplete dictionary of disturbances based on the corresponding system parameter variations caused by disturbances,an improved Joint Generalized Orthogonal Matching Pursuit(J-GOMP)algorithm is utilized for *** reconstructed sparse vectors are divided into three *** at least two parts have consistent node identifiers,the node is identified as the disturbance *** the node identifiers in all three parts are inconsistent,further analysis is conducted considering the weights to determine the disturbance *** results based on the IEEE 39-bus system model demonstrate that the proposed method,utilizing electrical quantity information from only 8 measurement points,effectively locates disturbance positions and is applicable to various disturbance types with strong noise resistance.

关键词： Disturbance location compressed sensing group sparse representation entropy power method GOMP algorithm

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