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Optimal controller Design for Non-Affine Nonlinear Power systems with Static Var Compensators for Hybrid UAVs

Tsinghua Science and Technology 2022年第1期27卷 196-206页

作者： Yanchu Li Qingqing Ding Shufang Li Stanimir Valtchev Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networkand School of Information&Communication EngineeringBeijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Control and Simulation of Power System and Generation Equipments Tsinghua UniversityBeijing 100084China the Nova School of Science and Technology(FCT/UNL) Caparica 2829-516LisbonPortugal Technical University of Sofia(TUS) Sofia 2125Bulgaria

A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator(SVC)or state Var system(SVS)for hybrid Unmanned Aerial Vehicles(UAVs).The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its *** the inverse system method and the Linear Quadratic Regulation(LQR),an optimized SVC controller is *** simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.

关键词： Static Var Compensator(SVC) Unmanned Aerial Vehicles(UAV) power system non-affine nonlinear control inverse system method Linear Quadratic Regulation(LQR)

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Voltage Stability Analysis of New Energy Mega Bases Based on STATCOM 6

Voltage Stability Analysis of New Energy Mega Bases Based on...

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6th International Conference on Electrical Engineering and control Technologies, CEECT 2024

作者： Zhu, Zimin Zao, Weihong Ma, Xing Liu, Zhen Duan, Yu Wu, Xiaofang Electric Power Research Institute of State Grid Xinjiang Electric Power Co. Ltd. Xinjiang Key Laboratory of Whole Process Simulation for Power System Urumqi China

ISBN: (纸本)9798331528096

Line-commutated converter based high-voltage direct current (LCC-HVDC) system plays an important role for long distance power transmission. However, its vulnerability to commutation failures threatens the stability of power grids. This paper takes the Tianzhong DC area in Xinjiang region, China, as a case study to analyze the impacts of the number of operational thermal power plants on the overvoltage situation at wind farm stations. As the number of operational units decreases, the probability of wind turbines disconnecting increases, emphasizing the importance of integrating STATCOM devices near new energy power stations in HVDC transmission sending-end areas. Additionally, the paper analyzes the control structure of STATCOM devices, examines the internal control parameters, identifies key parameters affecting control effectiveness, and provides recommendations for appropriate parameter ranges based on their effects. © 2024 IEEE.

关键词： Thermoelectric power plants

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Optimization Strategy for Virtual Energy Storage of Electric Vehicles to Participate in Multiple Ancillary Services 5

Optimization Strategy for Virtual Energy Storage of Electric...

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5th International Conference on Clean Energy and Electric Power Engineering, ICCEPE 2024

作者： Guo, Qi Gu, Haohan Zhao, Yifei Tu, Liang Chen, Qifang Cai, Haiqing Chen, Wei Chen, Zhihao Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou510663 China School of Electrical Engineering Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9798350390315

When EVs participate in multiple ancillary services of the power grid, due to the lack of a unified management scheduling plan, various ancillary service demands compete for limited energy storage resources. This would lead to conflicts when the virtual energy storage of EV participates in the regulation of multiple ancillary services. In order to solve the above problems, a reasonable and feasible optimization strategy for virtual energy storage of EVs is formulated to alleviate the conflict problems of ancillary services. The validity of the proposed method is verified by simulation cases. © 2024 IEEE.

关键词： control strategies electric vehicles multiple auxiliary services

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Peak Shaving and Power Allocation Strategies for Optimizing Lifespan and Reducing Energy Loss in BESS 4

Peak Shaving and Power Allocation Strategies for Optimizing ...

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4th Energy Conversion and Economics Annual Forum, ECE Forum 2024

作者： Guo, Gan Li, Junhui Mu, Gang Yan, Gangui Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China

ISBN: (纸本)9781837242627

To manage the challenge of optimizing energy efficiency, an optimization strategy for power allocation in battery clusters is proposed to reduce energy loss in Battery Energy Storage systems (BESS). Meanwhile, an improved peak shaving strategy is also proposed, aiming to increase the utilization of energy storage during the peak shaving process and reduce the ineffective utilization hours of energy storage, thereby extending the lifespan of the storage system. Furthermore, based on real-system data, a Simulink/Simscape model is developed to simulate component losses. Under a peak shaving scenario, the effectiveness of the strategy is demonstrated: it reduces the daily operational loss by 3.84% and improves energy round-trip efficiency by 0.4%. © The Institution of Engineering & Technology 2024.

关键词： battery cluster power allocation battery energy storage system efficiency particle swarm optimization peak shaving

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Synergically regulated silver species and surface oxygen on manganese oxide for promoted activity of formaldehyde oxidation

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Journal of Environmental Sciences 2024年第4期138卷 709-718页

作者： Shuo Hu Jianghao Zhang Xueyan Chen Xiaoxiao Qin Jinshui Yao Changbin Zhang School of Materials Science&Engineering Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China

Formaldehyde(HCHO)is a common indoor pollutant that is detrimental to human *** efficient removal has become an urgent demand to reduce the public health *** this work,Ag-MnO_(x)-based catalysts were prepared and activated under different atmosphere(i.e.,air,hydrogen(H_(2))and carbon monoxide(CO))for efficient oxidation of *** catalyst activated with CO(Ag/Mn-CO)displayed the highest activity among the tested samples with 90% conversion at 100℃ under a gas space velocity of 75,000 mL/(g_(cat)·hr).Complementary characterizations demonstrate that CO reduction treatment resulted in synergically regulated content of surface oxygen on support to adsorb/activate HCHO and size of Ag particle to dissociate oxygen to oxidize the adsorbed *** contrast,other catalysts lack for either abundant surface oxygen species or metallic silver with the appropriate particle size,so that the integrate activity is limited by one specific reaction *** study contributes to elucidating the mechanisms regulating the oxidation activity of Ag-based catalysts.

关键词： HCHO oxidation Ag-MnO_(x)-based catalyst Activation condition Synergic regulation Surface oxygen Oxidized Ag

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Decomposing Visual and Semantic Correlations for Both Fully Supervised and Few-Shot Image Classification

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1658-1668页

作者： Zhang, Chunjie Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Most image classification methods are designed to either boost the classification accuracies with abundant supervision, or cope with the shortage of supervision information. This is often achieved by using the visual and semantic information of other sources. However, these methods use the visual and semantic information within the same class independently, leaving their intrinsic correlations unconsidered. Objects and disturbing components as well as noise exist on the same image. Besides, semantic representations also contain noisy information. To solve the problems mentioned above, we propose a novel method for both fully supervised image classification and few-shot image classification by decomposing visual and semantic correlations. We jointly explore the intrinsic correlations of visual and semantic information of images within the same class. For each class, we decompose its visual and semantic correlations using low-rank and sparse constraint respectively. The decomposed low-rank parts character the intrinsic correlations of images can be used in a linear transformation way. Using the decomposed parts of each class, Classification can be achieved by reconstruction error minimization. We conduct experiments on several datasets for both fully supervised image classification and few-shot image classification. Experimental results well show the effectiveness of the proposed method. © 2020 IEEE.

关键词： Semantics

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Real-time Optimal Energy Management of Combined Cooling, Heating and Power systems Based on Knowledge conlusion 6

Real-time Optimal Energy Management of Combined Cooling, Hea...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： He, Chunjiang Wang, Yijian Xu, Yang Cui, Yang China Electric Power Research Institute State Key Laboratory of Power Grid Security and Energy Conservation Beijing China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin China

ISBN: (纸本)9798350346671

Combined Cooling, Heating and Power(CCHP) system is an important way to improve the efficiency of energy utilization and wind power consumption. In this case, increasing the operational flexibility of CCHP systems can help increase renewable energy consumption and reduce carbon emissions. So, it is necessary to provide real-time optimal energy management(OEM) for CCHP systems. In this paper. Firstly, a new training method is proposed for the LightGBM to improve the accuracy of real-time wind power prediction. In addition, to solve the nonlinear OEM of CCHP in real-time, a novel deep reinforcement learning algorithm-Soft Actor-Critic, is used in this paper. By combining the mechanism of CCHP with the reward function through knowledge fusion, the non-convex models can be translated into Markov Decision Processes(MDP), and then according to the Bellman optimal equation, the real-time optimized operation of the CCHP system is realized. Finally, the effectiveness of the proposed policy is verified by the actual operation data of a CCHP system in Northwest China. © 2023 IEEE.

关键词： Reinforcement learning

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CAEFusion: A New Convolutional Autoencoder-Based Infrared and Visible Light Image Fusion Algorithm

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Computers, Materials & Continua 2024年第8期80卷 2857-2872页

作者： Chun-Ming Wu Mei-Ling Ren Jin Lei Zi-Mu Jiang Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationSchool of Electrical EngineeringNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China School of Electronic Information Engineering Bozhou UniversityBozhou236800China

To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is *** region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature *** the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image *** study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional *** methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other *** algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)*** experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.

关键词： Image fusion deep learning auto-encoder(AE) infrared visible light

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Exogenous-organic-matter-driven mobilization of groundwater arsenic

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Environmental Science and Ecotechnology 2023年第3期15卷 106-120页

作者： Fan Feng Yonghai Jiang Yongfeng Jia Xinying Lian Changjian Shang Meng Zhao State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental SciencesBeijing100012China State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution Chinese Research Academy of Environmental SciencesBeijing100012China College of Water Sciences Beijing Normal UniversityBeijing100875China

The potential release capacity of arsenic(As)from sediment was evaluated under a high level of exogenous organic matter(EOM)with both bioreactive and chemically reactive organic matters(OMs).The OMs were characterized by FI,HIX,BIX,and SUVA254 fluorescence indices showing the biological activities were kept at a high level during the experimental *** the genus level,Fe/Mn/As-reducing bacteria(Geobacter,Pseudomonas,Bacillus,and Clostridium)and bacteria(Paenibacillus,Acidovorax,Delftia,and Sphingomonas)that can participate in metabolic transformation using EOM were *** reducing condition occurs which promoted As,Fe,and Mn releases at very high concentrations of ***,As release increased during the first 15-20 days,followed by a decline contributed by secondary iron *** degree of As release may be limited by the reactivity of Fe(hydro)*** EOM infiltration enhances As and Mn releases in aqueous conditions causing the risk of groundwater pollution,which could occur in specific sites such as landfills,petrochemical sites,and managed aquifer recharge projects.

关键词： Groundwater arsenic Exogenous organic matter Redox condition Secondary pollution risk

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Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise control of Heavy-Duty Trucks

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 294-317页

作者： Hongqing Chu Xiaoxiang Na Huan Liu Yuhai Wang Zhuo Yang Lin Zhang Hong Chen School of Automotive Studies Tongji UniversityShanghaiChina Department of Engineering University of CambridgeCambridgeUK State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchunChina Qingdao Automotive Research Institute Jilin UniversityQingdaoChina Dongfeng Commercial Vehicle Technology Center Dongfeng Motor CorporationWuhanChina

Fuel consumption is one of the main concerns for heavy-duty *** cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road *** this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty *** minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is *** the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting *** programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed ***,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed *** results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing ***,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.

关键词： Heavy-duty truck Predictive cruise control Model predictive control Pontryagin’s maximum principle Real-truck implementation

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