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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Yang, Huan Cai, Dongsheng Bamisile, Olusola Li, Jian Zhang, Zhenyuan Huang, Qi Chengdu University of Technology School of Nuclear Technology and Automation Engineering Chengdu China University of Electronic Science and Technology of China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control Chengdu China

ISBN: (纸本)9798350347159

In the context of carbon neutrality, the power industry is becoming the main battlefield of carbon emission reduction. However, the low-carbon transformation of energy structure is a complex long-term task, it needs to be analyzed in combination with the actual situation. This paper is based on the microgrid in the grid connection mode, considering microgrid power output and carbon emission constraints. An optimal model is proposed to reduce carbon emission cost, the optimal economic operation, and build a low-carbon scheduling model of a microgrid system. In this paper, the improved multi-objective particle swarm optimization algorithm is used to solve the problem. Finally, the simulation results verify the effectiveness of the model and the superiority of the improved algorithm. © 2022 IEEE.

关键词： Emission control

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A Hierarchical Optimization-Based Model for Microgrids with Energy Storage Considering Operation Cost and Net Load Mean Square Error 6

A Hierarchical Optimization-Based Model for Microgrids with ...

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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Guan, Zexiang Cai, Dongsheng Bamisile, Olusola Li, Jian Zhang, Zhenyuan Huang, Qi Chengdu University of Technology School of Nuclear Technology and Automation Engineering Chengdu China University of Electronic Science and Technology of China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control Chengdu China

ISBN: (纸本)9798350347159

When a high proportion of renewable energy is connected to the grid, the net load fluctuation can be suppressed by configuring energy storage. However, the current cost of energy storage is high. This paper proposes a bi-level optimization model that takes into account the dynamic allocation of shared energy storage (SES) capacity in response to electric load demand. The upper-layer objective function adopts EO optimization algorithm, which is to maximize the income of the shared energy storage operator (SESO). The lower-layer multi-objective function is to minimize the sum of the operating cost and the net load mean square error of multiple microgrids, which can be classified as the mixed integer linear programming problem. Then, the solution flow of the algorithm is given. Finally, under the constraints of the hierarchical optimization-based model, solving the problem by the CPLEX solver on the MATLAB platform. The results demonstrate that the proposed method can allocate optimal capacity and reduce operating costs for microgrids. Simultaneously, this method increases the revenue of SESO and promotes the consumption of renewable energy. © 2022 IEEE.

关键词： Mean square error

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Non-intrusive Load Monitoring for Household Energy Disaggregation: A State-of-the-Art 6

Non-intrusive Load Monitoring for Household Energy Disaggreg...

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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Ramadan, R. Huang, Qi Bamisile, Olusola School of Mechanical and Electrical Engineering Chengdu611731 China Tanta University Electrical Power and Machines Engineering Department Tanta31511 Egypt Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu610059 China

ISBN: (纸本)9798350347159

The continual rise in energy consumption has become a significant issue for power systems. Hence it is important to promote energy saving and reduce consumption for solving this problem. Also, finding solutions to enhance energy efficiency is crucial due to the increase in global energy demand. To improve the effectiveness of a power system network, it is important to monitor, manage, and regulate electrical energy needs on a real-time consumption basis. The development of smart homes includes energy management as a key component. A reliable appliance load monitoring (ALM) system is important for the smart energy management framework. ALM's objectives include achieving comprehensive energy sensing and disseminating data on energy use. This will make it possible for automated energy management systems to identify appliances that use higher energy. Thereby enabling them to implement energy saving methods such as rescheduling the high power demand to off-peak hours. Non-intrusive load monitoring (NILM) is one of the most popular energy management strategies in recent years. It enables customers and industries to effectively control their energy use. Utilizing a single energy meter, the NILM technology has gained popularity as an emerging method for tracking events (on/off) and energy use of electrical services and appliances in buildings. Consumers might better understand their appliance behaviour and take the appropriate actions to reduce energy consumption with the aid of information on energy consumption at the appliance level. Hence, the main objective of this paper is to present a comprehensive review of energy management monitoring approaches with an emphasis on non-intrusive load monitoring. © 2022 IEEE.

关键词： Energy efficiency

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Calculation and Simulation Analysis of Current Carrying Capacity and Thermal Effect of 500kV Tunnel Cable 6

Calculation and Simulation Analysis of Current Carrying Capa...

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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Liang, Ruipeng Huang, Qi Bamisile, Olusola Li, Jian Zhang, Zhenyuan Cai, Dongsheng Chengdu University of Technology School of Nuclear Technology and Automation Engineering Chengdu China University of Electronic Science and Technology of China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control Chengdu China

ISBN: (纸本)9798350347159

The Qinghai-Tibet Plateau contains the most abundant clean energy such as hydropower, wind and solar in the world. However, it is very difficult to add overhead transmission lines on the ground due to the complex geographical environment. The large-capacity tunnel cables which is less affected by the earth surface environment, may play an important role on the energy transmission in such area. Based on the cable thermal circuit model, the electrical-magnetic-thermal multiphysics coupling of the cable is modeled in COMSOL Multiphysics. The parameter changes of the material during the temperature rising process, the influence of different ventilation conditions and different current-carrying capacities on the changes of the cable temperature field are quantitatively analyzed. The results show that the proposed model is valid in certain conditions. The research on the current carrying capacity and thermal effect of tunnel cables is of great significance for the transportation and consumption of large-scale clean energy resources. © 2022 IEEE.

关键词： Cables

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Point Cloud based Motion State Estimation Method for Autonomous Driving

Point Cloud based Motion State Estimation Method for Autonom...

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2023 International Conference on Advanced Mechatronic Systems, ICAMechS 2023

作者： Jiang, Tao Zhu, Enzhi Wu, Sidong Zhang, Linshuai Gu, Shuoxin Xu, Lin Wang, Qian Tang, Xianggui Chengdu Univ. of Traditional Chinese Med. Unmanned Syst. Intelligent Percept. Contr. Technol. Eng. Laboratory of Sichuan Province Chengdu University of Information Technology School of Intelligent Medicine Chengdu China Chengdu University of Information Technology School of Automation Chengdu China Chengdu Univ. of Info. Technol. Unmanned Syst. Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province Chengdu University of Information Technology School of Automation Chengdu China Chengdu University of Traditional Chinese Medicine School of Automation Chengdu Univ. of Info. Technol. Intl. Jt. Res. Ctr. of Robotics and Intell. Syst. of Sichuan Prov. School of Intelligent Medicine Chengdu China Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province School of Automation Chengdu China

ISBN: (纸本)9798350307474

Generally, motion vector information primarily stems from moving objects, while static objects contribute minimally to the estimation task. Traditional approaches for motion vector estimation typically rely on scene flow methods that depend on deep models to extract features from individual points at a high cost. These methods then acquire flow information through complex matching mechanisms or feature decoding. Such approaches are computationally expensive and exhibit substantial latency. Moreover, they neglect the importance of motion objects in motion vector estimation and the interference from static objects. Therefore, this paper introduces a novel method that first performs point cloud motion segmentation and subsequently estimates motion vectors. This approach focuses on leveraging point cloud information annotated with motion objects to estimate three-dimensional scene flow more effectively. By employing motion segmentation, we can obtain annotations for moving objects, enabling greater emphasis on the estimation of motion vectors for more challenging cases. In our experiments conducted on the KITTI dataset, the proposed method demonstrates superior performance compared to existing scene flow estimation methods. Specifically, without considering motion segmentation errors, the error in the motion direction is only 0.0363 m/s, showcasing better performance. Additionally, our method achieves an error of 0.076 m for three-dimensional endpoint error (EPE3D), showcasing distinct advantages over current scene flow networks. © 2023 IEEE.

关键词： Errors

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A Reliability Analysis Method for an Aircraft Power System with Hybrid Uncertainty and Failure Dependence 3

A Reliability Analysis Method for an Aircraft Power System w...

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3rd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2022

作者： Song, Yufei Zhu, Yukui Cao, Xiang Yu, Min Zhang, Jie Co. Ltd Chengdu China University of Electronic Science and Technology of China Department of Automation Engineering Chengdu China

ISBN: (纸本)9781665492812

Because of the increasing complexity of modern electromechanical systems, it is important to develop a reliability analysis model for systems with hybrid uncertainty and failure dependence. In practice, engineers may not have enough information to estimate the correlation between components/subsystems, which is named as non-deterministic dependence problem. In order to model the impact of uncertainty and non-deterministic dependence on system performance, this paper proposed a reliability analysis method based on Bayesian network and affine arithmetic. The proposed method can be used to overcome the limitation of interval arithmetic and retains the advantages of Bayesian network in dealing with the problems of correlation and uncertainty. Finally, the proposed affine-based Bayesian network is applied to an aircraft power system. © 2022 IEEE.

关键词： affine arithmetic Bayesian network failure dependence interval arithmetic uncertainty

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Experimental Investigation on Local Behaviors of PEMFC with Segmented Cell

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Automotive Innovation 2021年第2期4卷 165-175页

作者： Cong Yin Yan Gao Kai Li Yating Song Hao Tang School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 610023China Hydrogen and Fuel Cell Institute University of Electronic Science and Technology of ChinaChengdu 610023China

When designing a cell stack and developing an operational strategy for proton exchange membrane fuel cell,it is critical to characterize the local current,water and *** measure distributions of current density,relative humidity and temperature for both anode and cathode simultaneously along the straight parallel flow channels,this paper uses a segmented tool based on the multilayered printed circuit board flow field plates with embedded *** this study,two kinds of experimental operations of fuel cell reactants are carried out for comparison:the co-flow operation with identical gas flow direction of hydrogen and air and the counter-flow operation with opposite gas flow *** detected relative humidity(RH)distributions of both anode and cathode indicate that the asymmetry of RH distribution at two sides of the membrane in counter-flow operation is better at holding water inside the fuel cell compared with the co-flow *** in situ measured performance distributions show that segments around the middle of the fuel cell contribute the highest current in counter-flow operation,while for co-flow operation,the current peak locates near the outlet of reactants.

关键词： Proton exchange membrane fuel cell ·Segmented cell Local relative humidity Local temperature Current distribution

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A New Method to Detect the Inter-Turn Short Circuit Fault of Dry-Type Air-Core Shunt Reactor 4

A New Method to Detect the Inter-Turn Short Circuit Fault of...

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4th International Conference on Power and Energy technology, ICPET 2022

作者： Wu, Jie Luo, Rongsen Zhang, Man Peng, Yumin Jing, Shi Huang, Qi Electric Power Research Institute of State Grid Sichuan Electric Power Company Chengdu China University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu China Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu China

ISBN: (数字)9781665480796

ISBN: (纸本)9781665480796

Due to the insulation fails caused by complex factors, such as the manufacture factors, transportation and complicated working environment, inter-turn short circuit fault is one of the frequent failures of shunt reactor, at the early stage of whom, its current is not high enough to trigger the protection equipment. However, the current in the shorted turn is very high, which causes serious copper loss, resulting in high temperature rise. In severe case, it will cause fire accident and explosion. Thus, it's important to design a sensitive and reliable method to detect the inter-turn short circuit fault at its early stage. In this paper, a method based on the power loss factor (PLF) considering both the activate power and equivalent resistance of reactor, is proposed to detect the inter-turn short circuit fault of an air-core shunt reactor considering the effect of insulation resistance. Taking a BKDCL-20000/35 dry-type air-core shunt reactor as an example, the inter-turn short circuit faults occur at different axial heights and coil layers are investigated. The electrical parameters, including equivalent resistance, equivalent inductance, active power, reactive power etc. are presented and comparison is implemented between the normal condition and failure conditions. The current and active power of the shorted turn is calculated and analyzed, which are used to explain the parameters variation of the reactor when inter-turn short circuit fault occurs. Finally, PLF under various working conditions is computed and presented, which provide an alternative to monitor the inter-turn short circuit fault. © 2022 IEEE.

关键词： Timing circuits

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Research of nuclide identification method based on background comparison method

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Applied Radiation and Isotopes 2023年 192卷 110596页

作者： Li, Xiaozhe Zhang, Qingxian Tan, Heyi Tan, Wei Cheng, Zhiqiang Ge, Liangquan Shi, Zeming Zeng, Guoqiang Gu, Yi Zhang, Jian Dong, Chunhui Wang, Ming Chengdu University of Technology The College of Nuclear Technology and Automation Engineering Sichuan ChengDu610059 China Sichuan ChengDu610059 China

Radioactive material inspection in public is important to nuclear safety, and it is also the key security for holding large-scale events, while fast and efficient means of detecting radioactive materials are an important technical guarantee for nuclear safety. In this paper, energy and time distribution characteristics information of the natural background and target nuclide gamma particles are used to improve the sequential background comparison method. By using those energy and time distribution characteristics information, with the half-life and characteristic gamma-ray energy and branching ratio information of the nuclide, the response time and the identification accuracy of extremely low radioactive nuclides detected under natural-radiation background can be improved. Based on the theoretical research, the particle event acquisition device with the LaBr3(Ce) detector was used to carry out the experimental verification, and the results show that, this method can identify 137Cs (characteristic energy of 0.662 MeV，8700 Bq，the position relative to the detector is 30 cm) in 6.2 s, and identify 60Co (characteristic energy of 1.173 MeV and 1.332 MeV, 4500 Bq, the position relative to the detector is 15 cm) in 5.9 s. Experiments prove that the improved background comparison-based sequential Bayesian method can identify low radioactivity radionuclides under natural-radiation background rapidly. © 2022 Elsevier Ltd

关键词： Isotopes

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A Data-Driven Hybrid Machine Learning and Transfer Learning Algorithm for Long Consecutive Atmospheric Environment Missing Data Imputation 43

A Data-Driven Hybrid Machine Learning and Transfer Learning ...

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43rd Chinese Control Conference, CCC 2024

作者： Meng, Hao Shao, Lizhen Fu, Dongmei Song, Guangxuan Meng, Jintao School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing Engineering Research Center of Industrial Spectrum Imaging Beijing100083 China National Key Laboratory of Security Communication Chengdu610041 China

ISBN: (纸本)9789887581581

Comprehensive and accurate environmental data form the foundation for studying the correlation between substance properties and the environment. Nevertheless, missing data is inevitable during the data collection process, posing a challenge to research advancement, especially in cases of prolonged and consecutive data gaps. The inherent periodicity of environmental data, which has rarely been considered separately in previous studies, plays an important role in imputing long consecutive missing data. This article combines the advantages of machine learning and transfer learning methods and proposes an imputation algorithm that can fully utilize the inherent periodic components of long consecutive missing data. The algorithm initially utilizes wavelet coherence to assess the periodic coherence of the data, decomposing it into periodic and non-periodic components. Subsequently, the random forest method is employed to impute the periodic components, while the transfer learning approach is used to impute the non-periodic components. By aggregating the imputed values of each component, the final imputation output is obtained. The algorithm was validated using environmental data from five regions in China, demonstrating superior performance compared to existing algorithms across various levels of missing data. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Adversarial machine learning

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