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Electrical engineering and control Science (IC2ECS), International Conference on

作者： Ruixiong Yang Yong Chen Kai Xu Shuping Gao Guangdong Power Grid Co. Ltd. DC Distribution Power Research Center Zhuhai Guangdong China College of Electrical and Control Engineering Xi'an University of Science and Technology Xi'an Shaanxi China Xi'an Key Laboratory of Electrical Equipment Condition Monitoring and Power Supply Security Xi'an Shaanxi China

At present, the waveforms generated in the power system are more and more complex, not only a single sinusoidal current, the pulsating DC component and the smooth DC component are often generated when the fault occurs. But the traditional AC residual current protector can only detect the AC residual current, and can not protect this complex waveform signal. In this paper, the pulsating DC residual current is studied, and a residual current detection method based on Fourier transform is proposed. It can effectively identify the residual current waveform, and set threshold according to different waveforms. It can accurately detect the residual current, but its anti-interference ability is poor. In order to solve the problem of anti-interference, a residual current detection method based on Kalman filter is proposed. The predicted value of Kalman filter is obtained after the generated residual current is filtered, and the threshold of the action of the system protection device can be set according to the predicted value. Simulation results show that this method can effectively improve the anti-interference ability of the system.

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High-Precision and Wide-Range Temperature Measurement and control System of Satellite-Borne Calibration Blackbody

SSRN

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SSRN 2023年

作者： Jiang, Leijie Liu, Chuande Zhu, Lixun Zhang, Zhenzhong Hou, Qiankang School of Mechanical Engineering and Rail Transit Changzhou University Changzhou213164 China Jiangsu Province Engineering Research Center of High-Level Energy and Power Equipment Changzhou University Changzhou213164 China School of Automation Nanjing University of Information Science and Technology Nanjing210044 China Department of Electrical Engineering Shanghai Maritime University Shanghai201306 China

The temperature of the blackbody can affect the quality and effect of the radiometric calibration. A configurable system is developed to measure and control the temperature of satellite-borne blackbody. A novel temperature measurement and control circuit is designed. A coarse-fine measurement method considering the wire resistance and the self-heating effect of the platinum resistance is presented to calculate the resistance values of the platinum resistors. The precision of temperature measurement is improved using a line fitting algorithm with temperature drift error compensation. A fuzzy self-adaptive PID controller is designed to improve the temperature control effect. The performances of the developed system are implemented on an FPGA/A3PE3000-FG484I controller board. The test results show that the device temperature measurement precision can reach ±0.03 K for the entire temperature range 238 K to 367 K. The proposed scheme can be extended to the temperature control systems of other satellite-borne devices. © 2023, The Authors. All rights reserved.

关键词： Three term control systems

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Fast control Strategy of Grid-forming Inverter Based on power Feedforward

Fast Control Strategy of Grid-forming Inverter Based on Powe...

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第42届中国控制会议

作者： Sheng Zhang Zhijian Fang Qine Liu Muchao Xiang Dingbang Huang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education State Grid Hubei Electric Power Co. LtdXiangyang Power Supply Company Electric Power Scientific Research Institute of State Grid Hubei Electric Power Co. Ltd

Grid-forming inverter is widely used in grid-connected systems of distributed generation because of its frequency and voltage support capacity and good stability in microgrid,but its large inertia will affect the dynamic response speed of grid-forming *** order to solve this problem,this paper introduces the loop that affects the dynamic response of grid-forming inverter,and carries out small signal modeling for active loop,analyzes the dynamic performance indicators and determinants of typical second-order ***,a method of adding power feedforward coefficient to the forward channel of the power loop is designed,and the response speed of the system with or without feedforward coefficient under the unit step response is ***,the simulation results show that adding the power feedforward coefficient can improve the response speed of the grid-forming inverter during startup and power switching,then achieves the effect of fast control.

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Reinforcement Learning Based control for Uncertain Robotic Manipulator Trajectory Tracking

Reinforcement Learning Based Control for Uncertain Robotic M...

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Chinese Automation Congress (CAC)

作者： Aohua Liu Bo Zhang Weiliang Chen Yiang Luo Shuxian Fang Ouyang Zhang Zhuang Liu Zhenhuan Wang Jianxing Liu Department of Control Science and Engineering Harbin Institute of Technology Harbin P. R. China The Suihua Power Supply Company State Grid Heilongjiang Electric Power Company Limited Suihua China Space Control and Inertial Technology Research Center Harbin Institute of Technology Harbin China

This paper investigates the trajectory tracking control method for a robotic manipulator with uncertainties. A compound controller combining a traditional control law with deep reinforcement learning is developed to improve tracking accuracy and adaptability. The model-based control method is able to increase sampling efficiency for learning control strategy. The introduction of deep reinforcement learning based on soft actor-critic structure and Lyapunov function constrain enables the system to compensate unknown uncertainties and remain stable. Eventually, a 3-DOF manipulator is used to show the effectiveness of the proposed controller. Comparative simulation results demonstrate that the compound controller acquires higher tracking accuracy than the pure model-based control method.

关键词： Deep learning Uncertainty Trajectory tracking Simulation Reinforcement learning Manipulators Stability analysis

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Optimization of Robot End-Effector Load Gravity Compensation for Unmanned Live Work in Electric power Distribution Networks Based on Improved PSO Algorithm

Optimization of Robot End-Effector Load Gravity Compensation...

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Chinese Automation Congress (CAC)

作者： Jinge Chen Xin Chen Chenyu Hu Guangxian Huang Shu Sun Xu Jian School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering-Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Distribution Department State Grid Hubei Electric Power Co. Ltd. Xianning Power Supply Company Xianning China Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan China

In the field of electric power distribution network operation, most tasks involve contact operations. A key technology to enable the flexible operation of robots in live distribution network tasks is the installation of six-dimensional force sensors on the robot's end flange. These sensors allow the robot to perceive external environmental contact forces. However, the presence of the end load interferes with the accurate perception of external forces. Aiming at the gravity compensation of robot end load, an optimization algorithm of gravity compensation based on particle swarm optimization is proposed. In this method, the optimal solution model is established with the objective of minimum sum of squared errors, and the particle swarm optimization algorithm is used to estimate the mounting declination angle of the force sensor and improve the precision of gravity compensation. The experiments show that the proposed method can effectively reduce the maximum gravity compensation error and the average gravity compensation error in each direction after optimization, in which the maximum gravity compensation error of the resultant force is reduced by 9.11% and the average gravity compensation error of the resultant force is reduced by 12.34%.

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The 110kV Live-Maintaining Robot control System Design for Substation Equipment in Complex Working Conditions

The 110kV Live-Maintaining Robot Control System Design for S...

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Chinese control Conference (CCC)

作者： Chenyu Hu Xin Chen Chengyu Li Guangxian Huang Cheng Zhou Xu Jian School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Future Technology China University of Geosciences Wuhan China Distribution Department State Grid Hubei Electric Power Co. Ltd. Xianning Power Supply Company Xianning China Operations and Maintenance Department State Grid Hubei Electric Power Co. Ltd Xianning Xian'an District Power Supply Company Xianning China Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Live-maintaining work is essential for continuous power supply to the substation. To improve the safety and efficiency of live-maintaining work, this paper proposes an equipotential live-maintaining robot system suitable for 110kV voltage levels. Considering the narrow space, complex working conditions and strong electromagnetic interference in substations, binocular vision technology, manipulator trajectory planning algorithm based on time-energy optimization, high voltage electromagnetic shielding technology are utilized to develop the system, and the live-maintaining robot is successfully applied in actual substation. By accurately identifying and locating the joint bolts and insulator, the robot system can achieve equipotential live-disassemble, live-assemble the joint bolts within 18 minutes and live-clean insulator within 5 minutes, demonstrating its the effectiveness and practicability.

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Fast control Strategy of Grid-forming Inverter Based on power Feedforward

Fast Control Strategy of Grid-forming Inverter Based on Powe...

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Chinese control Conference (CCC)

作者： Sheng Zhang Zhijian Fang Qine Liu Muchao Xiang Dingbang Huang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China State Grid Hubei Electric Power Co. Ltd Xiangyang Power Supply Company Xiangyang China Electric Power Scientific Research Institute of State Grid Hubei Electric Power Co. Ltd Wuhan China

Grid-forming inverter is widely used in grid-connected systems of distributed generation because of its frequency and voltage support capacity and good stability in microgrid, but its large inertia will affect the dynamic response speed of grid-forming inverter. In order to solve this problem, this paper introduces the loop that affects the dynamic response of grid-forming inverter, and carries out small signal modeling for active loop, analyzes the dynamic performance indicators and determinants of typical second-order system. Thus, a method of adding power feedforward coefficient to the forward channel of the power loop is designed, and the response speed of the system with or without feedforward coefficient under the unit step response is compared. Finally, the simulation results show that adding the power feedforward coefficient can improve the response speed of the grid-forming inverter during startup and power switching, then achieves the effect of fast control.

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BNNG Algorithm Modeling for Vehicle Classification Recognition under Non Line-of -sight Environment 4

BNNG Algorithm Modeling for Vehicle Classification Recogniti...

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2019 4th International Conference on Advances in Energy and Environment research, ICAEER 2019

作者： Wu, Long Huang, Kaifeng Feng, Juqiang School of Mechanical and Electrical Engineering Huainan Normal University Huainan232038 China Research Center for Power Supply and Control Engineering Technology of Rail Transit Huainan232038 China

At present, the automatic classification of vehicles on roads is mostly based on image recognition, and there are defects in adaptability under non-line-of-sight environments. In this paper, based on the similarity of the integration of the ecosystem model and multi-neural network model, an artificial neural network group (BNNG) algorithm was proposed. The vehicle's driving acoustic signal was taken as the research object, and it was calculated using the Artificial Neural Network (BNNG) algorithm to achieve automatic classification and recognition of vehicle models. Through experimental tests, it is shown that under non-line-of-sight environments, the accuracy of vehicle classification can be improved, and the misrecognition rate of similar models can be greatly reduced. This provided a new method for the automatic classification and identification of vehicles on roads, which was of great significance to monitor vehicle safety in non-line-of-sight environments. © The Authors, published by EDP Sciences, 2019.

关键词： Neural networks

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Deep neural network based interpolation of sparse samples for time-dense power load forecasting

Deep neural network based interpolation of sparse samples fo...

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International Conference on Computer engineering and Applications (ICCEA)

作者： Bo Li Ruifeng Zhao Jiangang Lu Kuo Xin Jinhua Huang Guanqiang Lin Jinrong Chen Xueyue Pang Shunxin Wu Electric Power Dispatching and Control Center of Guangdong Power Grid Co. Ltd. Guangzhou Guangdong China Electric Power Dispatching and Control Center of China Southern Power Grid Co. Ltd. Guangzhou Guangdong China Electric Power Research Institute of Guangdong Power Grid Co. Ltd. Guangzhou Guangdong China Huizhou Power Supply Bureau of Guangdong Power Grid Co. Ltd. Huizhou Guangdong China Foshan Power Supply Bureau of Guangdong Power Grid Co. Ltd. Foshan Guangdong China China Energy Engineering Group Guangdong Electric Power Design Institute Co. Ltd. Guangzhou Guangdong China State Key Laboratory of Power Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing China

Large amount of power load data with high-sampling rate plays a crucial role in the training of time-dense power load forecasting network. However, in many cases, there is a large amount of data with low-sampling rate, which can't directly train a time-dense forecasting network. Therefore, this paper proposes a deep learning based dataset interpolation method, which uses the available high-sampling rate power load datasets to train a dataset interpolation network, then interpolates the low--sampling rate datasets with trained network to obtain high-sampling rate datasets, and finally uses the interpolated datasets for time-dense forecasting network training. The results show that the data obtained based on the method proposed in this paper fits the ground-truth closer than the traditional interpolation, and the results of the network trained based on this dataset are more accurate in the subsequent forecasting tasks.

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Study on temperature characteristics of mineral ferric phosph ate lithium-ion battery 2

Study on temperature characteristics of mineral ferric phosp...

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2019 2nd International Conference on Manufacturing technology, Materials and Chemical engineering, MTMCE 2019

作者： Feng, Juqiang Huang, Kaifeng Wu, Long Zhang, Xing School of Mechanical and Electrical Engineering Huainan Normal University Huainan232038 China Research Center for Power Supply and Control Engineering Technology of Rail Transit Huainan232038 China

Lithium-ion battery (SE60AHA type)is the main power of mine trolleybus. It studies the characteristics of main parameters such as capacity, charging and discharging time and cycle life with temperature, which can effectively ensure safety. This paper designs charging and discharging experiments under different temperature conditions and conducts OCV-SOC curve analysis. The results show that under the charging conditions of different temperature, there is no significant change in the relative capacity of charging, but the lower the temperature is, the shorter the constant-current charging time is and the longer the constant-voltage time is. Under the discharging condition of different temperature, the change of relative discharging capacity is obvious, the voltage drops faster when the temperature is lower than 0°C, and it keeps the same voltage variation when the temperature is higher than 0°C, while the discharging time reduces with decreased temperature. Further more, according to the variation of charging and discharging voltage with different temperature, it analyze the health status and optimal working environment of mine-type lithium-ion battery adopting the characteristics of charging and discharging efficiency. The research results provide a basis of the using and maintenance of large-capacity lithium-ion battery stack in special environments of the coal mining. © Published under licence by IOP Publishing Ltd.

关键词： Lithium-ion batteries

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