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Multi-objective Optimal Operation of Centralized Battery Swap Charging System with Photovoltaic

Journal of Modern Power Systems and Clean Energy 2022年第1期10卷 149-162页

作者： Yuanzheng Li Yihan Cai Tianyang Zhao Yun Liu Jian Wang Lei Wu Yong Zhao School of Artificial Intelligence and Automation Ministry of Education Key Laboratory of Image Processing and Intelligence ControlHuazhong University of Science and TechnologyWuhanChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore College of Mechatronics and Control Engineering Shenzhen UniversityShenzhenChina Department of Electrical&Computer Engineering Stevens Institute of TechnologyHobokenUSA

Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV *** paper proposes a multi-objective optimal operation method for the centralized battery swap charging system(CBSCS),in order to enhance the economic efficiency while reducing its adverse effects on power *** proposed method involves a multi-objective optimization scheduling model,which minimizes the total operation cost and smoothes load fluctuations,***,we modify a recently proposed multi-objective optimization algorithm of non-sorting genetic algorithm III(NSGA-III)for solving this scheduling ***,simulation studies verify the effectiveness of the proposed multi-objective operation method.

关键词： Multi-objective optimization electric vehicle battery swap charging system scheduling photovoltaic

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Intelligent On-Line System for Monitoring Technical Condition of High-Voltage Cable Couplings

Intelligent On-Line System for Monitoring Technical Conditio...

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2024 International Russian Smart Industry Conference, SmartIndustryCon 2024

作者： Gasiyarov, Vadim R. Voronin, Stanislav V. Radionov, Andrey A. Lyubimov, Ivan V. Evdokimov, Sergey A. Khramshin, Vadim R. Moscow Polytechnic University Department of Automation and Control Moscow Russia South Ural State University Department of Mechatronics and Automation Chelyabinsk Russia Power Engineering and Automated Systems Institute Nosov Magnitogorsk State Technical University Magnitogorsk Russia

ISBN: (纸本)9798350395044

The article provides the characteristics of the end cable couplings of the closed switchgear 110 kV at the electric steelmaking workshop of the metallurgical plant. The functions of the continuous technical condition monitoring system are substantiated, including continuous temperature monitoring and on-line registration of partial discharges in the insulation. The first function provides monitoring of the operational load, and the second has the maximum sensitivity for diagnosing defect propagation. A functional diagram of the developed intelligent on-line system for monitoring technical condition with digital signal transmission is provided. The choice of sensors and processor unit is justified. The authors consider the temperature control system of high-voltage equipment 'WDM-T', including a wireless sensor and an information receiver. The results of monitoring the thermal regime are provided, the advantages of partial discharge analysis are pointed out. The temperature trends of the end couplings included in the cable line phases are considered. The system is implemented on the closed switchgear 110 kV end couplings, its long-term operation has confirmed the effectiveness of technical condition monitoring. The developed system may be a component of an on-line cyberphysical system for monitoring the condition of high-voltage equipment in the electric steelmaking workshop. © 2024 IEEE.

关键词： Electric lines

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Cutting force and specific energy for rotary ultrasonic drilling based on kinematics analysis of vibration effectiveness

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Chinese Journal of Aeronautics 2022年第1期35卷 376-387页

作者： Zhen LI Songmei YUAN Jiang MA Jun SHEN Andre D.L.BATAKO College of Mechatronics and Control Engineering.Shenzhen University Shenzhen 518060China College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China School of Mechanical Engineering and Automation Beihang UniversityBeijing 100083China The General Engineering&Techmology Research Institute Liverpool John Moores UniversitLiverpool L33AF.UK

Rotary ultrasonic drilling(RUD)has become an effective approach for machining advanced composites which are widely using in the field of *** cutting kinematics and the corresponding material removal mechanisms are distinct in different drilling areas during ***,these fundamentals have not been fully considered in the existing *** this research,two distinct forms of interaction induced by ultrasonic vibration were considered as impact-separation and vibratory lapping between the abrasives and *** the conditions to guarantee the effectiveness of these interactions were obtained to eliminate diminishing effects of ultrasonic *** on indentation fracture theory,the penetration depth of abrasives and the axial drilling force model was derived for *** verification tests of C/SiC composites resulted in a prediction error within 15%.Due to the minimal volume of material removed during each vibration cycle,the drilling force was more stable in vibration assisted *** specific drilling energy of RUD was firstly calculated based on the measured drilling *** was found the drilling parameters should be matched with vibration frequency and amplitude to make better usage of the advantages of ultrasonic vibration,which is critical in the vibration assisted processing of advanced materials.

关键词： Ceramic matrix composite Drilling force modelling Kinematics analysis Rotary ultrasonic drilling Specific drilling energy Vibration diminishing effect

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Transient stability enhancement for power grid with MMC-MTDC under N-k contingencies 7

Transient stability enhancement for power grid with MMC-MTDC...

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7th Asia Conference on Power and Electrical engineering, ACPEE 2022

作者： Shi, Zhongpei Long, Yuanjian Wang, Huaizhi Wu, Ting Shenzhen University College of Mechatronics and Control Engineering Shenzhen China Harbin Institute of Technology The School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9781665418195

With the global climate change, the frequency of extreme weather is getting higher and higher, and the threat to the safe operation of the power system is gradually increasing, which is likely to cause large-scale power outages then result in N-k contingencies. Meanwhile, Modular Multi-level Converter (MMC) based Multi Terminal High Voltage Direct Current (MTDC) has been confirmed that can provide the possibility for the network interconnection between regional power systems and various renewable energy resources to boost supply reliability and economy. To enhance the transient stability of the power grid, a generation rescheduling scheme by optimal emergency control that considers the risk-based dynamic security constraint and reactive power constraints is proposed. The proposed strategy can avoid subsequent N-k-1 contingencies in the harsh environment by changing the generating capacity of the generator and the operation state of the MMC. The simulation results from studies on a 10-machine-39-bus power system have been demonstrated the effectiveness of the proposed control strategy. © 2022 IEEE.

关键词： Electric power transmission networks

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Lyapunov control Method Based Optimal control of Alpha-Type Stirling Motor 4

Lyapunov Control Method Based Optimal Control of Alpha-Type ...

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4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2022

作者： Azanpa, Mahmut Vural, Berkem Tas, Ali Ihsan Ozden, Ali Burak Iscan, Mehmet Yildiz Technical University Mechatronics Engineering Department Istanbul Turkey Yildiz Technical University Control and Automation Engineering Department Istanbul Turkey

ISBN: (纸本)9781665468350

Nowadays, the optimally developed system design has been important with the improvement of the technology. The mathematical model approach with the proper controller design provides a more efficient system with its outputs, as well. One of the complex structures is the alpha type Stirling motor in which it is used to control two independent pistons for gaining more power and but makes controlling its dynamics difficult due to its complex structure dynamics in terms of heat and mechanics interactions. In addition to these difficulties, it must be required to design optimal control via system dynamics perspectives because of the characteristics of four different phases. Due to these reasons, in this study, nonlinear Lyapunov-based optimal control for alpha type stirling engine was performed by combining ideal thermodynamic and mechanic equations. The suggested controller was tested under the different reference motor velocities by calculating optimal heat energy consumption via the control rule. After designing two cascade controllers, both mechanical and heat system controls were achieved to optimize heat energy consumption for different motor velocities. It was proved that the proposed method attained high performance for reference tracking of alpha Stirling motor velocities by interacting heat-mechanical system dynamics modeling via Lyapunov control theory. © 2022 IEEE.

关键词： control theory

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Real Time Discrete control Algorithm for Gimbal System Design in Mini Unmanned Aerial Vehicles 4

Real Time Discrete Control Algorithm for Gimbal System Desig...

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4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2022

作者： Tas, Ali Ihsan Iscan, Mehmet Ozden, Ali Burak Cinar, Emre Vural, Berkem Yilmaz, Cuneyt Yildiz Technical University Mechatronics Engineering Department Istanbul Turkey Yildiz Technical University Control and Automation Engineering Department Istanbul Turkey

ISBN: (纸本)9781665468350

Nowadays, gimbal systems have been a very critical role to obtain some important information related to live images photos and target detection in unmanned aerial vehicles. The most basic performance criterion of gimbal systems depends on its stabilization in which the desired reference tracking must be accomplished by designing complex controller structure. For this purpose, a discrete controller design is presented to provide reduced cost, high-performance, 3-axis gimbal systems in real-time operation. Firstly, the mathematical model of the system was obtained and 3D - computer aided design was made in order to calculate the system parameters like inertia, damping factor, etc. After that forward and inverse kinematic equations for the gimbal system were obtained in order to calculate the reference degree in each axis. The discrete controller was derived from energy-based computed torque proportional controller which was based on the Lyapunov Stability Theorem in discrete notation. The reference tracking results at 10 milliseconds sampling time are as follows;0 overshoot for 3 axes with lack of steady-state errors, and the time constants are 0.1575, 0.1610, and 0.27 second which are acceptable for roll, pitch, and yaw axes, respectively. In addition, the discrete-time performance of the proposed controller was compared with a PID controller designed in continuous time, and it was shown that the continuous-time design did not work efficiently as well as discrete time one. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Parallel Driving with Big Models and Foundation Intelligence in Cyber-hysical-ocial Spaces

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Research 2024年第2期2024卷 1-17页

作者： Xiao Wang Jun Huang Yonglin Tian Chen Sun Lie Yang Shanhe Lou Chen Lv Changyin Sun Fei-Yue Wang School of Artificial Intelligence Anhui UniversityHefeiChina Macao University of Science and Technology MacaoChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina MVSLab Department of Mechanical and Mechatronics EngineeringUniversity of Waterloo200 University Ave WestWaterlooON N2L3G1Canada School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs);on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the ?S?goals of parallel driving.

关键词： breakthrough integrate corners

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Online Volt-Var control Based on Reinforcement Learning in Active Distribution Systems Considering PV Inverters 5

Online Volt-Var Control Based on Reinforcement Learning in A...

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5th International Conference on Power and Energy Technology, ICPET 2023

作者： Gu, Changlei Zhang, Xian Wang, Hong Sayed, Ahmed Rabee Wang, Guibin Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen China Electric Power Research Institute China Southern Grid Guangzhou China Shenzhen University College of Mechatronics and Control Engineering Shenzhen China

ISBN: (纸本)9798350339673

Due to the wide deployment of photovoltaic (PV) power generation, voltage stability is facing a severe challenge in the active distribution networks (ADNs). Reinforcement Learning (RL) techniques have been widely adopted in the power system optimal operation and quick control with high-performance achievements. Existing RL algorithms can handle only homogenous control action spaces, i.e., either continuous or discrete actions. However, the voltage control problem has hybrid action spaces. This paper proposes a hybrid soft actor-critic (H-SAC) algorithm for online quick-optimal voltage control. First, the problem is formulated to consider all types of control actions, including the setpoints of PV inverters. Second, it is standardized to be compatible with RL techniques. Third, the fundamental sample-efficient entropy-based maximization SAC algorithm is enhanced to train a policy with hybrid action spaces, where an action selection method is employed to map the continuous output of the actor-network into the integer action spaces. The proposed method is applied to the modified IEEE 33-bus system, where the voltage has been controlled with a very low computational burden. © 2023 IEEE.

关键词： active distribution networks hybrid action spaces Reinforcement Learning Soft Actor-Critic voltage control

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Effective State Estimation for a Class of Nonlinear Systems using Soft Actor-Critic Reinforcement Learning

Effective State Estimation for a Class of Nonlinear Systems ...

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International Conference on Computer Theory and Applications (ICCTA)

作者： Sohila Megahed Ayman El-Badawy Automation and Control German International University Mechatronics Engineering Department German University in Cairo

ISBN: (数字)9798331529680

ISBN: (纸本)9798331529697

A state estimator using soft actor-critic (SAC) reinforcement learning (RL) algorithm is presented in this paper. Estimating states of non linear systems is a challenging task due to the inherent complexities of such systems, including uncertainties, nonlinearities, and measurement noise. Motivated by the need to address these limitations, thereby enhancing control performance, this work proposes an efficient state estimation technique. Specifically, we aim to replace the computationally expensive gain calculation within the Extended Kalman Filter (EKF) with the output of a neural network trained using the SAC algorithm. This approach eliminates the requirement for explicit computation of the covariance and Jacobian matrices, which are significant bottlenecks in the EKF. Consequently, the estimation process exhibits improved efficiency, particularly after the neural network has been adequately trained. To validate the efficacy of the proposed technique, a deep RL agent was implemented, trained, and tested on an unmanned aerial vehicle (UAV) system. The convergence of the estimation error and the observed 71% reduction in simulation execution time serve as evidence for the accuracy and efficiency of this estimation method.

关键词： Estimation error Accuracy Neural networks Reinforcement learning Autonomous aerial vehicles Real-time systems Mathematical models Vectors State estimation Nonlinear systems

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Enhancing Visual Odometry Accuracy Through Block-Based Techniques

Enhancing Visual Odometry Accuracy Through Block-Based Techn...

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Innovations in Intelligent Systems and Applications Conference

作者： Cem Atilgan Muharrem MerciMek Department of Mechatronics Engineering Kirklareli University Kirklareli Turkey Department of Control and Automation Engineering Yildiz Technical University Istanbul Turkey

ISBN: (数字)9798350379433

ISBN: (纸本)9798350379440

Visual odometry (VO) is a method used to estimate the spatial movement of vehicles or camera-equipped systems by analyzing visual data from the environment. It is a cost-effective and accurate alternative to systems like Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS), and is particularly favored in autonomous vehicles, unmanned aerial vehicles (UAV s), and augmented reality applications. This study focuses on the performance challenges faced by visual odometry systems in low-light environments, where traditional systems may not be effective and presents a novel approach, Contrast-Adaptive Block Optimization (CABO), to enhance VO in low-light environments. CABO divides images into blocks and selectively applies Contrast Limited Adaptive Histogram Equal-ization (CLAHE) to darker regions, optimizing image quality without compromising natural appearance. By improving feature extraction and matching, CABO enhances VO accuracy and robustness. We utilized the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) dataset, we demonstrate the effectiveness of the proposed method in improving position and orientation estimation under challenging lighting conditions.

关键词： Visualization Global navigation satellite system Technological innovation Accuracy Lighting Autonomous aerial vehicles Robustness Intelligent systems Optimization Visual odometry

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