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control and Optimization Circuit of Solar Electric Vehicles 1

Control and Optimization Circuit of Solar Electric Vehicles

引用

1st international conference on intelligent Technologies for Sustainable Electric and Communications systems, iTech SECOM 2023

作者： Amrudha Harshan, P.R. Vigneshwaran, S. Ajithkumar, R. Karunamoorthy, B. Kumaraguru College of Technology Department of Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798350371185

This paper is focused on the control method of a Solar electric vehicle in the future which may become a reality. The proposed control system below is used for the solar electric vehicle, which relies on solar energy for 100% of its energy needs and it uses battery as its secondary source of energy, which is the vice versa of the present electric vehicles, where the solar energy is used as additional source instead of the main source. This specializes on the switching control methods between the Battery and the inverter which gives the supply straight to the load usually the motor load. The energy from the solar panel is directly transferred to the motor instead of coming from the battery. The recommended microcontroller-based system is designed to detect the electricity from the solar panel the car relieson. The energy from the panel is continuously checked using a sensor system and delivers feedback to the controller regarding the status. When the energy from the panel is less or not enough, the switching circuit directly switches to the battery, which is a secondary source of power in the car. As a result, this enables smooth movement of the vehicle without any jerk when there is no electricity. © 2023 ieee.

关键词： Timing circuits

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Coordinated Optimal Scheduling of Power System with Wind Power Considering the Flexibility Space of Energy-intensive Load and Pumped Storage 3

Coordinated Optimal Scheduling of Power System with Wind Pow...

引用

3rd international conference on Power systems and Electrical technology, PSET 2024

作者： Li, Lingfang Yue, Xiaoyu He, Xuehao Yang, Jiaquan Pan, Ruxiang Liao, Siyang Yunnan Power Grid Corporation Ltd Power Grid Planning and Construction Center Yunnan China Wuhan University Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network School of Electrical Engineering and Automation Wuhan China Electric Power Research Institute Yunnan Power Grid Corporation Ltd Kunming China

ISBN: (纸本)9798350353204

Insufficient peak regulation capacity in the power system limits wind power integration. Energy-intensive industrial loads and pumped storage stations offer substantial capacity and rapid adjustment, yet their potential remains underutilized. This study proposes a coordinated optimization method considering both factors. It analyzes the flexible regulation of energy-intensive loads, establishes their regulation model, and similarly for pumped storage, considering its flexibility margin. Additionally, it creates a multi-resource coordination optimization model, factoring in the economic aspects of thermal power deep peak shaving. Tested on a typical system, the proposed model can significantly reduce the wind curtailment rate of the system, greatly reduce the total operating cost of the system, and improve the economy of thermal power. Meanwhile, the utilization rate of the pumped storage unit is improved, the potential of energy-intensive load regulation is excavated, and the peak load regulation structure of the system is reasonably optimized. © 2024 ieee.

关键词： Wind power integration

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Enhancing Performance of Full-Duplex Cooperative NOMA systems via Reconfigurable intelligent Surface

Enhancing Performance of Full-Duplex Cooperative NOMA System...

引用

2024 international conference on Advanced Technologies for Communications, ATC 2024

作者： Van Nguyen, Minh-Sang Thanh, Tran Thien Bao, Vo Nguyen Quoc Ho Chi Minh City University of Transport Faculty of Information Technology Ho Chi Minh City70000 Viet Nam Posts and Telecommunications Institute of Technology Department of Electrical Engineering Ho Chi Minh City70000 Viet Nam School of Technology Van Lang University Faculty of Information Technology Ho Chi Minh City70000 Viet Nam

ISBN: (纸本)9798350353983

In recent years, the advancement of Recon-figurable intelligent Surfaces (RIS) in wireless communications has empowered the control of radio waves, mitigating the adverse effects of natural wireless propagation. This technology has demonstrated substantial gains in spectrum within wireless net-works. Concurrently, Non-Orthogonal Multiple Access (NOMA) technology has emerged as a promising solution to enhance spectrum efficiency in fifth-generation and subsequent wireless networks. Motivated by these advancements, we explore the ap-plication of RIS-based NOMA networks in the downlink scenario, incorporating interference Full-Duplex (FD) with two users. Furthermore, we assess the performance of the proposed system by analyzing the Outage Probability (OP) through analytical derivations. Simulation results underscore: (i) the validation of analytical formulas;and (ii) the pivotal role played by the number of metasurfaces in RIS, transmit power at the base station, power allocation parameters, target data rate for two users in enhancing system performance. © 2024 ieee.

关键词： Radio communication

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Structuring intelligent automation: A Hyperautomation Taxonomy 58

Structuring Intelligent Automation: A Hyperautomation Taxono...

引用

58th Hawaii international conference on System Sciences, HICSS 2025

作者： Neis, Nicolas Kathol, Elise Winkelmann, Axel University of Würzburg Germany

ISBN: (纸本)9780998133188

Hyperautomation is an emerging technology stack that combines various automation technologies to streamline and optimize business processes. Companies increasingly adopt these technologies to reduce costs, increase efficiency, and gain a competitive advantage. This study focuses on combining the different technologies under the hyperautomation approach. From a management perspective, we examine the benefits and challenges of hyperautomation that focus on increasing company productivity. Based on a literature review, we develop a taxonomy that enables a profound understanding of the complex hyperautomation landscape. Findings underscore the substantial potential of hyperautomation to improve productivity, particularly through cost and time savings and enhanced employee efficiency. This research addresses the lack of systematization in previous studies, presenting a nuanced understanding of hyperautomation's implications for managerial strategies. © 2025 ieee Computer Society. All rights reserved.

关键词： Empowerment of personnel

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Research on Medical Equipment Operation State Monitoring and Early Warning technology of Failure

Research on Medical Equipment Operation State Monitoring and...

引用

2024 international conference on Power, Electrical Engineering, Electronics and control, PEEEC 2024

作者： Huang, Hangliang Shengzhou Hospital of Traditional Chinese Medicine Zhejiang Shengzhou312400 China

ISBN: (数字)9798350378917

ISBN: (纸本)9798350378917

With the continuous advancement of medical technology, medical devices play a crucial role in clinical diagnosis and treatment. However, malfunctioning of medical equipment may lead to serious medical accidents and affect the health and safety of patients. Therefore, how to effectively monitor the operation status of medical devices and realize early warning of failures has become an urgent problem. This study is dedicated to exploring and developing advanced monitoring techniques and early warning systems to improve the reliability and safety of medical equipment. This paper firstly reviews the existing medical device monitoring technologies and their limitations, and then explores the application of sensor technology, data acquisition and processing, machine learning and artificial intelligence in medical device monitoring, and analyzes the integration of remote monitoring and Internet of Things (IoT) technologies. Subsequently, the paper describes the construction method of the early warning system for failures, including the establishment of warning models, data analysis and prediction techniques. Through specific case studies, the paper demonstrates the practical application effects of these technologies. Finally, the paper discusses the challenges that may be faced during the implementation of these technologies and looks forward to the future development direction. The study shows that the combination of advanced monitoring technologies and intelligent warning systems can significantly improve the operational efficiency and safety of medical devices and provide strong support for the medical industry. © 2024 ieee.

关键词： Patient treatment

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Application of a Multi Wing Chaotic System in Image Encryption 4

Application of a Multi Wing Chaotic System in Image Encrypti...

引用

4th international conference on Neural Networks, Information and Communication Engineering, NNICE 2024

作者： Shen, Min Wang, Yanling Li, Xiumin Zhao, Wenjing Guo, Shengjin Dai, Wenpeng Qilu Institute of Technology School of Intelligent Manufacturing and Control Engineering Jinan China Yantai University of Science and Technology School of College of Ocean Engineering Yantai China

ISBN: (纸本)9798350394375

Firstly, the dynamic characteristics of Lyapunov exponent, bifurcation diagram, power spectrum and equilibrium point stability of a class of six-wing chaotic system are analyzed theoretically and simulated numerically. The results show that the system has rich dynamic characteristics. Based on the circuit simulation software Multisim14, the experimental simulation circuit is made. The circuit is simple and easy to implement, which proves the achievability of the proposed chaotic system circuit in circuit principle, and thus verifies the chaotic dynamics capability of the chaotic system. Finally, the DNA algorithm and the new system chaotic sequence are adopted to encrypt the image, and the encrypted histogram, information entropy and the correlation of adjacent pixels are analyzed. The analysis results show that the proposed chaotic system has high security performance when applied to image encryption. © 2024 ieee.

关键词： Chaotic systems

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Prediction model of photovoltaic output power based on VMD-EMD-BiLSTM

Prediction model of photovoltaic output power based on VMD-E...

引用

Industrial cyber-Physical systems (ICPS)

作者： Shaolong Zheng Danyun Li 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 Wuhan China

The accuracy of photovoltaic (PV) power prediction is significantly influenced by the high complexity and volatility of the PV sequence. The existing methods for predicting photoelectric power are difficult to effectively mine and analyze the internal variation law of data. To improve the accuracy of PV power prediction, a new method is proposed that first performs variational mode decomposition (VMD) and empirical mode decomposition (EMD), and then establishes a bi-directional long and short-term memory neural network (BiLSTM) for PV output power prediction. The proposed method extracts the amplitude and frequency characteristics of the PV output power series through VMD. After that, the residual term with strong non-stationarity is generated, which still has more sequence characteristics. The residual term is then decomposed by EMD for the second time to extract more features. Finally, the BiLSTM model is established to conduct bidirectional mining for PV power data and predict PV output power. The actual PV data is used to test the experimental results, which show that the proposed VMD-EMD-BiLSTM prediction model has better prediction performance.

关键词： Photovoltaic systems Empirical mode decomposition Simulation Neural networks Predictive models cyber-physical systems Prediction algorithms

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Proceedings of the 2022 ieee international conference on Dependable, Autonomic and Secure Computing, international conference on Pervasive Intelligence and Computing, international conference on Cloud and Big Data Computing, international conference on cyber Science and technology Congress, DASC/PiCom/CBDCom/cyberSciTech 2022

Proceedings of the 2022 IEEE International Conference on Dep...

引用

20th ieee international conference on Dependable, Autonomic and Secure Computing, 20th ieee international conference on Pervasive Intelligence and Computing, 7th ieee international conference on Cloud and Big Data Computing, 2022 ieee international conference on cyber Science and technology Congress, DASC/PiCom/CBDCom/cyberSciTech 2022

ISBN: (纸本)9781665462976

The proceedings contain 185 papers. The topics discussed include: wearable IMU based gait quality quantitative evaluation method;quantum computing approach for energy optimization in a prosumer community;raising citizens and institutions awareness of environmental problems using smart sensing technologies;event detection in financial markets;design-space exploration of quantized transposed convolutional neural networks for FPGA-based systems-on-chip;seamless sensor data acquisition for the edge-to-cloud continuum;occupancy prediction in buildings: an approach leveraging LSTM and federated learning;lightweight model by iterative momentum pruning scheme for channel reduction;a deep reinforcement learning based approach for intelligent reconfigurable surface elements selection;exploiting mobility data to forecast Covid-19 spread;machine learning methods for microwave imaging in cancer detection;and physical activity recognition using deep transfer learning with convolutional neural networks.

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Research on Energy Management Strategy of intelligent Building Microgrid Based on Particle Swarm Optimization 2

Research on Energy Management Strategy of Intelligent Buildi...

引用

2nd international conference on Power systems and Electrical technology, PSET 2023

作者： Ni, Gaojun Zheng, Wenjun Li, Ping Zheng, Kai Yuan, Songlin Zhejiang University Center for Balance Architecture Hangzhou China The Architectural Design & Research Institute of Zhejiang University Co. Ltd. Hangzhou China

ISBN: (纸本)9798350339703

The energy management optimization model of AC-DC hybrid microgrid system for intelligent buildings based on Simulink is introduced. Under the incentive of time-of-use price, the life expenditure of the energy storage battery is taken into account, and the optimal distribution scheme of the energy storage system under this time-of-use price is sought by using particle swarm optimization, so as to achieve the lowest daily cost of AC-DC hybrid microgrid. On this basis, the influence of the input and output power on the converter efficiency is further considered, and the maximum economic benefit of the system is realized by dynamically changing the charge-discharge power of the energy storage battery. A practical case is given to verify the effectiveness of the control strategy. © 2023 ieee.

关键词： Energy management systems

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Developing an Electroencephalogram Based Robotic Motion control System Using Brainwaves Enabled Signal Processing Technique

Developing an Electroencephalogram Based Robotic Motion Cont...

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2024 international conference on Innovative Computing, intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Govindaraj, R. Ranjith, S. Deepthi, K. Babu, K. Kishore Bodkhe, Rajesh G. Amer, Ayman Saveetha School of Engineering Dept of Ece Chennai India Jeppiaar Engineering College Department of Ece Rajiv Gandhi salai Chennai119 India Qis College of Engineering and Technology Department of S&h Pondur Road Vengamukkapalem Ongole Prakasam AndhraPradesh PrakasamDistrict523272 India Qis College of Engineering and Technology Department of Aimlds Pondur Road Vengamukkapalem Ongole Prakasam AndhraPradesh PrakasamDistrict523272 India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Zarqa University Department of Energy Engineer zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331543617

This work presents the development of an Electroencephalogram (EEG)-based robotic motion control system utilizing brainwave-enabled signal processing techniques. The system is designed to translate mental commands into real-time robotic actions, offering a non-invasive brain-computer interface (BCI) for users. The system involves EEG signal acquisition, preprocessing, feature extraction, and classification using machine learning algorithms, followed by robotic control via a real-time interface. Data was collected from 10 participants performing four mental tasks: move forward, turn left, turn right, and stop. The classification accuracy across these tasks ranged from 84% to 94%, with an average accuracy of 88%. Response times for translating mental commands into robotic actions varied between 205 milliseconds and 280 milliseconds, ensuring near real-time control. Testing under different environmental conditions (normal, noisy, fatigued) showed the system's robustness, although there was a slight drop in accuracy under noisy (80-85%) and fatigued (81-88%) conditions. User satisfaction scores indicated a positive overall experience with high ratings for ease of use and perceived accuracy. The results demonstrate the system's potential for applications in assistive technologies and rehabilitation robotics. © 2024 ieee.

关键词： Assistive technology

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