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Effect of Ongrid EV Charging and Discharging on Frequency Profile on an Islanded AC Microgrid 3

Effect of Ongrid EV Charging and Discharging on Frequency Pr...

引用

3rd Odisha international conference on electrical Power engineering, Communication and computing Technology, ODICON 2024

作者： Tripathy, Sabita Sahu, Prakash Chandra Mohapatra, Srikanta Sahu, Binod Kumar Debdas, Subhra Debnath, Manoj Kumar Siksha 'o' Anusandhan University Department of Electrical Odisha India School of Electrical and Comp. Science Indian Institute of Technology Bhubaneswar India School of Electrical Engineering Kiit Deemed to Be University Bhubaneswar India Siksha 'o' Anusandhan University Department of Electrical Engineering Odisha India

ISBN: (纸本)9798350354379

This research article effectively addresses the modeling of an electric car, as well as its integration and effects across a microgrid topology based on renewable energy. The electric vehicle's frequent charging and discharging causes a fluctuation in the frequency of the grid. A variety of variables, such as load dynamics, wind fluctuation in wind plants, variations in solar intensity in photovoltaic plants, etc., can have a significant impact on the performance, particularly frequency, of an islanded AC microgrid. The goal of this research project is to control the system's net power generation in response to overall demand in order to maintain standard frequency. This work designed a fractional order fuzzy PID control mechanism in many dynamic scenarios to monitor net generation. The suggested FO-Fuzzy PID control strategy is the best bet for addressing system frequency stability in the disturbances mentioned above. Under various circumstances, a novel Frank-Wolf Optimization Algorithm (FWOA) is suggested by the ideally calibrated controller gains. When it comes to microgrid system frequency regulation, the best FO-Fuzzy PID controller performs better than both ordinary fuzzy controllers and PID controllers. The findings indicate that the proposed FO- Fuzzy PID control method has the potential to decrease the settling time of ΔF (microgrid frequency) by 250.82% and 98.60%, respectively, in comparison to fuzzy controllers and PID controllers. To further support its superiority, the suggested FWOA's dynamic optimal performance is contrasted with that of the original SCA and PSO approaches. © 2024 IEEE.

关键词： Frequency stability

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The integrated monitoring system for rail transit and the switching method for the main and backup control centers 17

The integrated monitoring system for rail transit and the sw...

引用

IEEE Congress on Cybermatics: 17th IEEE international conference on Internet of Things, iThings 2024, 20th IEEE international conference on Green computing and Communications, GreenCom 2024, 17th IEEE international conference on Cyber, Physical and Social computing, CPSCom 2024, 10th IEEE international conference on Smart Data, SmartData 2024

作者： Song, Jing Zhang, Changkai Che, Xun Nr Electric Co. Ltd Nanjing China Nanjing University of Science and Technology School of Computer Science and Engineering China

ISBN: (纸本)9798350351637

The integrated monitoring system for rail transit is a highly complex control and supervision system used for the regulation and control of various facilities and services in the rail transit network. Due to its high requirement for reliability, it is necessary to establish both a primary and a backup system. When the primary system encounters issues, the backup system takes over the line control authority. When the primary system recovers, the backup system returns the line control authority. However, existing switching methods suffer from issues such as poor reliability and low stability, seriously affecting the safe operation of rail transit. We propose a switching method for the integrated monitoring system and the main and backup control centers of rail transit, aiming to improve the reliability and stability of the integrated monitoring system. Firstly, we establish primary and backup monitoring systems with consistent software and hardware, which operate independently and simultaneously, providing the basic conditions for reliable and stable switching. Secondly, we construct a line control authority switching method that effectively enhances the timeliness of line monitoring during primary system failures through automatic switching of line control authority. Finally, we demonstrate the advantages of our proposed method in terms of stability and reliability through a case study based on real scenarios. © 2024 IEEE.

关键词： Light rail transit

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Impact of Class Labeling on Myocardium Segmentation using Cascaded Deep Learning for Improved Myocardial Infarction Segmentation 14

Impact of Class Labeling on Myocardium Segmentation using Ca...

引用

14th IEEE international conference on control System, computing and engineering, ICCSCE 2024

作者： Damit, Dayang Suhaida Awang Hilmi, A'Isyah Nadiyah Sulaiman, Siti Noraini Osman, Muhammad Khusairi Karim, Noor Khairiah A. Leh, Nor Adni Mat Universiti Teknologi MARA Cawangan Pulau Pinang Permatang Pauh Campus Electrical Engineering Studies College of Engineering Penang13500 Malaysia UiTM Puncak Alam Campus Bandar Puncak Alam Selangor Puncak Alam42300 Malaysia Electrical Engineering Studies College of Engineering Penang13500 Malaysia Advanced Medical & Dental Institute Universiti Sains Malaysia Department of Biomedical Imaging BertamPulau Pinang Kepala Batas13200 Malaysia Advanced Medical & Dental Institute Universiti Sains Malaysia Heart Failure Research Initiative BertamPulau Pinang Kepala Batas13200 Malaysia

ISBN: (纸本)9798350364507

Myocardial infarction is a leading cause of death and illness globally which necessitates early detection and characterization of the infarcted tissue for treatment planning and prognosis. Accurate and fast segmentation of this tissue is crucial for quantifying disease severity. CNNs have shown promise in this area. However, the non-differentiable contrast in Late Gadolinium Enhancement (LGE) MRI poses a challenge for infarcted tissue detection. Additionally, network architecture significantly impacts segmentation performance. Our study proposes a cascaded Deep Learning approach for automatic myocardial infarction segmentation in short-axis LGE cardiac magnetic resonance imaging (CMR). We investigate two cascaded network models (Q and R) that differ in class labeling approaches;single and multi-class labeling. These models specifically search for infarcted tissue within the myocardium, effectively restricting the search area. Notably, Model R achieves slightly better performance with median Dice Score different about 3.51% for infarcted tissue segmentation in the second stage compared to model Q. © 2024 IEEE.

关键词： CNN DeeplabV3++ LGE-CMR LV myocardium Myocardial infarction ResNet50 Xception

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PLC Based Levelling and Positioning control System 9

PLC Based Levelling and Positioning Control System

引用

9th international conference on Advanced computing and Communication Systems, ICACCS 2023

作者： Sheela, A. Shibi, P.S. Vinothkumar, S. Sri Lakshmanar, V. Prasanna, V. Jagadeeshwaran, A. Kongu Engineering College Electrical and Electronics Engineering Erode India Sona College of Technology Electrical and Electronics Engineering Salem India

ISBN: (纸本)9798350397376

Many devices need a high precision horizontal platform during normal operation, and sometimes the horizontal position of the platform needs to be adjusted, such as the isolation switch mechanism box in the power system. In the past there were manual adjustment which takes lot of time and those are not accurate sometimes. This manual adjustment leads to low efficiency and accuracy. The idea is to automate the movement control of the platform. This automation is done by setting up a four-leg platform with automatic control system using PLC. Here the principle of levelling is analyzed and the strategy of raising legs in one direction is proposed which makes the control easy and efficient. Once the platform is moved by any physical or by natural causes the angle is measured by the sensors and the inputs are send to the PLC and the inputs are processed and those output from PLC is send to the relay and the relay controls the electric motor. The motor helps the platform to regain its original position. © 2023 IEEE.

关键词： Efficiency

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automatic Identification Mechanism for Access control System 3rd

Automatic Identification Mechanism for Access Control System

引用

3rd international conference on Machine Vision and Augmented Intelligence, MAI 2023

作者： Sandhya, G. Suresha, S. Shivalingappa, P. Yogish Rao, Vishal Kodabagi, Mallikarjuna Sumitha, B.S. Balasundaram, Tarun School of Computing & Information Technology REVA University Bengaluru India Information Science & Engineering Nagarjuna College of Engineering and Technology Bengaluru India

ISBN: (纸本)9789819743582

The majority of educational institutions still track student attendance using the old-fashioned method (paper-based). Paper-based attendance registers have a variety of problems, including the inability to evaluate the data because it is not uploaded to a centralized system. The embedded cameras on campus will take a picture of it. The faces of all the students are in the database. Students’ photos for future usage. Face recognition was used to capture the student's image. Either students are arriving, or everyone is seated in the space. The student's presence is recognized right away. The final step in the recognition process is to compare the detected face photos to the database of student images. if the image and database are identical. The pupil is noted as being present. Parents will send the student attendance report by mail. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Stealthy False Data Injection Cyberattack Targeting under Load Tap Changing Transformers in Smart Power Grid Causing Abnormal Voltage Profile 3

Stealthy False Data Injection Cyberattack Targeting under Lo...

引用

3rd international conference on Power, control and computing Technologies, ICPC2T 2024

作者： Naderi, Ehsan Asrari, Arash College of Engineering and Computer Science Arkansas State University Department of Electrical Engineering JonesboroAR United States Purdue University Northwest Department of Electrical and Computer Engineering HammondIN United States

ISBN: (纸本)9798350349207

In the process of protecting power systems against different types of cyberattacks, the primary step is to precisely model such frameworks from attacker's perspective. This paper investigates a false data injection (FDI) attack framework, which can target under-load tap changing (ULTC) transformers, resulting in manipulated voltage profile in radial smart distribution networks. The developed FDI model compromises the voltage profile of a distribution feeder through misleading the volt/var optimization, that optimally manages system-wide voltage profile and flow of reactive power. The presented attack model is formulated as a bi-objective optimization problem. The objective functions from the attacker's point of view are 1) minimizing the level of false data to be injected into the smart meters associated with load data and 2) maximizing the voltage deviation of the distribution grid. Negative impacts of such a cyberattack model have been validated and discussed in this work on an IEEE distribution test system, necessitating proper remedial actions, which will be elaborated in the next step of this research. © 2024 IEEE.

关键词： Reactive power

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Implementation of a Water Level control System Using Programmable Logic controller with Remote Access 16th

Implementation of a Water Level Control System Using Program...

引用

16th APCA international conference on automatic control and Soft computing, controlO 2024

作者： Žakelj, Blaž Podržaj, Primož Šolski Center Škofja Loka Škofja Loka4220 Slovenia Faculty of Mechanical Engineering University of Ljubljana Ljubljana1000 Slovenia

ISBN: (纸本)9783031817236

In this paper a water level control system is presented. The system is used for lab exercises in all the courses related to control engineering. It is realized in a way that makes it not dependent on a water supply system, and it also operates with much smaller pressures. The control tasks are realized with a programmable logic controller Siemens S7–1500. The control algorithm is a classical PID. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Three term control systems

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Distributed Computation of Source, Target, and Mixed Strongly Connected Components in Multi-agent Systems 16th

Distributed Computation of Source, Target, and Mixed Stron...

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16th APCA international conference on automatic control and Soft computing, controlO 2024

作者： Ramos, Guilherme Pequito, Sérgio Department of Computer Science and Engineering Instituto Superior Técnico University of Lisbon Lisbon1049-001 Portugal Instituto de Telecomunicações Lisbon1049-001 Portugal Department of Electrical and Computer Engineering Instituto Superior Técnico University of Lisbon Lisbon1049-001 Portugal Institute for Systems and Robotics Instituto Superior Técnico University of Lisbon Lisbon1049-001 Portugal

ISBN: (纸本)9783031817236

Strongly Connected Components (SCCs) play a crucial role in understanding the structural properties of directed graphs, with a plethora of applications across various domains including engineering, computer science and social sciences. In this paper, we propose a method for computing both the source SCCs and target SCCs in a distributed fashion. Our method leverages the decentralized nature of distributed systems to efficiently identify SCCs within large-scale graphs. We illustrate the proposed methods with examples. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Distributed computer systems

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Design and Research of automatic Generation control Code for Dual Three-Phase PMSM Based on FPGA 26

Design and Research of Automatic Generation Control Code for...

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26th international conference on electrical Machines and Systems, ICEMS 2023

作者： Song, Fangzheng Xu, Wei Wang, Jiyao Southeast University Software College Suzhou China Southeast University Electrical Engineering Nanjing China

ISBN: (纸本)9798350317589

This article investigates the impact of the sector control delay problem that has been commonly encountered in traditional multiphase motor control, which reduces the synchronization of motor sectors, increases the ripple amplitude, and reduces control accuracy. To address this issue, this paper proposes a new motor control method based on FPGA parallel computing and parallel control ability. By utilizing the characteristics of FPGA, this method reduces control latency and improves control synchronization. To simplify the development process of this control method, this article adopts a model design method based on HDL Coder to optimize parallel channels and reduce motor control delay time. To experimentally verify this method, a console frame is introduced as the time stamp to evaluate the running time of the algorithm. Under a dual three-phase permanent magnet synchronous motor test platform, the results convince the effectiveness of this high-performance method that can achieve synchronization for multi-phase currents with ripple. The proper configuration of the HDL toolchain is also described that provides fast development of the FPGA control model. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Convolutional Neural Network Based Approach for automatic Detection of Diseases from Pomegranate Plants 8

Convolutional Neural Network Based Approach for Automatic De...

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8th IEEE international conference on Distributed computing, VLSI, electrical Circuits and Robotics, DISCOVER 2024

作者： Rana, Harsh Singh Manjunatha, N. Pokhare, Somnath S. Marathe, Rajiv A. Rajan, Jeny National Institute of Technology Karnataka Dept. of Computer Science and Engineering Surathkal India ICAR National Research Centre on Pomegranate Solapur India

ISBN: (纸本)9798350350593

Recent advancements in Artificial Intelligence, particularly Convolutional Neural Networks (CNNs), have significantly enhanced computer vision tasks, including plant disease detection. India is a global leader in pomegranate cultivation and production. Pomegranate is a vital horticultural commodity with significant export potential but is highly susceptible to various diseases, leading to substantial economic losses. Existing research on automatic pomegranate disease detection has limitations, as it typically analyzes either fruits or leaves in isolation and uses datasets with plain backgrounds that do not reflect real-world complexities such as lighting variations and overlapping foliage. This study proposes a novel hybrid deep learning approach that addresses these limitations. We utilized a hybrid CNN model specifically developed using the pomegranate dataset provided by the ICAR-National Research Centre on Pomegranate. This comprehensive collection includes 1,632 high-resolution images captured from orchards across India, categorized into three classes: healthy, bacterial diseases, and fungal diseases. Our model achieves an impressive accuracy rate of 98.46%, demonstrating its potential for real-world application in pomegranate disease detection and improved agricultural outcomes. © 2024 IEEE.

关键词： Convolutional neural networks

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