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Advancements in Efficient and Sustainable Wireless Charging for Electric Vehicles

Advancements in Efficient and Sustainable Wireless Charging ...

引用

2024 IEEE Region 10 Conference, TENCON 2024

作者： Shufian, Abu Rahman, Md. Tanvir Shib, Sowrov Komar Omi, Mehrab Islam Zishan, Saniat Rahman Fattah, Shaikh Anowarul Saquib, Mohammad American International University-Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh Bangladesh University of Engineering and Technology Dept. of Electrical and Electronic Engineering Dhaka Bangladesh The University of Texas at Dallas Dept. of Electrical Engineering RichardsonTX United States

ISBN: (纸本)9798350350821

The transition to Electric Vehicles (EVs) is crucial for sustainable transportation. However, the adoption of traditional plug-in charging systems remains limited due to their time-consuming nature and infrastructure demands. This study presents a Wireless Power Transfer (WPT) system leveraging inductive coupling to enhance EV charging efficiency, compatibility, and safety. The system converts AC to DC with power factor correction, then transforms it into high-frequency AC to energize the transmitter coil. The receiver coil generates alternating current (AC), which then converts to direct current (DC) for charging the battery. The proposed WPT model, developed using MATLAB Simulink Optimizer, demonstrates a charging efficiency ranging from 90 % to 93 %, resulting in energy losses as low as 10 % to 15 % and improved user convenience by reducing the need for manual plug-in operations. The developed model assumes a standard 60 kWh EV battery can be charged from 20 % to 80 % in approximately 3 hours using the proposed WPT system, compared to 5-6 hours with conventional plug-in chargers. © 2024 IEEE.

关键词： Wireless charging

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A Smart Manufacturing Ecosystem for Industry 5.0 using Cloud-based Collaborative Learning at the Edge 36

A Smart Manufacturing Ecosystem for Industry 5.0 using Cloud...

引用

36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023

作者： Javed, Salman Javed, Saleha Deventer, Jan Van Mokayed, Hamam Delsing, Jerker Lulea University of Technology Dept. of Computer Science Electrical and Space Engineering Luleå97187 Sweden

ISBN: (纸本)9781665477161

In the modern manufacturing industry, collaborative architectures are growing in popularity. We propose an Industry 5.0 value-driven manufacturing process automation ecosystem in which each edge automation system is based on a local cloud and has a service-oriented architecture. Additionally, we integrate cloud-based collaborative learning (CCL) across building energy management, logistic robot management, production line management, and human worker Aide local clouds to facilitate shared learning and collaborate in generating manufacturing workflows. Consequently, the workflow management system generates the most effective and Industry 5.0-driven workflow recipes. In addition to managing energy for a sustainable climate and executing a cost-effective, optimized, and resilient manufacturing process, this work ensures the well-being of human workers. This work has significant implications for future work, as the ecosystem can be deployed and tested for any industrial use case. © 2023 IEEE.

关键词： Automation

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Comparative Analysis of Machine Learning Algorithms for Load Forecasting 4

Comparative Analysis of Machine Learning Algorithms for Load...

引用

4th International Conference on Power, Control and Computing Technologies, ICPC2T 2025

作者： Onteru, Rupesh Rayalu Vuddanti, Sandeep Dept. of Electrical Engineering National Institute of Technology Andhra Pradesh Tadepalligudem India

ISBN: (纸本)9798331530402

Load forecasting involves estimating the optimal quantity of electrical power required for generation. It plays a crucial role for power companies in predicting the necessary power to maintain a balance between supply and load demand consistently. With the increasing trend of deregulation and enhanced competition in the global electric power sector, the importance of load forecasting has intensified These forecasts are essential for facilitating energy transactions within competitive electricity markets. This study concentrates on short-term load forecasting through the use of the Long Short-Term Memory (LSTM) technique, which is a superior alternative to traditional methods due to its ability to manage variability and non-stationarity in load series. The framework is evaluated using a real-time dataset and compared against conventional Support Vector Regression (SVR) and Artificial Neural Networks (ANN). The proposed LSTM model effectively tackles long-term dependency issues, such as vanishing and exploding gradients, demonstrating greater efficiency compared to other methods. © 2025 IEEE.

关键词： Electric utilities

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Elastic Blockchain Security Solution for Edge Computing Supporting Mobile IoT Devices

Elastic Blockchain Security Solution for Edge Computing Supp...

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2024 International Conference on electrical and computer engineering Researches, ICECER 2024

作者： Almubark, Hameed Jedidi, Ahmed Al-Raweshidy, Hamed S. Brunel University London Dept. of Computer Science United Kingdom Ahlia University Dept. of Computer Engineering Manama Bahrain Brunel University of London Dept. of Electronic and Electrical Engineering United Kingdom

ISBN: (纸本)9798331539733

When integrated, blockchain technology and cloud computing (EC) may improve security and protect data. However, when data is sent to EC, the Internet of Things (IoT) device layer cannot guarantee data security. As a result, in the IoT ecosystem, end users and IoT devices are susceptible to assaults. Additionally, as the number of IoT devices rises and generates a large quantity of data, especially in mobile IoT devices, security concerns rise dramatically. High security and privacy standards are necessary for industrial Internet of Things (IIoT) applications in order to safeguard data and guarantee that IoT devices may seamlessly switch to another network. By utilising its decentralised structure, consensus process, and encryption features, blockchain technology can offer a solution. However, because IIoT devices have limited resources, the encryption procedure might be complicated. Actually, in order to secure communication between IIoT devices and EC, this research suggests a new security mechanism built on blockchain technology. Additionally, two security tiers will be used by the Elastic Blockchain Security Solution (EBC) to create a dynamic system for mobile IIoT devices. To evaluate the EBC solution's effectiveness, scalability, and performance, as well as its consensus method and encryption capabilities, it was put into practice and tested in a number of scenarios © 2024 IEEE.

关键词： Industrial internet of things (IIoT)

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A comprehensive step of XAI for Bengali and English text detection and recognition from natural scene images 2

A comprehensive step of XAI for Bengali and English text det...

引用

2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Dutta, Mithun Das, Utpol Kanti Das, Jugal Krishna Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati Bangladesh Jahangirnagar University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350367461

A critical first step in many applications, including augmented reality, document analysis, and scene comprehension, is text detection from images. Even though text identification for the English language has advanced significantly, there are particular difficulties when applying these methods to languages such as Bengali because of variations in script, morphology, and typographic characteristics. This article offers a wonderful method for leveraging the Faster R-CNN framework to identify and categorize text from images that contain Bengali and English sentences. The study utilizes a dataset named "Bengali and English text image dataset (BETID)"that consists of images with text in both Bengali and English scripts, taken from a variety of sources such as books, documents, natural scenes, internet images, and landscapes. Pre-processing methods are used to improve the resilience and generalization of the model, including image scaling, normalization, and augmentation. The Faster R-CNN architecture is tuned and trained to identify text regions in images and categorize Bengali or English text. The performance of the text Classification model is evaluated using evaluation measures such as accuracy on the BETID dataset. The proposed Faster R-CNN model achieved an average of 97.90% accuracy, which is better than other deep learning models. Empirical findings showcase the capacity of transfer learning to alleviate data scarcity concerns and enhance text detection precision for low-resource languages such as Bengali.) © 2024 IEEE.

关键词： Deep learning

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ANN Based Approach for Detection of Islanding Using HOG Features 2

ANN Based Approach for Detection of Islanding Using HOG Feat...

引用

2nd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Pal, Kumaresh Bhuyan, Anshuman Benia, Tapas Kumar Jena, Kasinath National Institute of Technology Department of Electrical Engineering Jamshedpur India Gandhi Institute for Education & Technology Dept. of Electrical Engineering Bhubaneswar India National Institute of Technology Department of Electrical Engineering Arunachal Pradesh India Arka Jain University Dept. of Electrical and Electronics Engineering Jamshedpur India

ISBN: (纸本)9798350360523

In this paper, a novel approach for detecting islanding based upon image categorisation using Artificial Neural Network (ANN) is proposed. Images are used to derive the histogram of oriented gradient (HOG) characteristics so as to identify non-islanding as well as islanding events. In the suggestive method, spectrogram images are obtained from the time-series signal which are derived from the point of common coupling. These images are utilised to extract the features using histogram of oriented gradient, which is then utilised as a feature input for the ANN model for training as well as testing. It uses rate of change of negative sequence voltage parameter for deriving spectrogram image. The results from classification demonstrates that detection of islanding using ANN method and HOG features being used for image classification achieved excellent results with 97.3 % accuracy and mean square error of 0.0002. © 2024 IEEE.

关键词： Neural networks

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PIR-R Control for Three-Phase Grid-Connected Inverter with Unbalanced Grid Current Correction 14

PIR-R Control for Three-Phase Grid-Connected Inverter with U...

引用

14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Ghanayem, Haneen Yang, Xingyu Alathamneh, Mohammad Nelms, R.M. Al-Huson University College Al-Balqa Applied University Dept. of Electrical Engineering Irbid Jordan Auburn University Dept. of Electrical and Computer Engineering AuburnAL United States

ISBN: (纸本)9798331516116

Proposed in this paper a proportional-integral-resonant-resonant (PIR-R) control method for a three-phase grid-connected inverter. Unbalanced loads at the point of common coupling (PCC) can disrupt grid current balance and adversely impact other PCC connections, impairing the inverter's ability to accurately track active and reactive power commands. The PIR-R control integrates PI and PR components for fundamental reference current tracking and second-order harmonic rejection. The first resonant controller component targets the grid frequency, while the second addresses the double-frequency oscillations caused by unbalanced grid currents. Without the need for additional correction devices such as shunt active power filters at the PCC, the PIR-R method ensures effective reference command tracking and corrects unbalanced grid currents. Simulation and experimental results confirm that the PIR-R control provides improved transient response and reduced steady-state error compared to conventional methods. © 2025 IEEE.

关键词： Proportional control systems

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Performance Analysis of Modified Leaky LMS Based Control Scheme for Single-Stage and Dual-Stage Three-Phase Grid-Tied PV System 1

Performance Analysis of Modified Leaky LMS Based Control Sch...

引用

1st IEEE International Conference on Smart and Sustainable Developments in electrical engineering, SSDEE 2025

作者： Rathod, Urvashiben Pawar, Darsh V. Chauhan, Siddharthsingh K. Parida, Abhisek Tekwani, P.N. Institute of Technology Nirma University Dept. of Electrical Engineering Ahmedabad382481 India

ISBN: (纸本)9798331542108

Photovoltaic (PV) based distributed generation (DG) helps meeting continuously increasing power demand. Effective control of PV-based DG becomes crucial for its integration into the power network. This paper presents a Modified Leaky Least Mean Square (MLLMS) algorithm based control scheme for SSGPV and DSGPV three-phase grid-tied PV system. The DSGPV system consists of a PV array, a dc-dc boost converter controlled using Incremental Conductance (InC) technique for maximum power point tracking (MPPT) operation and three-phase DG for dc to ac conversion, which is integrated with the utility grid. In a SSGPV system, DG is controlled for MPPT operation as well as power exchange with the grid and load. The presented grid-tied DG employs MLLMS based control scheme to generate the reference grid currents. Simulation analysis of the given SSGPV and DSGPV DG performance is carried out using MATLAB. The PV based DG effectively exchanges power with the grid as well as feeds to the load. It balances grid currents even in case of unbalanced load condition. The transient response of the DG is analysed for irradiation change and load unbalanced condition. Simulation results depict satisfactory steady-state as well as transient response of grid-tied PV based DG. © 2025 IEEE.

关键词： Distributed power generation

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Futuristics Technologies for Reduction of Plastic Waste 13

Futuristics Technologies for Reduction of Plastic Waste

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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Dhiman, Riya Sharma, Ashish Chandigarh University Dept. of Computer Science Mohali India Chandigarh University Dept. of Electrical Engineering Mohali India

ISBN: (纸本)9798350380583

Plastic plays a vital role in daily life most of the food items, Baggies, vegetables are packed in plastic material. As plastic is non-biodegradable there are harming effect on human beings and animals. Due to these global warming also increases. Although 80% Fishes, 88% Vertebrates, 56% Mammals and 52% Reptiles are affected due to plastic waste. In this work with the various techniques proposed like Eco-bricks, Furniture, Replace Plastic By Bamboo and also Doormats are made through the Plastic Waste. It is seen that by using above techniques significantly reduce the harmful effect of plastic and there is improvement in life of human beings and animals also the alternative techniques to reuse the plastic and to replace plastic are proposed with which there is a increase in the earning of poor peoples. Above techniques are helpful to decrease the employment and also by using these techniques more than 60% of plastic reuse, with this the temperature is also decreased. © 2024 IEEE.

关键词： Invertebrates

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Identification of PMU Measurements-Based Low-Frequency Oscillation Modes in the IEEE 39 Bus System via DMD 5

Identification of PMU Measurements-Based Low-Frequency Oscil...

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5th IEEE International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2024

作者： Adam, Mohammed Elmubarak Das, Biswarup Mohammed, Bahaaldeen Indian Institute of Technology Roorkee Dept. of Electrical Engineering Roorkee India

ISBN: (纸本)9798350352863

The implementation of phasor measurement units (PMUs) in power grids has revolutionized the monitoring and management of power systems, allowing for precise voltage and current phasor measurements at high sampling rates. However, the increasing complexity and interconnectivity of power systems have led to the emergence of low-frequency oscillations, posing a significant threat to system stability. This article explores the use of the Dynamic Mode Decomposition (DMD) algorithm to accurately identify these oscillation modes from PMU measurements. Early detection of these oscillations is crucial for preventing potential blackouts and minimizing economic and societal impacts. The DMD technique is applied to an IEEE 10-Machine, 39-Bus system subjected to a fault, with real power flow measurements taken over specific lines. The methodology includes data collection, processing, and mode identification using the DMD algorithm. The algorithm effectively identifies dominant oscillation modes, their frequencies, and damping ratios, showcasing its potential for system analysis and control. This study demonstrates the applicability of the DMD algorithm to other power systems and its potential for real-time application and analysis of measurement noise impact. © 2024 IEEE.

关键词： Phasor measurement units

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