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28th International electrical Power Distribution Conference, EPDC 2024

作者： Dousti, Hazhir Hagh, Mehrdad Tarafdar Jirdehi, Mehdi Ahmadi Kermanshah University of Technology Faculty of Electrical Engineering Department of Electrical Engineering Kermanshah Iran University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran

ISBN: (纸本)9798350385502

Due to the increase in demand for electricity, the lack of fossil fuels, and the use of renewable energy sources, the use of energy storage systems becomes necessary. The use of storage systems in different parts of microgrids has countless advantages. These benefits include improving the overall efficiency of the system, increasing the stability of the network, the possibility of optimal control strategies at both the national and regional levels and the effective identification of vulnerabilities in the system. This paper focuses on the issue of coordinated and optimal energy management in a microgrid, especially when dealing with centralized and decentralized storage. This study simultaneously examines the impact of the presence of storage systems in both centralized and decentralized modes, as well as the creation of incentive policies to reduce demand. It examines the interaction between these two factors and their effects on cost reduction and overall network voltage deviation. The work has been done on a standard IEEE network with 69 buses using MATLAB software. It has been shown that in the presence of decentralized energy storage, network performance and consumer consumption are better, and network losses and voltage deviations are also reduced. © 2024 IEEE.

关键词： Renewable energy

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Edge detection using the Prewitt operator with fractional order telegraph partial differential equations (PreFOTPDE)

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Multimedia Tools and Applications 2025年第13期84卷 12329-12345页

作者： Tenekeci, Mehmet Emin Abdulazeez, Sadeq Taha Karadağ, Kerim Modanli, Mahmut Department of Computer Engineering Faculty of Engineering Harran University Şanlıurfa Turkey Department of Mathematics College of Basic Education University of Duhok Duhok Iraq Department of Electrical and Electronics Engineering Faculty of Engineering Harran University Şanlıurfa Turkey Depertmants of Mathematics Faculty of Arts and Sciences Harran University Sanliurfa Turkey

Detecting edges in image processing is an important process in image analysis or enhancement. Many methods detected edge information based on the differences in brightness values. Prewitt, the most widely used edge detection method, performs the extraction of edges by partial differential calculation. This study performed fractional order partial differential calculation with the Telegraph equation in the Prewitt method calculation. Filter coefficients are determined by using Grumwald-Letnikov series expansion for fractional partial differential equation calculation. To determine the most appropriate fraction value, five different coefficients were tried. The proposed method is compared with the conventional edge detection methods Sobel, Canny and standard Prewitt. The obtained result showed that the proposed method detects the edges more accurately. In addition, it has been compared with Prewitt fractional order edge detection (FOED) and edge detection method based on ant colony optimization (ACO) methods developed in recent years. Pratt's figure of merit (FOM) metric was used to compare these studies. It was realized that the FOM values calculated with the proposed method were more accurate than the others methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Edge detection

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Power Prediction of Wind Farm Considering the Wake Effect and its Boundary Layer Compensation

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Protection and Control of Modern Power Systems 2024年第6期9卷 19-29页

作者： Zao Tang Jia Liu Jielong Ni Jimiao Zhang Pingliang Zeng Pengzhe Ren Tong Su the Department of Automation Hangzhou Dianzi UniversityHangzhou 310038China the Department of Electrical and Computer Engineering Rowan UniversityGlassboro 08028USA the Jiaxing Power Supply Company of State Grid Zhejiang Electric Power Company Jiaxing 314000China the Department of Electrical and Computer Engineering University of ConnecticutStorrs 06269USA

With significant expansion in wind farm capacity,wake disturbances from upstream wind turbines have emerged as a detrimental factor,adversely affecting the generated power of downstream ***,the conventional power prediction models usually neglect the wake effect between adjacent wind *** bridge this gap,this paper proposes a novel power prediction model that considers the wake effect and its boundary layer compensation,to enable joint spatial and temporal wind power prediction for wind ***,a two-dimensional convolutional neural network is adopted to extract the key features and reconstruct wind power prediction ***,utilizing historical data,a long short-term memory algorithm is employed to investigate the correlation between elemental characteristics and wind ***,a 3D-Gaussian Frandsen wake model that accounts for the wake effect and boundary layer compensation in wind farms is developed to precisely calculate the spatial wind speed ***,these distributions allow the power outputs of wind turbines in wind farms to be estimated more accurately via the rotor equivalent wind ***,several case studies are conducted to validate the effectiveness of the proposed *** results demonstrate that the suggested approach yields favorable outcomes in predicting both wind speed and wind power.

关键词： Wind farm wind power prediction wake effect 3D-Gaussian Frandsen model spatial-temporal distribution of wind speed.

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Data-driven output regulation control for constrained linear systems

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Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Enhancing biometric authentication security through the novel integration of graph theory encryption and chaotic logistic mapping

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Multimedia Tools and Applications 2025年第16期84卷 16909-16943页

作者： El-Shafai, Walid El-Mesady, A. Kamal, F.M. Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Physics and Engineering Mathematics Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Mathematics and Engineering Physics Department Faculty of Engineering Mansoura University PO 35516 Mansoura Egypt

The escalating reliance on biometric systems for identity verification underscores the imperative for robust data protection mechanisms. Biometric authentication, leveraging unique biological and behavioral characteristics, offers unparalleled precision in individual identification. However, the integrity and confidentiality of biometric data remain paramount concerns, given its susceptibility to compromise. This research delineates the development and implementation of an innovative framework for cancellable biometrics, focusing on facial and fingerprint recognition. This study introduces a novel cancellable biometrics framework that integrates graph theory encryption with three-dimensional chaotic logistic mapping. The methodology encompasses a multifaceted approach: initially employing graph theory for the secure and efficient encryption of biometric data, subsequently enhanced by the complexity and unpredictability of three-dimensional chaotic logistic mapping. This dual-layered strategy ensures the robustness of the encryption, thereby significantly elevating the security of biometric data against unauthorized access and potential compromise. Thus, the resulting cancellable biometrics, characterized by the ability to transform biometric data into an adjustable representation, addresses critical challenges in biometric security. It allows for the revocation and reissuance of biometric credentials, thereby safeguarding the original biometric characteristics of individuals. This feature not only enhances user privacy and data security but also introduces a dynamic aspect to biometric authentication, facilitating adaptability across diverse systems and applications. Preliminary evaluations of the proposed framework demonstrate a marked improvement in the security of face and fingerprint recognition systems. Through the application of graph theory encryption, coupled with three-dimensional chaotic logistic mapping, our framework mitigates the risks associated with t

关键词： Cryptography

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Utilizing Deep Reinforcement Learning for Enhanced Microgrid Voltage Regulation under Fluctuating Load Conditions 4

Utilizing Deep Reinforcement Learning for Enhanced Microgrid...

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4th International Conference on electrical engineering and computer Science, ICECOS 2024

作者： Dinata, Noer Fadzri Perdana Jambak, Muhammad Irfan Ramli, Makbul Anwari Muhammad Sidik, Muhammad Abu Bakar Universitas Sriwijaya Faculty of Engineering Department of Electrical Engineering Palembang Indonesia King Abdulaziz University Faculty of Engineering Department of Electrical and Computer Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798350368253

This study explores the application of Deep Reinforcement Learning (DRL) in controlling a microgrid, with a focus on evaluating the performance of a DRL-based inverter voltage regulator compared to a traditional PID-based controller. The microgrid is subjected to fluctuating load conditions, simulating real-world scenarios where load demand varies significantly. Detailed specifications for the microgrid components are provided, and both control algorithms are tested for their effectiveness in maintaining voltage stability and synchronization with the main grid. Simulation results reveal that the DRL-based controller outperforms the PID controller in tracking the main grid voltage and stabilizing the voltage profile under dynamic conditions. While islanded, the DRL controller achieves a mean absolute deviation of 0.02 from the setpoint, compared to 0.06 for the PID. In grid synchronization, the DRL maintains a synchronization error of less than 6Vrms, while the PID controller exhibits a larger error of up to 15 Vrms. The DRL controller's adaptive learning capabilities allow it to respond more effectively to rapid load changes, reducing deviations and enhancing overall performance. These findings suggest that DRL offers a promising alternative to conventional control methods for microgrids, providing improved reliability and efficiency in environments characterized by high variability. Further research is recommended to optimize DRL algorithms for better voltage stability and synchronization. © 2024 IEEE.

关键词： Deep reinforcement learning

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Ontology-Based Semantic Reasoning for Multi-Source Heterogeneous Industrial Devices Using OPC UA

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IEEE Internet of Things Journal 2025年第13期12卷 25020-25032页

作者： Bi, Jing Wu, Rina Yuan, Haitao Wang, Ziqi Zhang, Jia Zhou, MengChu Beijing University of Technology College of Computer Science Beijing100124 China Beihang University School of Automation Science and Electrical Engineering Beijing China Southern Methodist University Department of Computer Science Lyle School of Engineering DallasTX75205 United States New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States

The advent of smart manufacturing in Industry 4.0 signifies the era of connections. As a communication protocol, Object linking and embedding for Process Control Unified Architecture (OPC UA) can address most semantic heterogeneity issues. However, its semantics are not formally defined at the application layer. To address the information silo problem caused by semantic heterogeneity, an integration framework named Querying of Ontology Mapping-based OPC UA (QOMOU) is proposed. QOMOU extracts information models of OPC UA servers into resource description framework triples and utilizes web ontology language for semantic enrichment and inference. Then, an Event Class Semantic Similarity Calculation (ECSSC) method is proposed for device type identification, enabling the classification of semantically heterogeneous OPC UA devices. The effectiveness of ECSSC is validated through queries with the RDF query language (SPARQL) protocol in Apache Jena. Experimental results demonstrate that ECSSC improves the accuracy of device identification by approximately 7% compared to benchmark device identification models. Specifically, compared with graph embedding-based methods, QOMOU’s query performance is approximately 13% higher, and its query efficiency is 5% higher on average compared to both structured query and extensible markup languages. Moreover, by employing a keyword-matching algorithm, the query accuracy of the existing heterogeneous data integration scheme is improved by 4% on average. This enhancement can boost the operational efficiency of Internet of Things systems based on the OPC UA architecture. © 2014 IEEE.

关键词： Structured Query Language

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Resilient Distributed Optimization for Multi-Agent Cyberphysical Systems

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IEEE Transactions on Automatic Control 2025年第6期70卷 3952-3967页

作者： Yemini, Michal Nedic, Angelia Goldsmith, Andrea J. Gil, Stephanie Bar-Ilan University Faculty of Engineering Israel Arizona State University School of Electrical Computer and Energy Engineering TempeAZ85281 United States Princeton University Department of Electrical and Computer Engineering PrincetonNJ08544 United States Harvard University Computer Science Department School of Engineering and Applied Sciences CambridgeMA02139 United States

This work focuses on the problem of distributed optimization in multi-agent cyberphysical systems, where a legitimate agent's iterates are influenced both by the values it receives from potentially malicious neighboring agents, and by its own self-serving target function. We develop a new algorithmic and analytical framework to achieve resilience for the class of problems where stochastic values of trust between agents exist and can be exploited. In this case, we show that convergence to the true global optimal point can be recovered, both in mean and almost surely, even in the presence of malicious agents. Furthermore, we provide expected convergence rate guarantees in the form of upper bounds on the expected squared distance to the optimal value. Finally, numerical results are presented that validate our analytical convergence guarantees even when the malicious agents compose the majority of agents in the network and where existing methods fail to converge to the optimal nominal points. © 1963-2012 IEEE.

关键词： Multi agent systems

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Analysis of Electric Arc Furnace Influence on Power Quality in Low and Medium Voltage Networks 24

Analysis of Electric Arc Furnace Influence on Power Quality ...

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24th EEEIC International Conference on Environment and electrical engineering and 8th I and CPS Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2024

作者： Grabowski, Dariusz Klimas, MacIej Lange, Andrzej Silesian University of Technology Faculty of Electrical Engineering Department of Electrical Engineering and Computer Science Gliwice Poland University of Warmia and Mazury Faculty of Technical Sciences Department of Electrical and Power Eng. Electronics and Automation Olsztyn Poland

ISBN: (纸本)9798350355185

This paper focuses on analyzing power quality issues resulting from electric arc furnace operation. It highlights the challenges posed by the stochastic nature of the arc and proposes strategies to mitigate its impact on the power grid. Through measurements carried out on the medium and low voltage side of the furnace, fluctuations in parameters such as voltage, current, and power factor were observed, indicating significant disturbances in power quality. Mitigation strategies, including e.g. installing compensators, are suggested to stabilize the network and improve power quality, enhancing efficiency and reducing energy consumption and electrode usage. © 2024 IEEE.

关键词： Electric arc furnaces

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A Compact T-arc-shaped Implantable Antenna for Biomedical Devices 24

A Compact T-arc-shaped Implantable Antenna for Biomedical De...

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14th International Conference on Biomedical engineering and Technology, ICBET 2024

作者： Leelatien, Pongphan Department Of Electrical and Computer Engineering Faculty Of Engineering Thammasat School Of Engineering Thammasat University Thailand

ISBN: (纸本)9798400717628

This paper reports on a single-fed compact slotted implantable patch antenna for biomedical applications. The proposed antenna operates at 915 MHz in the industrial, scientific, and medical (ISM) band. The antenna design features a single T-arc-shaped slot loading on the patch. The antenna is developed using Rogers 3010 as both the substrate and the superstrate. The reported antenna occupies a small volume of π × 42 × 1.27 mm3. It covers the broad bandwidth from 860 to 968 MHz (108 MHz) and exhibits the return loss value of -30.6 dB at the resonant frequency. To address patient safety concerns, the specific absorption rate (SAR) calculation was performed within muscle tissue. The biocompatibility issue for actual implementations was also addressed by means of two commonly utilized methods. These findings suggest the potential of the proposed antenna for implant biomedical applications. © 2024 Owner/Author.

关键词： Medical applications

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