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Modeling Method for DFIG-Based Wind Farm in High-Efficiency Real-Time Electromagnetic Transient (EMT) Simulations

IEEE Transactions on Power Electronics 2025年

作者： Liu, Yifan Xu, Jianzhong Zhu, Yiyang Tian, Zhaoxuan Zhao, Chengyong Li, Gen State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources China Energy Technology and Computer Science Section Department of Engineering Technology and Didactics Ballerup2750 Denmark

With the increasing integration of renewable energy into power systems, electromagnetic transient (EMT) simulation has become indispensable for accurate system analysis. However, the complexity of wind turbine (WT) modeling, characterized by a large number of electrical nodes, poses significant challenges and necessitates substantial real-time simulation hardware. Existing methods for reducing circuit complexity improve simulation efficiency but are each associated with inherent limitations. Aggregation methods sacrifice considerable internal station information, while existing decoupling techniques are constrained by specific requirements. This paper proposes a real-time simulation model for a Doubly Fed Induction Generator (DFIG)-based wind farm (WF) using latency decoupling and a multi-level nested fast and simultaneous solution (M-NFSS) approach, effectively reducing node count while preserving internal details. A WF test model is implemented in RTDS for validation. Results demonstrate highly accurate impedance characteristics and time-domain waveforms of the proposed model, utilizing only 33.3% of the hardware resources compared to the traditional detailed model. © 1986-2012 IEEE.

关键词： Electromagnetic transients

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Carbon Nanotubes Enhancement of Fiber Bragg Grating Surface Plasmon Resonance Sensor 25

Carbon Nanotubes Enhancement of Fiber Bragg Grating Surface ...

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25th International Electronics Symposium, IES 2023

作者： Thirunavakkarasu, Punithavathi Khan, Abdul Ali Shabaneh, Arafat Saidin, Norazlina Bte Sulaiman, Muhammad Syahnizam Noor, Ahmad Shukri Muhammad Universiti Kuala Lumpur Communication Technology Section British Malaysia Institute Gombak Malaysia Palastine Technical University-Kadoorie Department of Telecommunication Technology Engineering Tulkrarm Palestine International Islamic University Malaysia Department of Electrical and Computer Engineering Kuala Lumpur Malaysia Universiti Putra Malaysia Faculty of Engineering Department of Cmputer and Communication Systems Engineering Selangor Malaysia

ISBN: (纸本)9798350314731

In this research, a telecommunication standard fiber Bragg grating is sputtered with a 45 nm gold film to obtain surface plasmon resonance. Carbon nanotubes are deposited over the gold layer for sensitivity enhancement due to its unique chemical and optical properties. The developed sensor is interrogated with a broad-spectrum light source and spectrophotometer setup in the visible region and the sensing performance is analyzed. The sensor showed high sensitivity of 526 nm/RIU which was more than 4 time higher than a sensor without the carbon nanotubes enhancement. This shows great promise in the application of CNTs and possibly other sensitive nanomaterials as sensing enhancements of future sensing using optical fibers. © 2023 IEEE.

关键词： Surface plasmon resonance

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An Investigation Through Stochastic Procedures for Solving the Fractional Order computer Virus Propagation Mathematical Model with Kill Signals

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Neural Processing Letters 2023年第2期55卷 1783-1797页

作者： Sabir, Zulqurnain Raja, Muhammad Asif Zahoor Mumtaz, Nadia Fathurrochman, Irwan Sadat, R. Ali, Mohamed R. Department of Mathematics and Statistics Hazara University Mansehra Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Department of Computer Science Iqra University Islamabad Campus Islamabad Karachi Pakistan Department of Islamic Educational Management Institute Agama Islam Negeri Curup Rejang Lebong Indonesia Department of Mathematics Zagazig Faculty of Engineering Zagazig University Zagazig Egypt Faculty of Engineering and Technology Future University Cairo Egypt

In this study, the numerical investigations through the stochastic procedures for solving a class of fractional order (FO) computer virus propagation (CVP) mathematical model with kill signals (KS), i.e., CVP-KS is presented. The KS gets alert about those viruses, which can be infected through the computer system to decrease the virus propagation danger. The mathematical model of the CVP-KS is based on the SEIR-KS model. The focus of these investigations is to present the numerical solutions of the FO-SEIR-KS model using the sense of Levenberg–Marquardt backpropagation scheme (LMBS) together with the neural networks (NNs), i.e., LMBS-NNs. The use of the one dynamic of the other makes the model nonlinear. Three different FO values have been used to check the performances of the designed scheme for this FO-SEIR-KS nonlinear mathematical model. The statics used in this study is 80%, 10% and 10% for training, testing and certification for solving the FO-SEIR-KS nonlinear mathematical model. The numerical simulations are performed through the stochastic LMBS-NNs scheme for solving the FO-SEIR-KS nonlinear mathematical model. The obtained results will be compared with the design of database reference solutions based on the Adams–Bashforth–Moulton. In order to accomplish the validity, capability, consistency, competence and accuracy of the LMBS-NNs, the numerical results using the error histograms, regression, mean square error, state transitions and correlation have been provided. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Mean square error

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AI-Enabled Predictive Maintenance for Industrial Equipment in the Era of IoT 9

AI-Enabled Predictive Maintenance for Industrial Equipment i...

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9th International Conference on Science, technology, engineering and Mathematics, ICONSTEM 2024

作者： Subbiah, Muthu Raman Devi, Kabirdoss Dhanamalar, M. Shareef, Ashraf Mohammed Ai-Shaikhli, Taha Raad Nidamanuri, Sudheer University of Technology And Applied Sciences Mie Section Department of Engineering Muscat Oman School of Management Studies Vels Institute-of Science Technology And Advanced Studies Chennai Tamil Nadu Pallavaram600117 India Kristu Jayanti College Department of Computer Science Karnataka Bengaluru India College of Pharmacy National University of Science And Technology DhiQar Iraq AL-Nisour University College Department of Medical Laboratories Technology Baghdad Iraq Madanapalle Institute of Technology And Science Computer Science And Technology Andhra Pradesh Madanapalle517325 India

ISBN: (纸本)9798350365092

Modern digital technology breakthroughs include machine learning. It's used in medical, image processing, manufacturing, aviation, autonomics, and more. Our main goal is to find an automated system that can accurately rate production machines at any given moment. The critical energy meter characteristics needed to create power reports in automation system to solve production difficulties at defined intervals were also not captured. We apply machine learning to estimate manufacturing machine accuracy in this study. We employed supervised machine learning of binary decision tree using CART method and power report, obtained data using RS232 to RS485 convertor through Modbus communication protocol, to overcome these challenges. This study presents issue formulation, energy meter data analysis and retrieval, and ML approaches used to estimate production machine accuracy. After retrieving the parameters, we provide power reports for each machine and a graphical warning of deteriorating performance. © 2024 IEEE.

关键词： Internet of things

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Downsampling consistency correction-based quality enhancement for CNN-based light field image super-resolution

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Multimedia Tools and Applications 2024年第34期83卷 80919-80939页

作者： Chung, Kuo-Liang Hsieh, Tsung-Lun Department of Computer Science and Information Engineering National Taiwan University of Science and Technology No. 43 Section 4 Keelung Road Taipei10672 Taiwan

In recent years, numerous CNN-based light field (LF) image super-resolution (SR) methods have been developed. However, due to the downsampling inconsistency between low-resolution (LR) testing LF images and LR training LF images, they may suffer from quality degradation. To address this quality degradation issue, this paper proposes a downsampling consistency correction-based (DCC-based) quality enhancement method. Firstly, a quality-based voting strategy is introduced to identify the downsampling scheme used in the training step. Next, a cascaded Swin Transformer-based recognizer is proposed to identify the downsampled position and downsampling scheme used in the LR testing LF image, after which the proposed DCC-based method is employed to significantly improve the quality of the upsampled LF image. Comprehensive experiments have been conducted on typical LF image datasets to demonstrate the significant quality improvement achieved by our method in comparison to state-of-the-art LF SR methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image enhancement

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Eight-direction least-square phase unwrapping algorithm for optical three-dimensional measurement 3

Eight-direction least-square phase unwrapping algorithm for ...

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3rd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： He, Yantao Liu, Sijia Pan, Minling Wang, Rongfu Li, Xueri Zhang, Rong Department of Computer Science Guangdong University of Science and Technology No. 2 Songshan Lake Section 523668 China School of Mechanical Engineering Hunan University of Science and Technology Taoyuan Road 411201 China School of Electronics and Information Engineering Beibu Gulf University No. 12 Binhai Avenue 535011 China

ISBN: (纸本)9781510668522

The least-square method is widely used in the fast phase unwrapping of optical three-dimensional measurement due to its high-speed and comprehensive characteristics. In order to solve the problem of measurement error propagation in the phase unwrapping algorithm based on least-square method, an improved eight-direction least-square phase unwrapping algorithm is proposed in this paper. This algorithm not only researches the gradient difference between the target phase and its eight-neighbor phases, improving measurement accuracy and reducing measurement errors. The superiority and robustness of this algorithm have been demonstrated through simulation data and measurement of industrial bearing roller end faces © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Measurement errors

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Artificial Intelligence Scoring Algorithm for English Translation Based on DNN 2

Artificial Intelligence Scoring Algorithm for English Transl...

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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Priya, R. Krishna Aanandha Saravanan, K. Gadgil, Aashish A. Sabarmathi, K.R. Niranjanamurthy, M. Azarudeen, K. Department of Engineering-Electrical section College of Engineering and Technology University of Technology and Applied Sciences Shinas Oman Department of ECE Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and technology Chennai India Department of ECE KLS GOGTE institute of Technology Karnataka Belagavi India Department of Information Technology Bannari Amman Institute of Technology Tamilnadu Sathyamangalam India Department of AI and ML BMS Institute of Technology and Management Avalahalli. Karnataka Bangalore India Department of Computer Science and Engineering Velammal College of Engineering and Technology Madurai India

ISBN: (纸本)9798350305418

With the popularity of languages and the increasing demand for language translation, the optimization of artificial intelligence scoring algorithm for English translation has become the urgent need of the translation market. Based on the deep neural network(DNN) algorithm, it continuously integrates modern technology to realize information collection, storage, analysis and application, which promotes the deep integration of the DNN algorithm in the field of intelligent identification and expands the application scope of artificial intelligence identification technology. This paper focuses on how to efficiently optimize the model of English translation artificial intelligence scoring algorithm by DNN, specifically studying the DNN model, by studying the mathematical model and algorithm flow of the DNN optimization algorithm, and the basic principle of the DNN model;Based on the DNN model, a learning ability analysis model of English translation algorithm is proposed. Experiments show that this model can optimize the artificial intelligence scoring algorithm of English translation. © 2023 IEEE.

关键词： Artificial intelligence scoring algorithm DNN English translation

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Maximizing Stable Throughput in Age of Information-Based Cognitive Radio

Maximizing Stable Throughput in Age of Information-Based Cog...

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2022 IEEE International Conference and Expo on Real Time Communications at IIT, RTC 2022

作者： Mohamed, Ali Gaber Gamal, Mahmoud Alexandria University Department of Electrical Engineering Communications and Electronics Section Faculty of Engineering Alexandria Egypt Damanhour University Faculty of Engineering Department of Electrical Engineering Damanhour Egypt Higher Institute of Engineering and Technology Department of Computer Engineering El-Behira Egypt

ISBN: (数字)9781665475037

ISBN: (纸本)9781665475037

Cognitive radio can be considered as a viable frequency access framework that overcomes the disadvantages of the licensed-based transmission procedure by allowing the secondary users to access the spectrum to transmit their data. However, due to the evolution of latency-sensitive real-time communication applications such as gaming and extended reality, it becomes more vital that cognitive radio networks should be studied with latency requirements on the data transmission. Recently, Age of Information has introduced itself as a important metric for evaluating the freshness of the transmitted data. In this paper, we investigate the latency and stability analysis of a two-user cognitive radio network that consists of one primary user, one secondary user and their destinations. The latency requirements of the transmitted data packets are taken into consideration by imposing Age of Information constraints on the data transmission of the users. We present two optimization problems, in the first problem, the secondary user stable throughput is maximized under an Age of Information constraint imposed on the data transmission of the secondary user. While, in the second problem, we maximize the stable throughput of the secondary user with respect to Age of Information constraints set on the data transmission of both the primary and secondary users. The resultant problems are found to be non-linear programming optimization problems. An appropriate algorithm is used to solve the problems and provide the numerical solutions. Our results characterize the impact of setting Age of Information constraints on the stability region of the network;we demonstrate that the stability region, in certain cases, is reduced by only 11% with strict Age of Information restrictions if compared to the scenario where no latency requirements is considered. Our results also show the potential accuracy of the algorithm adopted in this paper to solve the formulated optimization problems. © 2022 IEEE.

关键词： Cognitive radio

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FPGA Implementation of Textural Feature Extractor and Distance Based Classifier for Multi Modal Biometric Pattern Recognition System Using Multi Resolution Approach 3

FPGA Implementation of Textural Feature Extractor and Distan...

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3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Hariprasath, S. Santhi, M. Prabakar, T.N. Koushick, V. Aravind, P. Gunasekaran, T. Saranathan College of Engineering Department of Ece Trichy India Sri Sairam College of Engineering Department of Ece Bangalore Anekal India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Mattu University Department of Electrical and Computer Engineering Ethiopia Electrical and Electronics Engineering Section University of Technology and Applied Sciences Muscat Oman

ISBN: (纸本)9798350322842

The design of biometric pattern recognition with better accuracy, high robustness and good permanence is a significant design issue in pattern recognition system. A pattern recognition system in which the biological and physiological traits of the user are employed to authenticate the users is known as biometric pattern recognition system. Unimodal biometric systems do not have the required characteristics like solidity, circumvention and permanence. When noisy data acquired from the sensor is given as input, the uni modal biometrics system's accuracy may reduce. Besides the noisy input, less variation of parameters of input data belonging to same class may be a cause for decrease in accuracy of the system. Several such limitations may be removed by applying input data from multi biometric sources. In this work, the design of a textural feature extractor and the classifier for a bimodal biometric system is described. The bimodal biometric system is constructed by fusion of iris code vector and palmprint code vector at feature level. In iris pattern, using the gray level dependent matrix values obtained from wavelet packet decomposed sub-images, the features are extracted Using gabor kernel, features are extracted from the palmprint pattern. The feature vector is formed by the concatenation of both the features after normalization is employed. By binarisation, the binary feature vector is created Using Hamming Distance and its variant, the classifier produces the classification result. The RTL description of the Hamming Distance Classifier (HDC) is written using VHDL 2008 language, Verilog HDL, and the implementation is performed on Spartan 6 FPGA. With a speed grade of 4, the propagation delay of the critical path is 330.12 ns. The obtained delay is sufficient for implementing the classifier as an off-chip design for real-time implementation. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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CONDITION ASSESSMENT OF 150 KV OUTDOOR COMPOSITE INSULATORS FOLLOWING A VEGETATION FIRE EVENT 23

CONDITION ASSESSMENT OF 150 KV OUTDOOR COMPOSITE INSULATORS ...

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23rd International Symposium on High Voltage engineering, ISH 2023

作者： Mavrikakis, Nikolaos C. Siderakis, Kiriakos Mouratis, Kiriakos Koudoumas, Emmanouel Section of Crete-Rhodes Transmission System Islands Network Operation Department Hellenic Electricity Distribution Network Operator S.A. Heraklion Greece High Voltage Laboratory Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Greece Center of Materials Technology and Photonics Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Greece

ISBN: (纸本)9781839539954

In electric power transmission and distribution systems, the use of overhead lines instead of underground cables is preferred by power utilities mainly due to the lower construction cost and the easier maintenance access. On the other hand the equipment used in overhead lines is stressed by several factors, such as weather conditions, lightning, vegetation fires, etc. In particular, vegetation fires under the overhead transmission lines could have catastrophic results for the installed equipment and can cause long-lasting electricity interruptions. In this study, condition assessment results are presented for eighteen 150 kV composite insulators exposed to a forest fire event, occurred in the August 2021, in the island of Rhodes, Greece. The evaluation of the fire effects on composite insulators was performed by employing several macroscopic and microscopic diagnostic techniques including visual inspection, hydrophobicity classification, Fourier Transform Infrared spectroscopy (FTIR) and optical microscopy analysis. © The Institution of engineering & technology 2023.

关键词： Construction equipment

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