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Hardware simulator for frequency-watt control in smart inverters

Transactions of the Korean Institute of Electrical Engineers 2021年第7期70卷 999-1007页

作者： Lee, Sun-Hang Cho, Sungjoon Lee, Kyo-Beum Dept. of Electrical and Computer Engineering Ajou University Korea Republic of

This paper presents a hardware simulator for a Frequency-Watt control in smart inverters. The power plant generator rotates at a constant speed, which is related to the frequency of the grid. The frequency of the grid is determined by the balance of power generation and power consumption. In addition, frequency fluctuations occur due to sudden changes in load or accidents. To reduce fluctuations and improve stability of grid system, the Frequency-Watt control in smart inverters was introduced. The PLL (Phase Locked Loop) control in various situations is important for grid-connected inverter to detect grid frequency. The real power limit of the smart inverter is controlled by the detected frequency to support grid stabilization. In this paper, the development of a hardware simulator for the Frequency-Watt control in smart inverters using three-level topology is introduced. The validity and performance of the proposed hardware simulator and its control strategies are demonstrated by various experimental results. Copyright © The Korean Institute of Electrical Engineers This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://***/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

关键词： Phase locked loops

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Moth flame optimization algorithm for efficient feature selection and hybrid classification technique for intrusion detection system

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Multimedia Tools and Applications 2025年 1-21页

作者： Keerthanarani, U. Selvakumar, V. Singaravelan, S. Raja, S. Edwin Thenmozhi, K. Shunmugam, D. Arun Dept. of Computer Science and Engineering P.S.R Engineering College Sivakasi India Dept.Of Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R & d Institute of Science and Technology Chennai Avadi India Dept. Of Computer Science and Engineering Coimbatore Institute of Engineering and Technology Coimbatore India Dept. Of Electronics and Communication Engineering P.S.R Engineering College Sivakasi India

The rapid expansion of the Internet of Things (IoT) brings numerous benefits but further presents fresh difficulties, especially in terms of security. The distributed and interconnected nature of IoT devices makes them susceptible to various security threats. An Intrusion Detection System (IDS) plays a crucial role in safeguarding IoT networks by monitoring, detecting, and responding to potential security incidents. The Internet of Things (IoT) connects billions of devices, sensors, and systems, transforming industries and everyday life. However, this extensive interconnectivity also introduces significant security risks, making Intrusion Detection systems (IDS) a critical component for safeguarding IoT environments. Feature selection is a crucial aspect of building effective Intrusion Detection systems (IDS). Selecting relevant features not only helps in achieving better classification accuracy but also contributes to reducing false alarm rates. In the proposed system a moth flame optimizer is utilized to select the efficient features from the dataset, overall accuracy of over 97%. Further it is classified employing Random Forest and J48 classifier which attains high classification accuracy and low false alarm rate. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Feature Selection

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A Method for Localization of Cellular Users from Call Detail Records

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IEEE Access 2025年 13卷 92203-92212页

作者： Ellingson, Steven W. Virginia Tech Dept. of Electrical & Computer Engineering BlacksburgVA24061 United States

A common problem in justice applications is localization of a user of a cellular network using a call detail record (CDR), which typically reveals only the base station and sector to which the user was connected. This precludes precise estimation of location. Instead, one is limited to estimating a region of plausible locations (RPL) using static information such as sector antenna orientation, beamwidth, and locations of nearby base stations. In this paper, we propose a method for RPL estimation in which the shape bounding the RPL is derived from a model of the antenna pattern via the Friis Transmission Equation, and the size of the RPL is determined by mean distance to nearby base stations. The performance of the proposed method is evaluated by "best server" analysis of measurements acquired from drive testing in the vicinity of Winter Garden, Florida, observing three 700 MHz-band LTE cellular networks serving this area. Of the 16 sectors evaluated, the aggregate error rate (i.e., fraction of users located outside the RPL estimated for the associated sector) is found to be 1.3%, with worst per-sector error rate of about 13.3% and error rates below 1.8% for 13 of the 16 sectors. The principal difficulty is shown to be estimation of RPL size, which entails a tradeoff between minimizing RPL area (yielding the "tightest" localization) and minimizing error rate. © 2013 IEEE.

关键词： Smartphones

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Interpretable Machine Learning Model for Breast Cancer Prediction Using LIME and SHAP 9

Interpretable Machine Learning Model for Breast Cancer Predi...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Maheswari, B Uma Aaditi, A. Avvaru, Ananya Tandon, Aryan De Prado, R. Pérez Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science And Engineering Bengaluru India University of Jaén Dept. Telecommunication Engineering Jaén23700 Spain

ISBN: (纸本)9798350394474

Breast cancer, which occurs in both men and women, causes approximately 10 lakh deaths globally and has no specific risk factors. The time frame of the treatment is a long-drawn process based on the person, the type of cancer, and its level of spread. It is imperative to detect this cancer early on in order to prevent mortality. Given the prediction's significance, an accurate breast cancer prediction model must be developed. This study explores the Breast Cancer Prediction dataset, applies SMOTE (Synthetic Minority Over-sampling Technique) to balance the dataset, and proposes an effective Machine Learning (ML) model fused with Explainable AI to provide health professionals with explanations. ML algorithms are analyzed before and after applying Principal Component Analysis (PCA), and visualization is performed using t-SNE. ML algorithms, Support Vector Machine (SVM), k-Nearest Neighbor (kNN), Random Forest (RF), Stochastic gradient Descent, XGBoost, Gradient Boosting, Decision Tree (DT), and Naïve Bayes are trained on the Breast Cancer dataset. It is seen that the RF model outperforms other models considered with 95.9% accuracy. To understand the weightage of features considered by the best breast cancer prediction models and to provide trust to the doctors, the Explainable AI (XAI) packages LIME (Local Interpretable Model-agnostic Explanations), and SHAP (SHapley Additive exPlanations) are used. The effective ML model with XAI techniques empowers clinicians with actionable insights for more informed breast cancer diagnosis and treatment decision-making. © 2024 IEEE.

关键词： Principal component analysis

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Power Quality Control and Comparison of a Micro Grid System Using Fuzzy MPPT Technique 5

Power Quality Control and Comparison of a Micro Grid System ...

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5th International Conference on Energy, Power, and Environment, ICEPE 2023

作者： Sahoo, Satyabrata Thokchom, Surmila Puhan, Pratap Sekhar Panda, Gayadhar NallaMallaReaddy Engineering College Dept. of Electrical and Electronics Engineering Hyderabad India National Institute of Technology Meghalaya Dept. of Computer Science and Engineering Meghalaya India Sreenidhi Institute of Science and Technology Dept. of Electrical and Electronics Engineering Hyderabad India National Institute of Technology Meghalaya Dept. of Electrical Engineering Meghalaya India

ISBN: (纸本)9798350313123

This paper presents a power quality control in a microgrid system using different Maximum Power Point Tracking (MPPT) techniques. The main aim of the study is to evaluate the performance of the microgrid system in terms of power quality parameters, such as harmonic distortion and voltage stability, when different MPPT techniques are employed. The microgrid system incorporates a hybrid power generation system consisting of solar panels, wind turbines, and energy storage systems, which are integrated and controlled using different MPPT techniques, including the Perturb & Observation (P&O) method and the Fuzzy MPPT technique. A single-phase sinusoidal pulse width modulation (SPWM) inverter, based on the PQ control strategy, is used to supply power to the grid and maintain a constant DC link voltage. Additionally, a fuel cell is employed to substantially reduce power fluctuations. A comparison of the power quality performance of the micro grid system using these MPPT techniques is carried out through simulation studies using MATLAB/Simulink platform. The results are analyzed and discussed in detail, and recommendations are provided for improving the power quality control of the microgrid system. © 2023 IEEE.

关键词： Wind turbines

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SEPHWIR: Search Engine Parsing for Hidden Web Information Retrieval 1

SEPHWIR: Search Engine Parsing for Hidden Web Information Re...

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1st International Conference on Smart and Sustainable Technologies in Energy and Power Sectors, SSTEPS 2022

作者： Sehgal, Manpreet Singh Gupta, Sachin Sehgal, Twinkle Apeejay Stya University School of Engineering and Technology Gurugram India MVN University Dept. of Computer Science and Engineering Palwal India Matrikiran Dept. of Computer Science Gurugram India

ISBN: (纸本)9781665464147

The world wide web consists of web pages and databases from which web pages can be generated on demand. It is presumed that the information stored in the databases is of better quality than the one published onto already created static webpages. The web search engine architectures are tuned to access static webpages and index and rank them in their results against the query. This results into the accessibility to the kind of information that is not of better quality. This paper talks about the approach to parse such results of the search engines and find the entry points to the databases to fetch the better-quality information. © 2022 IEEE.

关键词： Search engines

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State-Space Average Modeling Based PID Control for Three Novel Topologies of DC-DC Boost Converter

State-Space Average Modeling Based PID Control for Three Nov...

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2022 IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2022

作者： Zaman, Meem Tasfia Fu, Xingang Challoo, Rajab North South Univeristy Dept. of Electrical and Computer Engineering Dhaka Bangladesh Texas A&m University-Kingsville Dept. of Electrical Engineering and Computer Science Kingsville United States

ISBN: (纸本)9798350311563

The objectives of this paper are to obtain state-space average models of the three new topologies of the DC-DC boost converter and apply Proportional Integral Derivative (PID) controller on them to analyze their performance. One of the most important applications of DC-DC boost converter in modern world is in Photovoltaic (PV) systems. It boosts up the low DC voltage coming from the PV panels to a high DC bus voltage and it drives the DC-AC inverter. Thus, the efficiency and the control of it play very important role in this entire process. Recently, some new topologies have been proposed to improve the efficiency of this converter. In order to inspect these topologies, proper mathematical modeling is required, and the state-space average model is one of the efficient techniques to do that. Among various control techniques, PID controller is widely used to get the best-desired output voltage of this converter. To get the expected result, MATLAB Simulink models and MATLAB m-file code will be used in this paper. © 2022 IEEE.

关键词： Three term control systems

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Fingerprint generation and authentication though Adaptive convolution generative adversarial network (ADCGAN) 7

Fingerprint generation and authentication though Adaptive co...

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7th International Multi-Topic ICT Conference: IMTIC 2023

作者： Mustafa, Syed Muhammad Nabeel Zehra, Syeda Sundus Baber, Alina Siddiqui, Maria Andleeb Ned University of Engineering and Technology Dept. of Computer Science & Information Technology Karachi Pakistan Sir Syed University of Engineering and Technology Dept of Software Engineering Karachi Pakistan

ISBN: (纸本)9798350338461

Fingerprints are crucial in identification of humans. The uniqueness of finger prints makes it an interesting subject. Fingerprints are termed as a technique used to define, assess, and quantify a person's physical and behavioral property. Deep learning has made its application in all the major fields such as natural language processing, computer vision and speech processing. Deep learning has also found its application in the important subject of fingerprint synthesis and biometric. The ever-growing complexity of fingerprint authentication issues, from cellphone authentication to airport security systems, seems to be best handled by these models. In recent years, deep learning-based models have been used more and more to raise the accuracy of various fingerprint recognition systems. The persuasive capacity of Generative Adversarial Networks (GANs) to generate believable instances can be credibly taken from an existing distribution of samples. GAN exhibits exceptional performance on data generation-based tasks and also encourages study in privacy and security. In this work, using Adaptive Deep Convolution Generative Adversarial Networks (ADCGAN), we develop a model that generates and authenticate the fingerprints. A Socofing dataset was trained on ADGAN model. The model gave 92% accuracy. The conduct of fingerprint research has been made possible due to ADGAN, without restrictions related to the confidential nature of biometric data. © 2023 IEEE.

关键词： Generative adversarial networks

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127 Level Reduced Switch Asymmetric Cascaded H-Bridge Multilevel Inverter

127 Level Reduced Switch Asymmetric Cascaded H-Bridge Multil...

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2023 IEEE International Conference on Emerging Trends in engineering, Sciences and Technology, ICES and T 2023

作者： Zulfiqar, Ismaiel Syed, Shahzada Sufyan Syed, S. Subhan Malik, Yousaf Jadoon, Wasid Ali COMSATS University Islamabad Dept. of Electrical and Computer Engineering Abbottabad Campus Abbottabad Pakistan Allied Engineering and Services Limited Regional Manager dept. of Alternative Energy Solutions Lahore Pakistan

ISBN: (纸本)9781665455602

Depending upon the uses of multilevel inverter in different applications such as Uninterruptible power supply (UPS), high voltage DC transmission (HVDC) and Variable frequency drives (VFD), there is huge research which is carried on them. This paper describes the working of 127 level Reduce Switch Asymmetrical Cascaded H Bridge multilevel inverter (RS-ACHBMLI), the main objective is to produce a pure sinusoidal waveform without the use of any filter element and to reduce total harmonic distortion (THD) up to 0.80Asymmetric topology is used in which DC sources are of different magnitudesfuels cells are the best to use as a DC source in our proposed technique. Sine wave is compared with 63DCoffsets to trigger the Insulated gate bipolar junction transistors (IGBTs) in a specific manner, six dc sources and six IGBT's are used to produce required output waveform. Low frequency PWM technique is used in level generating circuitry to produce required output. © 2023 IEEE.

关键词： Pulse width modulation

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Dental Imaging Using a Higher Signal-to-Noise Ratio Optical Coherence Tomography System

Dental Imaging Using a Higher Signal-to-Noise Ratio Optical ...

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2023 IEEE International Conference on Electrical, computer and Energy Technologies, ICECET 2023

作者： Azeez, Akeem. A. Mezgebo, Biniyam Franca, Rodrigo Sherif, Sherif S. University of Manitoba Biomedical Engineering Graduate Program Winnipeg Canada University of Manitoba Dept. of Electrical and Computer Engineering Winnipeg Canada University of Manitoba Dept. of Restorative Dentistry Winnipeg Canada

ISBN: (纸本)9798350327816

This paper presents an optical coherence tomography (OCT) system in conjunction with a novel image reconstruction technique employed for in vitro imaging of human teeth. The primary goal is to enhance the signal-to-noise ratio (SNR) in the obtained images. The study entails a comparative analysis between the conventional Fast Fourier Transform (FFT) OCT image reconstruction method and a newly introduced scaled nonuniform discrete Fourier transform (NDFT) approach. The findings reveal that the NDFT method consistently delivers superior results in terms of peak signal-to-noise ratio (PSNR) and overall image quality, even when dealing with redundant and nonuniform frequency domain samples. In light of these results, this paper concludes that integrating NDFT into OCT procedures has the potential to significantly enhance the quality of image reconstructions, thereby fostering its broader application in the field of dental imaging. © 2023 IEEE.

关键词： dental imaging frame theory image reconstruction Optical Coherence Tomography (OCT) signal processing

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