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2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Aghmadi, Ahmed Hussein, Hossam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350347432

This paper introduces a highly efficient energy management system for a microgrid that combines PV system, wind turbine, and battery. The study presents an effective energy management system specifically designed for a small-scale hybrid microgrid, focusing on the development of solar and wind energy conversion systems and battery storage systems. Power electronic converters and control algorithms are implemented to evaluate the microgrid's operation. The energy management system plays a crucial role in maintaining power balance amidst varying renewable energy generation and load demand conditions. The microgrid is a testing platform to evaluate control algorithms, energy management systems, and various test scenarios. It provides a controlled environment for assessing the performance and efficiency of these systems. The efficient energy management system comprises photovoltaic (PV) modules, wind turbines, and batteries. The proposed strategy effectively manages the switching between the PV panel and the battery storage system while prioritizing power generation from the wind turbine. The efficacy and success of this strategy in microgrid control under various operational circumstances are demonstrated through MATLAB simulation results. © 2023 IEEE.

关键词： Wind power

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Techniques for Mitigating the Impact of Intra-CPI Waveform Agility

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar systems 2024年 2卷 24-40页

作者： Mattingly, Rylee G. Martone, Anthony F. Metcalf, Justin G. The University of Oklahoma Advanced Radar Research Center School of Electrical and Computer Engineering NormanOK73019 United States Devcom Army Research Laboratory AdelphiMD20783 United States

As the electromagnetic spectrum has become more congested, there has been increased interest in spectrum sensing and sharing techniques that enable frequency agility on a pulse-to-pulse basis within a single coherent processing interval (CPI). Although intra-CPI pulse agility allows for more efficient spectrum use, it creates unique processing challenges. Changing the bandwidth and intermediate frequency (IF) of pulses within a CPI reduces the performance of traditional range-Doppler processing techniques. This paper investigates the impact that bandwidth and IF frequency agility has on the slow time phase history and range sidelobes. To mitigate the effects of frequency hopping, a modified backprojection technique is proposed. Second, mismatched filtering techniques are examined to mitigate the range-sidelobe modulation (RSM) caused by the changing bandwidths. This work will investigate these two issues individually and repair each in turn before combining the process to compensate fully adaptive CPIs. Simulated data will be used to validate the performance of each technique using linear frequency modulated (LFM) waveforms. The mitigation techniques are further verified using real-world data from an agile pulse-Doppler radar experiment. © 2023 IEEE.

关键词： Bandpass filters

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Relative Permittivity of Natural Ester Oil-Based Nanofluids with Iron Oxide Nanoparticles 58

Relative Permittivity of Natural Ester Oil-Based Nanofluids ...

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58th International Universities Power engineering Conference, UPEC 2023

作者： Tsovilis, Thomas E. Staikos, Evangelos T. Hadjicostas, Alexandros Y. Datsios, Zacharias G. Litsardakis, George Pyrgioti, Eleftheria C. Bakandritsos, Aristeidis Peppas, George D. School of Electrical & Computer Engineering Aristotle University of Thessaloniki High Voltage Laboratory Greece School of Electrical & Computer Engineering Aristotle University of Thessaloniki Laboratory of Materials for Electrotechnics Greece University of Patras High Voltage Laboratory Electrical & Computer Engineering Department Greece Palacký University Olomouc Czech Republic Raycap Sa Industrial Area of Drama Research & Development Department Drama66100 Greece

ISBN: (纸本)9798350316834

The real part of the relative permittivity and the electrical conductivity of a natural ester oil, that serves as a liquid matrix for nanofluids, are measured for a wide frequency and electric field range. The focus of this work is the exploration of the modification of these basic electrical parameters of the liquid matrix after the integration of iron oxide nanoparticles. A series of experiments with the aid of an impedance analyzer, an LCR meter, and a variable-frequency power supply employing two different liquid test fixtures reveal an increase of both real and imaginary parts of relative permittivity with increasing nanoparticles concentration up to 0.5% w/w. © 2023 IEEE.

关键词： Iron oxides

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Dynamic Pulsed Load Mitigation in PV-Battery-Supercapacitor systems: A Hybrid PI-NN Controller Approach

Dynamic Pulsed Load Mitigation in PV-Battery-Supercapacitor ...

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2023 IEEE Design Methodologies Conference, DMC 2023

作者： Aghmadi, Ahmed Ali, Ola Hussein, Hossam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350315547

DC microgrids are becoming more and more popular, however there are still difficulties involving ongoing instability that are mostly caused by imbalances in energy supply and demand, particularly in situations with pulse load or variable pulse load patterns. Innovative solutions are required since these disruptive load dynamics significantly decrease the effectiveness of conventional PV-Battery control systems. conventional Proportional-Integral (PI) controllers, although widely employed, may encounter limitations when confronted with the unique challenges posed by specific load patterns, notably pulse load scenarios. These dynamic load profiles, characterized by rapid and unpredictable changes. The inherent non-linearity and variability in such load conditions can result in suboptimal control performance, potentially leading to voltage instability and transients within the microgrid. To overcome these issues and improve control performance, the introduction of Neural Network (NN) controllers promises to be a potential approach. NN controllers have a remarkable capacity to learn and adapt from data, making them particularly well-suited for situations characterized by non-linear and dynamic load behavior. In this study, a hybrid PI-NN (Proportional-Integral Neural Network) controller is introduced to reduce load effects, especially pulsed loads, in PV systems with batteries and supercapacitors. This method efficiently optimizes energy storage. For voltage control, it utilizes a PI system, which divides the reference current into low and high-frequency components for battery and supercapacitor control. For enhanced sensitivity and dynamic responsiveness, neural network control replaces conventional PIs. The performance of the hybrid PI-NN controller is evaluated in this work, with an emphasis on its potential to improve PV system efficiency in severe load circumstances. © 2023 IEEE.

关键词： Supercapacitor

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Enhancing Solar Radiation Forecasting with Hybrid Ensemble Empirical Mode Decomposition and Machine Learning Techniques

Enhancing Solar Radiation Forecasting with Hybrid Ensemble E...

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2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Aghmadi, Ahmed Mohammed, Osama Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350347432

The importance of short-term solar radiation forecasting for power system use and management cannot be overstated. However, Non-stationarity and unpredictability make accurate forecasting difficult. Time series approaches are suitable for forecasting stationary time series derived from a non-stationary sequence. Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) are time-domain decomposition methods used to separate the components of the original solar radiation time series that have distinct time1-scale characteristics. As a result, the components are forecasted using the Back Propagation Neural Network (BPNN) model, which is a simple and effective machine learning method. This paper presents a hybrid EMD/EEMD-BPNN model for predicting short-term solar irradiance. To identify unique data information at different time scales, EMD/EEMD first breaks up the solar radiation time series into several stationary or fundamental sub-series. The next step is to create BPNN models with specified parameters for each subsequence to forecast new ones. Finally, each subsequence's projected value is combined to generate the final forecast result. The accuracy of solar forecasts has greatly increased, especially when utilizing hybrid methods. Furthermore, using the proposed hybrid technique for multistep forecasting resulted in even more improvement. The basic BPNN model for 15 min time step achieves predicting with a root mean square error (RMSE) of roughly 416.04 W/m2 for 15min;however, this error decreases to 65.25 W/m2 with the EMD-Hybrid Model, and 32.86 W/m2 with the EEMD-Hybrid Model. In addition, the results of the skill score have proven clearly that EMD/EEMD-BPNN Model performs better compared to typical BPNN using several meteorological inputs © 2023 IEEE.

关键词： Empirical mode decomposition

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An Introduction to Power Electronics Design Methodology

An Introduction to Power Electronics Design Methodology

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2023 IEEE Design Methodologies Conference, DMC 2023

作者： Rafin, Sm Sajjad Hossain Hussein, Hossam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Dept. of Electrical and Computer Engineering MiamiFL United States

ISBN: (纸本)9798350315547

The development of effective and dependable electronic systems for a variety of applications, from renewable energy systems and electric vehicles to industrial automation and consumer electronics, depends heavily on power electronics design techniques. Moreover, the power electronics design technique offers a methodical way to create high-performance, dependable, and efficient electronic systems, which helps scholars and engineers address the unique requirements of varied applications while taking thermal management, electromagnetic interference, and safety considerations by integrating theoretical analysis, simulation tools, prototyping, and testing. The effectiveness of this methodology is further increased by the ongoing development of power semiconductor and design methodologies, which makes it possible to realize cutting-edge and environmentally friendly power electronic solutions for the modern world. Considering above mentioned importance, this paper is written as an initial guideline for scholars and engineers to design power electronic systems. © 2023 IEEE.

关键词： Design

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Dynamic Modeling of Double Segment Redundant Gough-Stewart Hybrid Manipulator based on the Principle of Virtual Work 12

Dynamic Modeling of Double Segment Redundant Gough-Stewart H...

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12th RSI International Conference on Robotics and Mechatronics, ICRoM 2024

作者： Ardakani, Alireza Kamali Akbari, Hossein Namazian, Parsa Masouleh, Mehdi Tale Bahrami, Arash University of Tehran Human and Robot Interaction Laboratory School of Mechanical Engineering Tehran Iran University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran School of Mechanical Engineering University of Tehran Tehran Iran

ISBN: (纸本)9798331529734

This paper presents the dynamic modeling and analysis of a hyper-redundant manipulator with two Gough-Stewart platforms. Initially, the kinematic model of the manipulator is reviewed and used, since it acts as a base component for the subsequent dynamic modeling. Then, the virtual work approach is introduced to establish a foundation for the dynamic modeling of a single Gough-Stewart platform. This modeling for a single segment is used to form the equation of motion for both segments. However, the external forces applied to the lower Gough-Stewart robot are different from the upper one, since the force and masses in the upper platform act on the lower one. By considering these effects on the lower platform, the dynamic equations for the whole have been formed and presented. The accuracy of the proposed model is validated through a detailed comparison with simulations performed using a Simscape environment. Notable challenges in aligning the results between the model and simulations are discussed, highlighting the complexities involved in ensuring consistency across different platforms. The comparisons show an average error of 1.537 percent per actuator. © 2024 IEEE.

关键词： Digital elevation model

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Stochastic Characterization-Based Performance Analysis of an Emulated Communication Network for Cyber-Physical Shipboard Power systems

Stochastic Characterization-Based Performance Analysis of an...

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2023 IEEE Electric Ship Technologies Symposium, ESTS 2023

作者： Abdelrahman, Mahmoud S. Nguyen, Tung-Lam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9781665465151

Emerging advanced and innovative Information and Communication Technologies (ICT), automation strategies, and associated algorithms in the traditional power system have transformed it into a Cyber-Physical Power System (CPPS). Energy management and control are crucial in the Shipboard Power System operation. For instance, to meet the ship's energy and other ancillary demands, especially the mission-critical loads that require practical and secure network communication. Therefore, a comprehensive modeling and testing and validation approach was developed in this paper. This enables flexible system-level aspect evaluation through numerous experiments, including virtual, real, and mixed lab settings. This paper presents a scalable and flexible three-layer cyber-physical co-simulation platform implemented in the FIU smart grid testbed. This includes real-time power system simulation using OPAL-RT, ns3 for communication network emulation, and MATLAB/SIMULINK for implementing various applications. To demonstrate the platform's effective operation, energy management with a central controller for SPS was configured and implemented to test the communication network performance by creating tools to characterize the network latency for this application. © 2023 IEEE.

关键词： Ships

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An IDM-Based Two-Stage Robust Balance Analysis Model for High-proportion Renewable Energy Integration through HVDC System 8

An IDM-Based Two-Stage Robust Balance Analysis Model for Hig...

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8th International Conference on Power and Renewable Energy, ICPRE 2023

作者： Qi, Jie Guo, Jincheng Zhang, Yaodan Xi'An Jiaotong University School of Electrical Engineering Xi'an China Case Western Reserve University Department of Electrical Computer and Systems Engineering Cleveland United States

ISBN: (纸本)9798350328813

Under the circumstance of the new-type power system, uncertainties on both sides of supply and demand lead to prominent characteristics of supply-demand probabilistic matching and multi-regional complementarity, which greatly increased the balance risk during system operation. In this regard, this paper proposes a short-term electric power balance analysis model for a renewable energy power base transmitted through a high-voltage direct current (HVDC) system. First, a detailed cascade hydropower system (CHS) and HVDC model are constructed , and different linearization techniques are applied to linearize different nonlinear constraints, reducing computational complexity. Second, to effectively capture the uncertainty of renewable energy, an Imprecise Dirichlet model (IDM) based method for constructing uncertainty sets is designed, greatly reducing the conservation of the robust optimization. Finally, a two-stage robust optimization model with mixed-integer recourse is established to analyze the potentially unbalanced state by minimizing the operational and curtailment costs. The proposed two-stage robust optimization model is a solved column-and-constraint generation (C&CG) algorithm by using customized nested. The result of the numerical verifies the effectiveness of the proposed model and algorithm. © 2023 IEEE.

关键词： Cascade hydropower Customized nested C&CG HVDC Imprecise Dirichlet model Two-stage robust optimization

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Synthetic Speech Attribution Using Self Supervised Audio Spectrogram Transformer

Synthetic Speech Attribution Using Self Supervised Audio Spe...

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IS and T International Symposium on Electronic Imaging: Media Watermarking, Security, and Forensics, MWSF 2023

作者： Yadav, Amit Kumar Singh Bartusiak, Emily R. Bhagtani, Kratika Delp, Edward J. Video & Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West LafayetteIN United States

The ability to synthesize convincing human speech has become easier due to the availability of speech generation tools. This necessitates the development of forensics methods that can authenticate and attribute speech signals. In this paper, we examine a speech attribution task, which identifies the origin of a speech signal. Our proposed method known as Synthetic Speech Attribution Transformer (SSAT) converts speech signals into mel spectrograms and uses a self-supervised pretrained transformer for attribution. This transformer is pretrained on two large publicly available audio datasets: Audio Set and LibriSpeech. We finetune the pretrained transformer on three speech attribution datasets: the DARPA SemaFor Audio Attribution dataset, the ASVspoof2019 dataset, and the 2022 IEEE SP Cup dataset. SSAT achieves high closed-set accuracy on all datasets (99.8% on ASVspoof2019 dataset, 96.3% on SP Cup dataset, and 93.4% on DARPA SemaFor Audio Attribution dataset). We also investigate the method's ability to generalize to unknown speech generation methods (open-set scenario). SSAT has high performance, achieving an open-set accuracy of 90.2% on the ASVspoof2019 dataset and 88.45% on DARPA SemaFor Audio Attribution dataset. Finally, we show that our approach is robust to typical compression rates used by YouTube for speech signals. © 2023, Society for Imaging Science and Technology.

关键词： Large dataset

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