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International Conference on Environment and electrical engineering (EEEIC)

作者： Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

Power system dynamics have significantly changed with the global integration of renewable energy sources (RESs). Traditionally, the stored kinetic energy is used for compensating the generation mismatch using the rotating mass of the Synchronous Generators (SGs). With the increase in RESs penetration, SGs are being replaced by inverter-based RESs generation systems which are decoupled from the power systems through power converters. Therefore, the total inertia of the system has decreased, and the system's stability is significantly impacted as the value of the rate of change of frequency (ROCOF) and frequency deviations will be increased. To overcome these challenges, inertia emulation from various energy storage systems (ESS) is used to act as a virtual source of inertia power. This work presents an isolated microgrid (MG) that includes conventional power generation sources and RESs, and an optimal virtual inertia (VI) control loop is proposed for frequency stability enhancement. Supercapacitors (SC) bank with a PID controller presents the VI control loop and acts as a supplementary source for inertia power to support the frequency stability of the system. A genetic algorithm (GA) is used as an optimization technique to get the optimal values of the PID controller gains. The performance of the islanded MG with the proposed optimal control scheme is examined under different operating conditions with varying levels of RESs penetration and system parameters uncertainties. The proposed technique showed its effectiveness and robustness over the system's operation without VI control for keeping the system stable under different operating conditions.

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Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays

Efficient Embedded Element Pattern Prediction via Machine Le...

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European Conference on Antennas and Propagation, EuCAP

作者： Nehir Berk Onat Ignacio Roldan Francesco Fioranelli Alexander Yarovoy Yanki Aslan Department of Microelectronics Faculty of Electrical Engineering Mathematics and Computer Science Microwave Sensing Signals and Systems Group Delft University of Technology Delft The Netherlands

Efficient prediction of embedded element patterns (EEPs) is including the mutual coupling (MC) effects in the optimization of irregular planar arrays is studied for the first time in the literature. An ANN-based methodology is used to predict the pattern of each element in the whole visible space for a flexible planar array topology in milliseconds. The technique is proposed is validated on a 4-element planar non-uniform sub-array structure. Excellent accuracy on the EEP prediction while providing great efficiency in computational time and load in comparison to the full-wave simulations is demonstrated.

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Rule-Based Power and Energy Management System For Shipboard Microgrid With HESS To Mitigate Propulsion and Pulsed Load Fluctuations

Rule-Based Power and Energy Management System For Shipboard ...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Mahmoud S. Abdelrahman Hossam Hussein Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Fl USA

A power and Energy Management System (P/EMS) is crucial to Microgrid's effective practical and reliable operation. In the Shipboard Microgrid (SMG), the load demand is dominated by the high penetration of propulsion loads, which is very dynamic. Some particular loads in naval ships draw very high power for very short periods. A hybrid application of battery and supercapacitor is proposed to cater to the energy consumed by pulse load in a naval ship and for backup purposes. The system proposed in this model is a stand-alone SMG with a Photovoltaic (PV) and Hybrid Energy Storage System (HESS). A rule-based energy supervision and power allocation technique have also been presented considering the specific fuel consumption of diesel engine generators and the characteristics of hybrid energy stored sources (battery and supercapacitor) of the entire SMG. The simulation studies using MATLAB/Simulink software indicate that the proposed P/EMS strategy enables management of power and energy contributions of hybrid resources on the ship. In addition, a reasonable allocation of power among HESS units, which can effectively smooth out the load power fluctuations of the proposed SMG has been introduced.

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Optimal Modulation and DM Filter Design for a High Switching Frequency Single-Stage Microinverter

Optimal Modulation and DM Filter Design for a High Switching...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Arafat Hasnain Michael D'Antonio Chanaka Singhabahu Yidi Shen Daniel Zakzewski Alireza Khaligh Department of Electrical and Computer Engineering Maryland Power Electronics Laboratory Institute for Systems Research University of Maryland USA

This paper presents an optimal modulation and systematic filter design approach for a single-stage dual-active-bridge (DAB) based dc-ac microinverter to achieve improved differential-mode (DM) noise performance for electromagnetic interference (EMI) tests. As DM filters contribute significantly to the overall converter volume, the main objective of this work is to leverage the degrees of freedom in the DAB converters to effectively attenuate the EMI noise. In addition, the DM filter design method needs to ensure near unity power factor converter operation. To achieve these targets, this paper analyzes three modulation strategies based on fixed or variable switching frequency operation where the different control modulation variables are varied to find the simulated DM noise spectrum. Based on the required DM attenuation, a constrained optimization problem is formulated to determine minimal DM filter parameters. Simulation results show that a spread spectrum approach with variable switching frequency is shown to minimize the DM EMI attenuation effort by spreading the noise profile. A fully GaN 400 W hardware prototype demonstrating the spread-sprectrum approach.

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ANN-TW Analysis Based Transmission Line Fault Identification and Location with High Penetration of Inverter-Based Resources

ANN-TW Analysis Based Transmission Line Fault Identification...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Mahmoud S. Abdelrahman Ibtissam Kharchouf Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Fl USA

A Power systems are undergoing a rapid change in generation mix due to the growth of Inverter-Based Resources (IBRs) such as wind and solar PV. This rapid growth creates new challenges for protection engineers. The output current of an IBR facility under short circuit conditions differs significantly from that of a conventional rotating synchronous source facility, posing protection problems. The protection schemes for the transmission line, which were designed locally at the planning stage, may operate reliably for low penetration of IBRs but in the case of high penetration, fault detection and location in the transmission line will be challenged. In this paper, a traveling wave-based protection schemes with the aid of Artificial Neural Network (ANN) as an innovative method to overcome these challenges and facilitate the widespread deployment of IBRs in transmission systems will be presented. A three-bus transmission network with voltage level of 380Kv and 94% of renewables penetration is simulated using DIgSILENT Power Factory is used in this study. The results demonstrates that fault identification is a quick and reliable way to identify a variety of faults, particularly single line to ground faults, which are the most challenging fault for the protection system.

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Transferable Learning of GCN Sampling Graph Data Clusters from Different Power systems

Transferable Learning of GCN Sampling Graph Data Clusters fr...

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Annual Allerton Conference on Communication, Control, and Computing

作者： Tong Wu Anna Scaglione Daniel Arnold Tianyi Chen The Department of Electrical and Computer Engi-neering University of Central Florida Orlando FL USA The Department of Electrical and Computer Engineering Cornell Tech Cornell University New York City NY USA Lawrence Berkeley National Laboratory The Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

ISBN: (数字)9798331541033

ISBN: (纸本)9798331541040

Contemporary neural network (NN) detectors for power systems face two primary challenges. First, each power system requires individual training of NN detectors to accommodate its unique configuration and base demands. Second, significant changes within the power system, such as the introduction of new substations or new generators, necessitate retraining. To overcome these issues, we introduce a novel architecture, the Nodal Graph Convolutional Neural Network (NGCN), which utilizes graph convolutions at each bus and its neighborhoods. This approach allows the training process to encompass multiple power systems and include all buses, thereby enhancing the transferability of the method across different power systems. The NGCN is particularly effective for detection tasks, such as cyber-attacks on smart inverters and false data injection attacks. Our tests demonstrate that the NGCN significantly improves performance over traditional NNs, boosting detection accuracy from approximately 85% to around 97% for the aforementioned task. Furthermore, the transferable NGCN, which is trained by samples from multiple power systems, performs considerably better in evaluations than the NGCN trained on a single power system.

关键词： Training Accuracy Substations Detectors computer architecture Inverters Power systems Cyberattack Faces Monitoring

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Real-Time Sensor Fault Tolerant Control of DC-DC Converters in DC Microgrids Using a Switching Unknown Input Observer

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IEEE Access 2025年 13卷 95837-95850页

作者： Ouahabi, Mohammed Said Benyounes, Abdelhafid Barkat, Said Ihammouchen, Syphax Rekioua, Toufik Rabehi, Abdelaziz El-Kenawy, El-Sayed M. Alharbi, Amal H. University of M’sila Electrical Engineering Laboratory Faculty of Technology M’sila28000 Algeria University of Bejaia Laboratoire de Technologie industrielle et de l’Information Bejaia06000 Algeria University of Djelfa Telecommunications and Smart Systems Laboratory PO Box 3117 Djelfa17000 Algeria PO Box 33349 Isa Town Bahrain Applied Science Private University Applied Science Research Center Amman Jordan Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Computer Sciences P.O. Box 84428 Riyadh11671 Saudi Arabia

DC Microgrids are rapidly developing, driven by the increasing integration of renewable sources and dynamic loads. Their growing adoption in critical applications raises the need for operational safety and reliability, particularly under fault conditions. This paper presents a sensor fault-tolerant control (FTC) for DC-DC power converters in DC Microgrids designed to maintain resilient and reliable operation. The proposed FTC leverages a single Switching Unknown Input Observer (SW-UIO) at the bottom control level to estimate arbitrary sensor faults with a high accuracy (0.3% fault estimation error), allowing a real-time identification and precise control reconfiguration to accommodate sensor faults with minimal computational burden. The approach is validated under diverse conditions, including time-varying loads, complete sensor failure, noise abnormality, and simultaneous faults/failure, achieving a consistent fault accommodation of 1μs from fault occurrence to compensation. Real-time simulation has been performed in the OPAL-RT environment to assess the efficacy and superiority of the proposed sensor fault tolerant strategy in comparison to reference FTC strategies. © 2013 IEEE.

关键词： Identification (control systems)

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Enhancing DC Microgrid Stability under Pulsed Load Conditions through Hybrid Energy Storage Control Strategy

Enhancing DC Microgrid Stability under Pulsed Load Condition...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ahmed Aghmadi Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

Despite the increasing prevalence of DC microgrids, they encounter instability issues due to imbalances in supply and demand, especially when dealing with specific loads such as pulse load or variable pulse load. The system faces severe changes which reduce the effectiveness of typical PV-Battery control systems. The solution to this problem frequently involves the use of energy storage devices such as supercapacitors SCs. When exposed to transients, batteries risk having their lifespans shortened and are challenged in keeping the stability of DC bus voltage and reducing overall transients. In order to increase the stability of DC microgrids and thereby increase their reliability and resilience, it is possible to combine the advantages of batteries and supercapacitors. Integrating both batteries and supercapacitors effectively enables DC microgrids to manage both steady-state and transient conditions. The main goal of this research paper is to investigate how the hybrid energy storage system (HESS) improves the stability of DC microgrids. According to sets of results, the proposed scheme has successfully reduced DC bus voltage variations regardless of variations in solar irradiance and the different pulsed load profiles.

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Low Complexity Single-Snapshot DoA Estimation via Bayesian Compressive Sensing

Low Complexity Single-Snapshot DoA Estimation via Bayesian C...

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IEEE National Conference on Radar

作者： Ignacio Roldan Lucas Lamberti Francesco Fioranelli Alexander Yarovoy Department of Microelectronics Microwave Sensing Signals and Systems Group Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands

The problem of single-snapshot direction of arrival (DoA) estimation with antenna arrays has been considered. A sectorized approach based on Bayesian Compressive Sensing (BCS) has been proposed. In this method, the angular space is discretized, defining many non-overlapping small grids which cover the desired large angular space. First, a BCS estimation is run in each of the sectors to estimate the DoA of the signals. Then, a second stage is performed to correct the inconsistencies at the edges due to signal leaking between sectors. The performance of the method has been analyzed via extensive Monte-Carlo simulations in which the number of targets, their Radar Cross Section (RCS), and their location have been varied in a large extent, and the targets were observed by a Frequency Modulated Continuous Wave (FMCW) radar with an 86-element Uniform Linear Array (ULA). The results are compared with state-of-the-art methods in terms of estimation accuracy and resolution. Moreover, an analysis of the computational time, critical for many real-time applications, is presented, which shows a reduction of 20 times in the computational time compared with the standard BCS. Finally, the method has also been validated using experimental data collected with a commercial automotive radar.

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Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexagonal Boron Nitride for Integrated Quantum Photonics

Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexa...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Roberts, Henry C. Waseem, Aadil Wicker, Scott A. Abudayyeh, Hamza Kim, Dong Seob Liu, Zhida Randolph, Steven Li, Xiaoqin Li, Xiuling Department of Electrical and Computer Engineering Microelectronics Research Center The University of Texas at Austin 10100 Harry Ransom Trail AustinTX78758 United States Department of Physics Center for Complex Quantum Systems Center for Dynamics Control of Materials Texas Materials Institute The University of Texas at Austin 2515 Speedway AustinTX78712 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

We report a new approach to generate waveguide-coupled emission from deterministically implanted boron vacancy spin defects in hBN using single-crystal AlN-on-sapphire ring resonators. This facilitates the eventual de... 详细信息

关键词： Single crystals

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