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Virtual Synchronous Generator-Based Positive Negative Sequence Control Scheme for Voltage Unbalance Mitigation in Low Inertia Islanded Microgrid 1

Virtual Synchronous Generator-Based Positive Negative Sequen...

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1st International Conference on Innovative Sustainable Technologies for Energy, Mechatronics and Smart Systems, ISTEMS 2024

作者： Sinha, Suruchi Ali, Nada Kumar, Deepak Anwar, Shamama Birla Institue of Technology Mesra Electrical and Electronics Engineering Ranchi India Birla Institute of Technology Mesra Computer Science and Engineering Ranchi India

ISBN: (纸本)9798350384246

The depletion of traditional energy sources, particularly fossil fuels, and increasing energy demands have prompted a combination of renewable energy sources (RES), Distributed Generation (DG) units, and the extensive uptake of micro grids are shaping the energy landscape. A micro grid operates either independently or in conjunction with the main power grid. In islanded mode, micro sources manage to supply power to loads while maintaining voltage and frequency within acceptable limits. However, islanded microgrids often face challenges related to poor power quality, with voltage unbalance being an important concern. Also, renewable energy systems lack inertia as they do not have any rotating parts. Therefore, this paper addresses the issue by proposing a positive-sequence (PS) in parallel with the negative sequence (NS) controller for a Voltage-Source Converter (VSC)-based DG unit for voltage unbalance reduction in microgrids. Additionally, to intensify the stability of the system, this paper also introduces a Virtual Synchronous Generator (VSG) control framework, utilizing inverter-interfaced distributed energy resources to impart virtual inertia to the system. The proposed controller's design concept is validated via simulation in Simulink/MATLAB, with the results confirming the efficacy of the controller as demonstrated. © 2024 IEEE.

关键词： Synchronous generators

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FDTD in Computational Electromagnetics and Quantum Transport

FDTD in Computational Electromagnetics and Quantum Transport

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2025 United States National Committee of URSI National Radio science Meeting, USNC-URSI NRSM 2025

作者： Ren, Kai Department of Electrical Engineering and Computer Science South Dakota School of Mines and Technology Rapid CitySD United States

ISBN: (纸本)9781946815200

The finite-difference time-domain (FDTD) method used in computational electromagnetics (CEM) and quantum transport are investigated. In CEM, FDTD is applied to coupled electric and magnetic fields based on the Maxwell's equations. In quantum transport, FDTD is implemented to coupled real and imaginary components of the electron wavefunction based on the time dependent Schrӧdinger equation. To have a better understanding of CEM and quantum transport, FDTD formulations and simulations of plane wave propagation in free space and electron scattering in metal-oxide-semiconductor field-effect transistors (MOSFETs) are presented. A comprehensive observation of electromagnetic and quantum techniques can be obtained through discretization of the time-dependent Maxwell's equations and Schrӧdinger equation. © 2025 USNC-URSI.

关键词： Maxwell equations

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Fusion of color and hallucinated depth features for enhanced multimodal deep learning-based damage segmentation

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Earthquake engineering and engineering Vibration 2023年第1期22卷 55-68页

作者： Tarutal Ghosh Mondal Mohammad Reza Jahanshahi Civil Architectural and Environmental EngineeringMissouri University of Science and TechnologyRollaMOUSA Lyles School of Civil Engineering Purdue UniversityWest LafayetteINUSA School of Electrical and Computer Engineering Purdue UniversityWest LafayetteINUSA

Recent advances in computer vision and deep learning have shown that the fusion of depth information can significantly enhance the performance of RGB-based damage detection and segmentation ***,alongside the advantages,depth-sensing also presents many practical *** instance,the depth sensors impose an additional payload burden on the robotic inspection platforms limiting the operation time and increasing the inspection ***,some lidar-based depth sensors have poor outdoor performance due to sunlight contamination during the *** this context,this study investigates the feasibility of abolishing depth-sensing at test time without compromising the segmentation *** autonomous damage segmentation framework is developed,based on recent advancements in vision-based multi-modal sensing such as modality hallucination(MH)and monocular depth estimation(MDE),which require depth data only during the model *** the time of deployment,depth data becomes expendable as it can be simulated from the corresponding RGB *** makes it possible to reap the benefits of depth fusion without any depth perception per *** study explored two different depth encoding techniques and three different fusion strategies in addition to a baseline RGB-based *** proposed approach is validated on computer-generated RGB-D data of reinforced concrete buildings subjected to seismic *** was observed that the surrogate techniques can increase the segmentation IoU by up to 20.1%with a negligible increase in the computation ***,this study is believed to make a positive contribution to enhancing the resilience of critical civil infrastructure.

关键词： multimodal data fusion depth sensing vision-based inspection UAV-assisted inspection damage segmentation post-disaster reconnaissance modality hallucination monocular depth estimation

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Gaussian PI Controller Network Classifier for Grid-Connected Renewable Energy System

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Intelligent Automation & Soft Computing 2023年第1期35卷 983-995页

作者： Ravi Samikannu K.Vinoth Narasimha Rao Dasari Senthil Kumar Subburaj Department of Electrical Computer and Telecommunications Engineering Botswana International University of Science and TechnologyBotswana Department of Electrical and Electronics Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennaiTamil NaduIndia Department of Electrical Power Engineering College of EngineeringDefence UniversityEthiopia Department Electrical and Electronics Engineering New Prince Shri Bhavani College of Engineering and TechnologySembakkamTamil NaduIndia

Multi-port converters are considered as exceeding earlier period decade owing to function in a combination of different energy sources in a single processing *** energy sources are playing a significant role in the modern energy system with rapid *** renewable sources like fuel combustion and solar energy,the generated voltages change due to their environmental *** develop energy resources,electric power generation involved huge *** power and output voltages are plays important role in our work but it not considered in the existing *** considering the power and voltage,Gaussian PI Controller-Maxpooling Deep Convolutional Neural Network Classifier(GPIC-MDCNNC)Model is introduced for the grid-connected renewable energy *** input information is collected from two input *** that,input layer transfer information to hidden layer 1 fuzzy PI is employed for controlling voltage in GPIC-MDCNNC *** layer 1 is transferred to hidden layer *** activation is employed for determining the output voltage with help of the *** last,the output layer offers the last value in GPIC-MDCNNC *** designed method was confirmed using one and multiple sources by stable and unpredictable input ***-MDCNNC Model increases the performance of grid-connected renewable energy systems by enhanced voltage value compared with state-of-the-art *** control technique using GPIC-MDCNNC Model increases the dynamics of hybrid energy systems connected to the grid.

关键词： Multi-port converters renewable sources fuzzy PI controller gaussian activation function fuel cell

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S3AM++: Integrating Differential Strategy into Spectral-Similarity-Based Spatial Attention Module for Hyperspectral Remote Sensing Image Classification 23

S3AM++: Integrating Differential Strategy into Spectral-Simi...

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15th International Conference on Digital Image Processing, ICDIP 2023

作者： Li, Ningyang Wang, Zhaohui Cheikh, Faouzi Alaya Ullah, Mohib Faculty of Computer Science and Technology Hainan University China Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology China

ISBN: (纸本)9798400708237

Algorithms based on deep learning, especially the attention mechanism, have been the preference for hyperspectral remote sensing image classification. Recently, a spectral similarity based spatial attention module (S3AM) was designed to solve the deficiency that the existing attention modules cannot take the center pixel into full account for the deduction of the spatial attention. However, two crucial processes, including the calculation and conversion of spectral similarity, of this module may be affected by its single policy, which is harmful to alleviate the spectral variability and the accurate spatial attention. In this article, an improved version called S3AM++ which integrates the differential strategy into the original attention module is proposed for hyperspectral image classification. The S3AM++ divides each neighborhood of the center pixel into the relevant pixel and the interfering pixel implicitly to make the individual optimization of the network for the two kinds of pixels possible. Benefit from this specific, the spectral variability can be relieved effectively for the similarity calculation and the relevant pixels and the interfering pixels can be preserved and restrained appropriately during the similarity conversion, respectively. Experimental results reveal that the spatial attention derived by the S3AM++ is more representative and the classification performance of the model adopting the new attention module is superior. © 2023 ACM.

关键词： Pixels

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Quadtree-based Free-space Cell-decomposition for Pathplanning with RRT* Implementation

Quadtree-based Free-space Cell-decomposition for Pathplannin...

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AIAA science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Otte, Noah Satpute, Sumeet Gajanan Banerjee, Avijit Nikolakopoulos, George Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper introduces a novel, computationally efficient, random-search based path-planning algorithm specifically designed to enhance the dexterous accessibility of autonomous lunar rovers operating on highly cluttered obstacle-dense planetary surfaces. The proposed pathplanning framework employs a Quadtree-based cell decomposition to enhance the performance of sampling-based path-planning algorithms, specifically those in the category of Rapidlyexploring Random Trees (RRT) and its optimized variant, RRT*. In the process of generating the path through an occupancy grid map, the obstacle-free cells are utilized as discrete sampling points for the RRT* algorithm. A unique non-uniform sampling approach is employed to favour larger cells with a higher degree of safety, thereby enabling seamless navigation through the obstacle-dense map. Additionally, the non-uniform sampling approach enhances the overall computational efficiency of the framework, making it suitable for fast, lightweight onboard implementation. The efficacy of the proposed planning framework is demonstrated through numerous simulation scenarios. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Decision trees

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A METHOD FOR MONITORING SLOW ELECTROMECHANICAL OSCILLATIONS IN MULTI-AREA electrical POWER SYSTEMS: THE CASE OF FOUR AREAS IEEE 39 BUS POWER SYSTEM 14

A METHOD FOR MONITORING SLOW ELECTROMECHANICAL OSCILLATIONS ...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Ilić, Marija D. Lawson, Riley E. Umbereen, Sayyeda Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering KTH Stockholm Sweden

ISBN: (纸本)9781837242689

This paper illustrates an earlier introduced method for systematic monitoring and control of slow electro-mechanical oscillations in electric power systems. The emphasis is on generalizing the two-area system concepts to a general multi-area power system. The method illustrates a transformed state space which explicitly models tie-line flow power dynamics between areas of interest (groups of interconnected equipment) and the rest of the system. Given parameters of an electric power grid, these tie-line power flow oscillations are expressed in terms of load and generation power deviations from given equilibrium, both controlled and uncontrolled. This new model sets the basis for identifying root causes of slow inter-area oscillations, needed to define the most important measurements and placement/enhancement of controllers for reducing these interactions. Notably, both conventional model and the transformed state space model have the same eigenvalues. The proposed approach does not require eigenmode calculations, and therefore lends itself to practical use of Phasor Measurmeent Units (PMUs). It is then shown how each area can monitor, compute and control inter-area oscillations either in an entirely decentralized way, much the same way as today's Automatic Generation Control (AGC) is carried out, or in a cooperative efficient way by jointly controlling inter-area fluctuations. © The Institution of engineering & technology 2024.

关键词： Eigenvalues and eigenfunctions

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NCFS:new chaotic fuzzy system as a general function approximator

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Journal of Control and Decision 2023年第4期10卷 514-528页

作者： Hamid Abbasi Mahdi Yaghoobi Arash Sharifi Mohammad Teshnehlab Department of Computer Engineering Science and Research BranchIslamic Azad UniversityTehranIran Department of Electrical and Computer Engineering Mashhad BranchIslamic Azad UniversityMashhadIran Department of Electrical and Computer Engineering K.N.T University of TechnologyTehranIran

Conventional fuzzy systems(type-1 and type 2)are universal *** goal of this paper is to design and implement a new chaotic fuzzy system(NCFS)based on the Lee oscil-lator for function approximation and chaotic *** incorporates fuzzy reasoning of the fuzzy systems,self-adaptation of the neural networks,and chaotic signal generation in a unique *** features enable the structure to handle uncertainties by generating new information or by chaotic search among prior *** fusion of chaotic structure into the neurons of the membership layer of a conventional fuzzy system makes the NCFS more capable of confronting nonlinear *** on the GFA and Stone-Weierstrass theorems,we show that the proposed model has the function approximation *** NCFS perfor-mance is investigated by applying it to the problem of chaotic *** results are demonstrated to ilustrate the concept of function approximation.

关键词： Chaotic fuzzy system function approximation chaotic neural network oscillatory neuron

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Coverage Hole Aware Data Routing for Mobile Sink Wireless Sensor Networks 14

Coverage Hole Aware Data Routing for Mobile Sink Wireless Se...

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14th IEEE International Conference on Electronics Information and Emergency Communication, ICEIEC 2024

作者： Wedaj, Fisseha Teju Hawbani, Ammar Wang, Xingfu Al-Gunid, Haithm M. Yilma, Getinet Farooq Qaisar, Muhammad Umar University of Science and Technology of China School of Computer Science and Technology Hefei China Shenyang Aerospace University School of Computer Science Shenyang China Adama Science and Technology University School of Electrical Engineering and Computing Adama Ethiopia Southern University of Science and Technology School of System Design and Intelligent Manufacturing Shenzhen China

ISBN: (纸本)9798350361889

In wireless sensor networks (WSNs), the coverage hole problem is one of the challenging problems that needs an effective solution. Data routing protocols in WSNs aim to disseminate the sensors' data to the central device with the minimum possible network resource usage. However, suppose there is a coverage hole in the middle of the source and destination nodes, and the source node doesn't have information about the hole. In that case, the data may choose the longer and more repetitive path to reach the destination, increasing resource usage, mainly energy and time. The condition is even more challenging when the network employs a mobile data collector. This paper proposes a Coverage Hole Aware Data Routing (CHADR) protocol for Mobile Sink WSNs that determines the shorter hole bypassing path in advance at the source node using the hole and data collector location information. CHADR evaluates the path efficiency using directional angle and expected hops count. After determining the path, data will be transmitted to the mobile sink using an Opportunistic routing technique. We proved CHADR performance with experimental simulations. © 2024 IEEE.

关键词： Routing protocols

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A FSS Inverse Design Method Based on Output Space Mapping Enhanced ECM

A FSS Inverse Design Method Based on Output Space Mapping En...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Tian, Ziheng Zhang, Juntao Kuang, Yu Cheng, Qingsha S. Southern University of Science and Technology Department of Electrical and Electronic Engineering Shenzhen China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore

ISBN: (纸本)9798350355581

This paper proposes an inverse design method for frequency selective surfaces (FSS) based on an equivalent circuit model (ECM) and output space mapping (OSM) technique. The method establishes an OSM enhanced ECM model (forward model) to replace expensive electromagnetic (EM) simulations for FSS shielding effectiveness (SE) evaluation. Furthermore, an inverse model is proposed to predict FSS unit cell structure parameter values using specification-driven feature point sampling method. Experiment results demonstrate that FSS designs with shielding frequency between 2-18GHz can be efficiently predicted and verified by EM simulation. © 2024 IEEE.

关键词： Frequency selective surfaces

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