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8th IEEE International Energy Conference, ENERGYCON 2024

作者： Vadavathi, Aswin Ramesh Hoogsteen, Gerwin Hurink, Johann dept. of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands

ISBN: (纸本)9798350382150

The widespread increase of photovoltaic panels in the distribution grid often leads to overvoltage. Traditional voltage regulation techniques are unfair for prosumers at the sensitive part of the grid due to larger power curtailment. Consequently, there has been considerable research on implementing fair curtailment strategies for congestion management. However, existing fairness-incorporated curtailment approaches yield varying results based on changes in the grid topology and integration of renewable energy sources. Therefore, this paper introduces proportional voltage fairness that is independent of the above-mentioned network properties and inherently distinguishes regions for fair curtailment. Additionally, there is a need to consider the underutilisation of the grid while adhering to a fair curtailment scheme. Thus this paper proposes a control algorithm incorporating proportional voltage fairness and gives the opportunity to specify the trade-off between fairness and the total power curtailed. Further, a comparative analysis with respect to state-of-the-art notions of fairness is performed. ©2024 IEEE.

关键词： Electric power distribution

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Cross-Domain Learning for Power Grid Security: Harnessing Human Physiology for Anomaly Detection 50

Cross-Domain Learning for Power Grid Security: Harnessing Hu...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Zadehgol-Mohammadi, Asef Shadmand, Mohammad B. Dept. of Electrical & Computer Engineering University of Illinois ChicagoIL United States

ISBN: (纸本)9781665464543

This work presents a novel approach to tackle the problem of real-time detection of cyber intrusions at power electronics dominated grids (PEDG) inverters by establishing an analogy between electrical and medical fields. The methodology leverages the significant similarities between electric grid and human body and posits the feasibility of utilizing the large body of knowledge available in medicine, particularly in the area of disease diagnosis, for the benefit of detecting intrusions occurring to the grid, considering the tools introduced by tremendous advances in artificial intelligence (AI). The theoretical foundation of the analogy is discussed and as a first validation step, the grid inverter voltage is classified into three types of normal, disturbed and anomalous by associating it with three classes of heart rate electrocardiogram (ECG) signals of normal sinus rhythm, mild arrhythmia (supraventricular), and severe arrhythmia (ventricular), respectively. This is done via AI-based time series analyzers which establish a mapping between the two signal categories and enable classifying grid voltage based on ECG using the trained analyzer block. Achieved results demonstrate validity of the approach and promise addressing one of the main challenges in developing intrusion detection systems, that is, data scarcity, by tapping at the enormous knowledge base in the medical field. © 2024 IEEE.

关键词： Knowledge based systems

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A review on 3D image reconstruction on specific and generic objects

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Materials Today: Proceedings 2023年 80卷 2400-2405页

作者： Shalma, H. Selvaraj, P. Dept. of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Dept. of Information Technology SRM Institute of Science and Technology Kattankulathur Chennai India

With the emergence of various techniques involved in deep learning the researchers of computer vision tends to focus on the strategies such as object recognition and segmentation of image. This has inclined to accomplish the deep learning techniques in 3D reconstruction of both specific and generic objects. As the space for reconstruction of 3D images either in single or multi view has envisioned the researchers to concentrate on the available technologies used for reconstruction. With the available built in methods and technologies in deep learning, the performance of the proposed methods were reviewed and analyzed using several parameters. As the remaking of 2D images is still in the beginning stage, it is important to study the 3D shape representations, various network architecture, methodologies and approaches behind 3D reconstruction. In this work a review of deep learning methods for single or multiple RGB images of specific and generic object 3D reconstruction was done. Several methods and their importance were also discussed along with the challenges encountered and with further research directions. This paper critically analyzes the various 3D Shaped Representations, 3D Data Network Architectures, dept. Estimation methods, Multi View Representations and the Data Representation Techniques. © 2021

关键词： Object recognition

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Kinematic Cycle Consistency Using Wearables and RF Data for Improved Human Skeleton Estimation 58

Kinematic Cycle Consistency Using Wearables and RF Data for ...

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58th Asilomar Conference on Signals, Systems and computers, ACSSC 2024

作者： Salehin, Sultanus Kearney, Sean Gurbuz, Z. The University of Alabama Dept. of Electrical & Computer Engineering TuscaloosaAL United States

ISBN: (纸本)9798350354058

Radar-based health monitoring has the potential to enable 24/7 in-home ambient sensing to increase accessibility to care in a privacy-protective, low-cost fashion. This paper focuses on the assessment of mobility and gait for early warning, post-treatment monitoring, and emergency response to health conditions affecting human movement. Current technology has focused on wearables for monitoring personalized health, but wearables are not effective if not worn. In this case radar can provide a backup source of health information, that can be utilized standalone or in conjunction with the information provided by a wearable. This paper explores the estimation of gait parameters and human pose (i.e. skeleton) using RF sensing alone as well as how wearables can be utilized with RF to improve estimation accuracy. In particular, we propose the concept of kinematic cycle consistency using RF and wearable-estimated kinematics to improve skeleton estimation accuracy. Our results are validated using a gold standard Vicon optical tracking system. © 2024 IEEE.

关键词： Musculoskeletal system

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MediAI: An AI Based Guide for Medical Content Authenticity Analysis

MediAI: An AI Based Guide for Medical Content Authenticity A...

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2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024

作者： Jadhav, Dhiraj Dighe, Aneesh Walunj, Ajinkya Sagri, Anish Bhandari, Akash Ashtagi, Rashmi Vishwakarma Institute of Technology Dept. of Computer Engineering Pune India

ISBN: (纸本)9798331517953

In the Internet age, it is critical to identify the legitimacy of accurate medical content. This proposed research offers a thorough NLP-driven architecture intended to improve the veracity and correctness of online medical material. The proposed system effectively differentiates AI-generated content from non-AI content by leveraging Machine Learning (ML) models for testing and Deep Learning (DL) models for implementation, particularly Long-Short Term Memory (LSTM) and Bidirectional Long-Short Term Memory (Bi-LSTM). This will help decrease the dissemination of medical misinformation with the use of higher techniques of ML and DL, hence greatly improving the level of public health literacy. The proposed system will be user-friendly and will provide real-time verification;hence it would be very useful for healthcare professionals, the general public, in effect leading to a better-informed and health-conscience society. © 2024 IEEE.

关键词： Electronic health record

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Optimal Slot Utilization in IEEE 802.15.4e TSCH Networks using Reinforcement Learning 35

Optimal Slot Utilization in IEEE 802.15.4e TSCH Networks usi...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Ara, Tarana Liscano, Ramiro Ontario Tech University Dept. of Electrical Computer and Software Engineering Oshawa Canada

ISBN: (纸本)9798350362244

This paper presents an innovative MAC scheduling algorithm to achieve energy savings in IEEE 802.15.4e TSCH sensor networks leveraging reinforcement learning to determine an optimal number of slots to keep active in order to maintain a specific packet delivery ratio for the network. The goal is to turn off slots in the 802.15.4e TSCH frame that are not highly utilized. Each node determines the slots that should be deactivated based on a threshold Q value. This scheduling strategy allows the nodes to conserve energy effectively by finding the optimal active timeslots for both transmission and reception. This algorithm we name it as RAST Reinforcement-based Slot utilization Technique) algorithm. Through extensive simulations and evaluations across various network configurations, the RAST algorithm reveals a significant packet delivery ratio improvement as compared to Orchestra utilizing less active slots. © 2024 IEEE.

关键词： Scheduling algorithms

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Ontology-Driven Reinforcement Learning for Personalized Student Support

Ontology-Driven Reinforcement Learning for Personalized Stud...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Hare, Ryan Tang, Ying Rowan University Dept. of Electrical and Computer Engineering GlassboroNJ United States

ISBN: (纸本)9781665410205

In the search for more effective education, there is a widespread effort to develop better approaches to personalize student education. Unassisted, educators often do not have time or resources to personally support every student in a given classroom. Motivated by this issue, and by recent advancements in artificial intelligence, this paper presents a general-purpose framework for personalized student support, applicable to any virtual educational system such as a serious game or an intelligent tutoring system. To fit any educational situation, we apply ontologies for their semantic organization, combining them with data collection considerations and multi-agent reinforcement learning. The result is a modular system that can be adapted to any virtual educational software to provide useful personalized assistance to students. © 2024 IEEE.

关键词： Adversarial machine learning

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Data-Driven Estimation of Grid Voltage Phase Angle through di/dt Analysis for Hysteresis-Controlled Single Phase Inverter

Data-Driven Estimation of Grid Voltage Phase Angle through d...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Akuta, Hector Li, Yuan University of Pittsburgh Dept. of Electrical & Computer Engineering PittsburghPA United States

ISBN: (纸本)9798350376067

This paper proposes a data-driven method for estimating grid voltage phase angle in a hysteresis-controlled single-phase inverter through current derivative analysis, bypassing the need for voltage sensors and phase-locked loops (PLLs). Particularly beneficial for weak grid connections, this voltage-sensorless approach incorporates unique data processing and both linear and nonlinear curve fitting techniques. Its effectiveness is validated by simulations and experimental data, showcasing the potential for enhancing the resilience of grid-connected converters in renewable energy systems. © 2024 IEEE.

关键词： Hysteresis

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Prospects and Challenges of Inertia Emulation Methods for Low Inertia Power Systems 4

Prospects and Challenges of Inertia Emulation Methods for Lo...

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4th International Conference on Smart Grid and Renewable Energy, SGRE 2024

作者： Umar, Muhammad F. Nazari, Amirhosein Gohari Shadmand, Mohammad B. University of Illinois Dept. of Electrical & Computer Engineering ChicagoIL United States

ISBN: (纸本)9798350306262

Due to massive incorporation of the renewable energy resources into the upcoming power grid, the share of power generation from synchronous generator (SG) is being decreased and is being replaced by distribution generation (DG). This change has led the significant decrease in the overall power system's inertia and transforming the future power system into low inertia power systems (LIPS). Because of the huge rotational mass of SG, it intrinsically provides system inertia that is critical for the stable and resilient operation of the power system under different types of disturbances. To cope with the challenges of stable operation of LIPS, several inertia emulation schemes has been proposed in the previous literature. However, each scheme has its specific benefits, limitations, and applications. Thus, this paper provides a comprehensive insight to the inertia emulation schemes for DG and compares each scheme in terms of implementation challenges and experimental effectiveness in enhancing the overall system's inertia. Moreover, this comparison is supported with experimental results and analysis to validate virtual inertia emulation schemes. © 2024 IEEE.

关键词： Renewable energy

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DC Fault Detection Using Time Derivative of High-Pass Filter Response in MTDC Systems 50

DC Fault Detection Using Time Derivative of High-Pass Filter...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Khan, Saad Ahmed Ukil, Abhisek Nair, Nirmal-Kumar C. Dept. of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand

ISBN: (纸本)9781665464543

In the DC fault event, DC link capacitors immediately discharge a colossal current of high frequency. These large currents of high frequencies can instantly damage the components attached to the DC transmission system. Therefore, a rapid and robust DC fault detection topology is necessary, facilitating protection coordination in forthcoming Multi-Terminal Direct Current (MTDC) systems. This study introduces a novel fault detection technique using the time derivative of the High Pass Filter (HPF) response to identify fault currents in just a few microseconds (µs). This topology enables protection coordination for modern MTDC systems. Furthermore, this technique can identify different types of DC faults and remains unaffected by AC faults and load variation. © 2024 IEEE.

关键词： Chebyshev filters

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