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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Wang, Jingyu Ding, Li Zhou, Tao University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai China

ISBN: (纸本)9798331515669

In classical Finite Rate of Innovation (FRI) theory, signal reconstruction is initially achieved with precision using the zeroing filter algorithm on noiseless pulse signals. However, with the introduction of noise, the zeroing filter algorithm exhibits reduced robustness when handling signals with low signal-to-noise ratios (SNR). This paper introduces the TLS-ESPRIT algorithm, which enhances robustness against noise to some extent. Additionally, building on the development of an FRI reconstruction system based on C-TEM sampling, this work innovatively proposes a cascaded filter phase compensation method. This method mitigates the nonlinear phase effects of analog filters, thereby improving reconstruction accuracy. Ultimately achieving a reduction in sampling rate while improving reconstruction accuracy. © 2024 IEEE.

关键词： Signal to noise ratio

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A Comparative Analysis of Early Departure Buttons in Coordinated Control of EV Charging

A Comparative Analysis of Early Departure Buttons in Coordin...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Ozceylan, Baver Hoogsteen, Gerwin Hurink, Johann L. University of Twente Dept. of Electrical Engineering Mathematics and Computer Science Enschede Netherlands

ISBN: (纸本)9789531842976

The increasing adoption of electric vehicles (EVs) necessitates the efficient management of large EV parking facilities to prevent them from exceeding grid capacity and to improve the overall user experience. This paper introduces a data-driven approach for coordinated control of EV charging in an office parking facility, integrating Early Departure Buttons (EDB) into the system. These buttons provide a binary option for users to indicate an earlier departure than a predefined time. We employ the EDB data to improve departure time estimations and to address issues where EVs receive no or only very low energy. We utilize three datasets originating from different geographical locations. One dataset displays a user pattern where users leave shortly after completing their charging, unlike the other datasets which follow typical working hours. Our simulations show that the unique user pattern significantly increases fairness among users, and integrating EDBs improves fairness for the other datasets to levels similar to those of quick station turnover. © 2024 IEEE.

关键词： electric vehicle energy management smart grid user information

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Designing A Student Success Framework with Zachman Architecture

Designing A Student Success Framework with Zachman Architect...

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2024 ASEE Annual Conference and Exposition

作者： Chaback, Benjamin Edward Watson, Bryan C. Embry-Riddle Aeronautical University Department of Electrical Engineering and Computer Science United States

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Towards Green AI by Reducing Training Effort of Recurrent Neural Networks Using Hyper-Parameter Optimization with Dynamic Stopping Criteria 22

Towards Green AI by Reducing Training Effort of Recurrent Ne...

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22nd IEEE International Symposium on Intelligent Systems and Informatics, SISY 2024

作者： Podgorelec, Vili Fister, Iztok Vrbancic, Grega University of Maribor Intelligent Systems Laboratory Faculty of Electrical Engineering and Computer Science Slovenia

ISBN: (纸本)9798350385601

Neural networks have become a leading model in modern machine learning, able to model even the most complex data. For them to be properly trained, however, a lot of computational resources are required. With the carbon footprint of ever-growing adoption of neural networks in mind, an approach to reduce the required training resources would be very welcome. We designed a new training effort reduction method based on the calculation of area under the normalized loss curve and assessed it on the electricity consumption forecasting problem with the recurrent neural networks. The results show that the proposed method was able to considerably reduce the amount of computational resources, while maintaining the predictive performance, and thus contributing towards the Green AI. © 2024 IEEE.

关键词： Green AI hyper-parameter optimization machine learning neural networks resource optimization

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A Comparative Study on Prosumers Load Demand and Production Forecasting Using Machine Learning and Time Series Techniques 16

A Comparative Study on Prosumers Load Demand and Production ...

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16th International Conference on Applied and Theoretical Electricity, ICATE 2024

作者： Solea, Claudiu Hera, Corina Florea, Adrian Morariu, Daniel Stanescu, Dorel Vintan, Maria Lucian Blaga University of Sibiu Computer Science and Electrical Engineering Department Sibiu Romania

ISBN: (纸本)9798350388107

A data-driven and realistic policy could overcome the current turmoil in the intricate energy landscape. With solar and wind expanding faster than liquified natural gas or nuclear ever have, local, bottom-up solutions, such as organising collaboratively residential prosumers into electricity trading communities and the efficient use of aggregators, are one way to resilience and control over these resources. This paper analyses the features and characteristics of some prosumers and facilitates the identification of relevant algorithms for the specific tasks of both load demand and production forecasting using machine learning and time series techniques, thus enabling them to operate on a level playing field in the market. Load demand and production forecast simulations on two data sets, one collected in 2019, corresponding to 50 residential households and a public building from Portugal, and the other from 2023, that aggregates values from 29 household prosumers from Romania, show that both simple and double exponential smoothing techniques are more accurate than Markov predictors. Provided that the external contingencies influencing either the consumption or the production are considered, the latter gives a better prediction accuracy for energy production, whereas the former provides a better forecast for the consumption. © 2024 IEEE.

关键词： Demand response

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Securing Energy Equity With Multilayer Market Clearing

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第3期2卷 301-312页

作者： Zhang, Qiwei Li, Fangxing The University of Tennessee Min H. Kao Department of Electrical Engineering and Computer Science KnoxvilleTN37996 United States

Energy equity has been quickly gaining attention as policymakers seek to place 'Clean Energy for ALL' at the center of the low-carbon energy transition. Power system researchers have started to build the groundwork for incorporating energy equity into grid modernization. However, existing research has mostly focused on energy equity from a policy perspective, such as concept clarifications and tariff designs for residential customers. Little effort has been devoted to discussing energy equity in wholesale markets and to reflecting energy equity in electricity price with technical models. To the best of our knowledge, this paper presents the first study attempting to understand and implement energy equity consideration within a physically constrained electricity market-clearing model. First, we identify and discuss several concerns regarding energy equity in the existing locational marginal pricing (LMP) model. Then, we propose a multilayer framework reflecting energy equity in LMPs. Finally, the proposed framework is elaborated via a modified PJM 5-bus system and demonstrated with the WECC 179-bus system. © 2023 IEEE.

关键词： Power markets

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Passive islanding detection in microgrids using artificial neural networks

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Applied Nanoscience (Switzerland) 2023年第4期13卷 2885-2900页

作者： Alyasiri, Ali Majeed Mohammed Kurnaz, Sefer Department of Electrical and Computer Engineering Institute of Science Altinbas University Istanbul Turkey

This research focuses on modeling and simulating voltage control of passive islanding detections with distributed generation. This research presents how reactive power generation and/or absorption can be utilized to partake voltage control in medium voltage distribution through multi-microgrids for passive islanding detection with rule-based mathematical model and artificial neural network (ANN). With the increased emphasis on renewable energy, modern power grids have become more reliant to smaller distributed generation units. Unlike traditional power grids that rely on larger centralized units, the detection of islanding events in these grids is more complex. However, it is still important to maintain the connection to the power grid to maintain high stability of the system and is also important to deenergize the grid when an islanding event happens, to protect the workers that may be working on the grid to clear the cause of the islanding. Islanding detection methods are categorized into passive, active and communication based. Active methods detect islanding by measuring the influence of noise they add to the grid, to predict the size of the grid, which reduces the quality of the power provided on that grid. Communication-based methods are expensive and highly reliable on the communications infrastructure, which limits their application. Unlike existing methods, the proposed method of ANN relies on the instantaneous current and voltage values to detect any islanding with an accuracy of 97.89% precisely. These values are directly fed to the ANN, i.e., without applying any feature extraction, so that, faster and more accurate decisions are made. The proposed method is expected to combine the high accuracy of ANNs with the faster change in instantaneous values, so that, faster and more accurate detection can be achieved. © 2022, King Abdulaziz City for science and Technology.

关键词： Detection Distributed energy Distribution grid Islanding Microgrid Reactive power Voltage control

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FPMT: Enhanced Semi-supervised Model for Traffic Incident Detection 27th

FPMT: Enhanced Semi-supervised Model for Traffic Incident De...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Lu, Xinying Xiao, Jianli School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

ISBN: (纸本)9783031781063

For traffic incident detection, the acquisition of data and labels is notably resource-intensive, rendering semi-supervised traffic incident detection both a formidable and consequential challenge. Thus, this paper focuses on traffic incident detection with a semi-supervised learning way. It proposes a semi-supervised learning model named FPMT within the framework of MixText. The data augmentation module introduces Generative Adversarial Networks to balance and expand the dataset. During the mix-up process in the hidden space, it employs a probabilistic pseudo-mixing mechanism to enhance regularization and elevate model precision. In terms of training strategy, it initiates with unsupervised training on all data, followed by supervised fine-tuning on a subset of labeled data, and ultimately completing the goal of semi-supervised training. Through empirical validation on four authentic datasets, our FPMT model exhibits outstanding performance across various metrics. Particularly noteworthy is its robust performance even in scenarios with low label rates. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Generative adversarial networks

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Sources of Nonlinearity in Phase Noise of MUTC Photodetectors at Comb-Line Frequencies

Sources of Nonlinearity in Phase Noise of MUTC Photodetector...

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2024 IEEE Photonics Conference, IPC 2024

作者： Anjum, Ishraq Md Simsek, Ergun Jamali Mahabadi, Seyed Ehsan Carruthers, Thomas F. Menyuk, Curtis R. University of Maryland Baltimore County Computer Science and Electrical Engineering MD United States

ISBN: (纸本)9798350361957

We calculate the phase noise of two high current modified uni-traveling carrier (MUTC) photodetectors at the first 100 comb-line frequencies. We observe a non-monotonic increase of phase noise. We investigate the underlying physics. Insights gained inform MUTC photodetector design and optimization for frequency-comb applications. © 2024 IEEE.

关键词： Photodetectors

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A Hybrid Rectifier Mode Control for Communication-Free Wireless Power Transfer

A Hybrid Rectifier Mode Control for Communication-Free Wirel...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Zhu, Gangwei Dong, Jianning Bauer, Pavol Delft University of Technology Department of Electrical Engineering Mathematics and Computer Science Delft Netherlands

ISBN: (纸本)9798350376067

This paper presents a hybrid rectifier mode control for broad-range output power regulation in wireless power transfer (WPT) systems. The proposed control method employs a secondary-side active rectifier for output tuning, thereby eliminating the necessity for communication links. Furthermore, leveraging the pulse-skipping technique, two hybrid modes are introduced in the proposed approach. These hybrid modes reduce circulating reactive power within the resonant circuits, thereby optimizing the transmission efficiency of the WPT systems. To validate the effectiveness of the proposed method, experiments were conducted using a WPT prototype. Experimental results demonstrate that the proposed approach achieves higher efficiency than the conventional phase-shift control strategy, with a maximum efficiency improvement of up to 3.7%. © 2024 IEEE.

关键词： Inductive power transmission

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