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Full-model-free Adaptive Graph Deep Deterministic Policy Gradient Model for Multi-terminal Soft Open Point Voltage Control in Distribution Systems

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Journal of Modern Power Systems and Clean Energy 2024年第6期12卷 1893-1904页

作者： Huayi Wu Zhao Xu Minghao Wang Youwei Jia Department of Electrical and Electronic Engineering The Hong Kong Polytechnic UniversityHong KongChina Shenzhen Research Institute The Hong Kong Polytechnic UniversityShenzhenChina Department of Electrical and Computer Engineering University of MacaoMacaoChina Department of Electrical and Electronic Engineering Southern University of Science and TechnologyShenzhenChina

High penetration of renewable energy sources(RESs)induces sharply-fluctuating feeder power,leading to volt-age deviation in active distribution *** prevent voltage violations,multi-terminal soft open points(M-sOPs)have been integrated into the distribution systems to enhance voltage con-trol ***,the M-SOP voltage control recalculated in real time cannot adapt to the rapid fluctuations of photovol-taic(PV)power,fundamentally limiting the voltage controllabili-ty of *** address this issue,a full-model-free adaptive graph deep deterministic policy gradient(FAG-DDPG)model is proposed for M-SOP voltage ***,the attention-based adaptive graph convolutional network(AGCN)is lever-aged to extract the complex correlation features of nodal infor-mation to improve the policy learning ***,the AGCN-based surrogate model is trained to replace the power flow cal-culation to achieve model-free ***,the deep deterministic policy gradient(DDPG)algorithm allows FAG-DDPG model to learn an optimal control strategy of M-SOP by continuous interactions with the AGCN-based surrogate *** tests have been performed on modified IEEE 33-node,123-node,and a real 76-node distribution systems,which demonstrate the effectiveness and generalization ability of the proposed FAG-DDPGmodel.

关键词： Soft open point graph attention graph convolutional network reinforcement learning voltage control distribution system deep deterministic policy gradient

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Dynamically updated digital twin for prognostics and health management:Application in permanent magnet synchronous motor

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Chinese Journal of Aeronautics 2024年第6期37卷 244-261页

作者： Haoyu GUO Shaoping WANG Jian SHI Tengfei MA Giorgio GUGLIERI Rujun JIA Fausto LIZZIO School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Tianmushan Laboratory Hangzhou 310023China Department of Mechanical and Aerospace Engineering Polytechnic University of TurinTurin 10129Italy Beihang Ningbo Research Institute Ningbo 315800China

Current research on Digital Twin(DT)based Prognostics and Health Management(PHM)focuses on establishment of DT through integration of real-time data from various sources to facilitate comprehensive product monitoring and health ***,there still exist gaps in the seamless integration of DT and PHM,as well as in the development of DT multi-field coupling modeling and its dynamic update *** the product experiences long-period degradation under load spectrum,it is challenging to describe the dynamic evolution of the health status and degradation progression *** addition,DT update algorithms are difficult to be integrated simultaneously by current *** paper proposes an innovative dual loop DT based PHM framework,in which the first loop establishes the basic dynamic DT with multi-filed coupling,and the second loop implements the PHM and the abnormal detection to provide the interaction between the dual loops through updating *** proposed method pays attention to the internal state changes with degradation and interactive mapping with dynamic parameter ***,the Independence Principle for the abnormal detection is proposed to refine the theory of *** at the first loop focus on accurate modeling of multi-field coupling,while the events at the second loop focus on real-time occurrence of anomalies and the product degradation *** interaction and collaboration between different loop models are also ***,the Permanent Magnet Synchronous Motor(PMSM)is used to verify the proposed *** results show that the modeling method proposed can accurately track the lifecycle performance changes of the entity and carry out remaining life prediction and health management effectively.

关键词： Digital Twin(DT) Dynamic Update Independence Principle Multi-field Coupling Permanent Magnet Synchronous Motor(PMSM) Prognostics and Health Management(PHM)

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Counting vehicles types using deep learning algorithm in video surveillance systems

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Multimedia Tools and Applications 2024年 1-24页

作者： Akoushideh, Alireza Sadat, Seyed Shafiullah Shahbahrami, Asadollah Electrical and Computer Engineering Department National University of Skill Tehran Iran Computer Engineering Department Kabul Polytechnic University Kabul Afghanistan Computer Engineering Department University of Guilan Rasht Iran

Detection, identification, and automatic counting of vehicles using video surveillance cameras plays an essential role in intelligent transportation management. Despite the progress that researchers have made in these cases, its operational implementation still faces challenges such as various environmental conditions, unbalanced data sets, accuracy, and speed. Therefore, research is fundamental in solving these issues. This research investigates the use of deep convolutional neural networks (CNNs) for vehicle detection, classification, and counting in video surveillance applications. We analyze recent research trends and challenges, examining the suitability of popular datasets like MSCOCO, PASCAL, ImageNet, DAWN, DETRAC, and MIO-TCD for validating proposed algorithms. Our study focuses on overcoming challenges like poor lighting conditions and unbalanced traffic scenarios. We propose a novel approach for counting vehicle types based on the YOLO model. The proposed method leverages the YOLO model for object detection and recognition, the ByteTrack algorithm for tracking vehicles across frames, and the CLAHE pre-processing and the Multiple-Zone-Line approach for addressing video surveillance challenges. Experimental results on three benchmark videos demonstrate the superiority of YOLOv8 over YOLOv9 in our benchmarks. Moreover, the application of CLAHE pre-processing algorithms further enhances performance. This research offers a promising solution for accurate and robust vehicle detection, classification, and counting in real-world video surveillance scenarios. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Convolutional neural networks

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Power System Reliability Evaluation Based on Sequential Monte Carlo Simulation Considering Multiple Failure Modes of Components

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Journal of Modern Power Systems and Clean Energy 2025年第1期13卷 202-214页

作者： Wei Huang Bo Hu Changzheng Shao Wei Li Xiaozhe Wang Kaigui Xie C.Y.Chung State Key Laboratory of Power Transmission Equipment Technology School of Electrical EngineeringChongqing UniversityChongqingChina China Southern Power Grid GuangzhouChina Department of Electrical and Computer Engineering McGill UniversityMontrealCanada Department of Electrical and Electronic Engineering Hong Kong Polytechnic UniversityHong KongChina

The component aging has become a significant concern worldwide,and the frequent failures pose a serious threat to the reliability of modern power *** light of this issue,this paper presents a power system reliability evaluation method based on sequential Monte Carlo simulation(SMCS)to quantify system reliability considering multiple failure modes of ***,a three-state component reliability model is established to explicitly describe the state transition process of the component subject to both aging failure and random failure *** this model,the impact of each failure mode is decoupled and characterized as the combination of two state duration variables,which are separately modeled using specific probability ***,SMCS is used to integrate the three-state component reliability model for state transition sequence generation and system reliability ***,various reliability metrics,including the probability of load curtailment(PLC),expected frequency of load curtailment(EFLC),and expected energy not supplied(EENS),can be *** ensure the applicability of the proposed method,Hash table grouping and the maximum feasible load level judgment techniques are jointly adopted to enhance its computational *** studies are conducted on different aging scenarios to illustrate and validate the effectiveness and practicality of the proposed method.

关键词： Power system reliability evaluation aging failure sequential Monte Carlo simulation

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A 500 kHz Wide Output LLC-T Resonant Converter With Narrow Frequency Range, Reduced Circulating Energy, and Low Voltage Stress

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IEEE Transactions on Power Electronics 2025年第8期40卷 11749-11762页

作者： Hou, Zhengming Jiao, Dong Lai, Jih-Sheng Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering BlacksburgVA24061 United States

The resonant converters are promising topologies for the electric vehicle charging applications due to the soft switching feature. However, the conventional LLC resonant converter regulates the wide output voltage through a wide frequency range, which leads to low efficiency with large circulating energy and the difficulty of the resonant tank optimization. This article proposes a novel LLC-T resonant converter, which parallels an auxiliary transformer with the LC resonant tank for the wide output applications. The proposed LLC-T resonant converter narrows the frequency range with less circulating energy, lower voltage stress on the resonant capacitor, and smaller flux linkage in the resonant inductor compared to the conventional LLC resonant converter. Meanwhile, the zero-voltage switching turn-on is maintained throughout the wide output voltage range and load range. Furthermore, a precise time-domain based analysis and the design methodology are proposed. A 500-kHz, 1.35 kW, 400 V input 250 V-450 V output prototype is built to verify the concepts of the proposed topology and demonstrates a 97.82% peak efficiency. © 1986-2012 IEEE.

关键词： Resonant converters

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Optimized Temporary Frequency Support for Wind Power Plants Considering Expanded Operational Region of Wind Turbines

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 51-64页

作者： Zhengyang Hu Bingtuan Gao Zhao Xu Sufan Jiang School of Electrical Engineering Southeast UniversityNanjing210096China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic UniversityHong Kong SARChina Department of Electrical Engineering and Computer Science The University of TennesseeKnoxvilleTN 37996 USA

Wind power plants(WPPs)are increasingly mandated to provide temporary frequency support to power systems during contingencies involving significant power ***,the frequency support capabilities of WPPs under derated operations remain insufficiently investigated,highlighting the potential for further improvement of the frequency *** paper proposes a bi-level optimized temporary frequency support(OTFS)strategy for a *** implementation of the OTFS strategy is collaboratively accomplished by individual wind turbine(WT)controllers and the central WPP ***,to exploit the frequency support capability of WTs,the stable operational region of WTs is expanded by developing a novel dynamic power control approach in WT *** approach synergizes the WTs'temporary frequency support with the secondary frequency control of synchronous generators,enabling WTs to release more kinetic energy without causing a secondary frequency ***,a model predictive control strategy is developed for the WPP *** strategy ensures that multiple WTs operating within the expanded stable region are coordinated to minimize the magnitude of the frequency drop through efficient kinetic energy ***,comprehensive case studies are conducted on a real-time simulation platform to validate the effectiveness of the proposed strategy.

关键词： Active power control model predictive control optimized temporary frequency support wind power plant wind turbine

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A Deepfake Detection Algorithm Based on Fourier Transform of Biological Signal

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computers, Materials & Continua 2024年第6期79卷 5295-5312页

作者： Yin Ni Wu Zeng Peng Xia Guang Stanley Yang Ruochen Tan School of Electrical and Electronic Engineering Wuhan Polytechnic UniversityWuhan430023China School of Mathematics and Computer Science Wuhan Polytechnic UniversityWuhan430048China Paul G.Allen School of Computer Science and Engineering University ofWashingtonSeattleWA98195USA School of Computer Science and Engineering University of CaliforniaSanDiegoCA92093USA

Deepfake-generated fake faces,commonly utilized in identity-related activities such as political propaganda,celebrity impersonations,evidence forgery,and familiar fraud,pose new societal *** current deepfake generators strive for high realism in visual effects,they do not replicate biometric signals indicative of cardiac *** this gap,many researchers have developed detection methods focusing on biometric *** methods utilize classification networks to analyze both temporal and spectral domain features of the remote photoplethysmography(rPPG)signal,resulting in high detection ***,in the spectral analysis,existing approaches often only consider the power spectral density and neglect the amplitude spectrum—both crucial for assessing cardiac *** introduce a novel method that extracts rPPG signals from multiple regions of interest through remote photoplethysmography and processes them using Fast Fourier Transform(FFT).The resultant time-frequency domain signal samples are organized into matrices to create Matrix Visualization Heatmaps(MVHM),which are then utilized to train an image classification ***,we explored various combinations of time-frequency domain representations of rPPG signals and the impact of attention *** experimental results show that our algorithm achieves a remarkable detection accuracy of 99.22%in identifying fake videos,significantly outperforming mainstream algorithms and demonstrating the effectiveness of Fourier Transform and attention mechanisms in detecting fake faces.

关键词： Deepfake detector remote photoplethysmography fast fourier transform spatial attention mechanism

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Demonstration of wireless synchronisation methods in autonomously controlled fleet of drones

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International Journal of Mobile Network Design and Innovation 2024年第1期11卷 1-10页

作者： Lai, Christopher Song, Harris Madrigal, Aaron Youssef, Michael Lieng, Borick Hamida, Mohamed Tran, Quyen Ngo, Phu Chang, Bethany Dobbs, Steven Yu, Zhen Department of Electrical and Computer Engineering California State Polytechnic University PomonaCA91768 United States Department of Aerospace Engineering California State Polytechnic University PomonaCA91768 United States

This paper describes methods used in synchronising the behaviour of multiple autonomous flight vehicles utilising custom external hardware and firmware injected into current aviation flight systems. To prove the reliability and consistency of an autonomous ground-based landing sequence, a fleet of drones, each with varying capabilities and sizes, is modified to fit the landing criteria. Each drone in the fleet is controlled through a singular re-programmable controller running software developed for smooth and precise communication with a unmanned aerial vehicles (UAVs) onboard flight computer. The results of experiments performed on the landing sequence for each drone relay information about the strengths and weaknesses of the ground station landing protocol and pave the way for further innovation in autonomous landing procedures. © 2024 Inderscience Publishers. All rights reserved.

关键词： computer vision

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Enhanced battery life prediction with reduced data demand via semi-supervised representation learning

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Journal of Energy Chemistry 2025年第2期101卷 524-534,I0011页

作者： Liang Ma Jinpeng Tian Tieling Zhang Qinghua Guo Chi Yung Chung School of Mechanical MaterialsMechatronic and Biomedical EngineeringUniversity of WollongongNSW 2522Australia Department of Electrical and Electronic Engineering and Research Centre for Grid Modernisation The Hong Kong Polytechnic UniversityKowloonHong Kong 999077China Photonics Research Institute The Hong Kong Polytechnic UniversityKowloonHong Kong 999077China School of Electrical Computer and Telecommunications EngineeringUniversity of WollongongWollongongNSW 2522Australia

Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion *** various machine learning models offer promising predictions,one critical but often overlooked challenge is their demand for considerable run-to-failure data for *** of such training data leads to prohibitive testing efforts as the run-to-failure tests can last for ***,we propose a semi-supervised representation learning method to enhance prediction accuracy by learning from data without RUL *** approach builds on a sophisticated deep neural network that comprises an encoder and three decoder heads to extract time-dependent representation features from short-term battery operating data regardless of the existence of RUL *** approach is validated using three datasets collected from 34 batteries operating under various conditions,encompassing over 19,900 charge and discharge *** method achieves a root mean squared error(RMSE)within 25 cycles,even when only 1/50 of the training dataset is labelled,representing a reduction of 48%compared to the conventional *** also demonstrate the method's robustness with varying numbers of labelled data and different weights assigned to the three decoder *** projection of extracted features in low space reveals that our method effectively learns degradation features from unlabelled *** approach highlights the promise of utilising semi-supervised learning to reduce the data demand for reliability monitoring of energy devices.

关键词： Lithium-ion batteries Battery degradation Remaining useful life Semi-supervised learning

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Xf-Calc: Towards a Fair Comparison between Approaches for Fuzzy Numbers Arithmetic

Xf-Calc: Towards a Fair Comparison between Approaches for Fu...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Pisco-Jordan, Juan Ramos-Pozo, Luis Townsend-Hinostroza, Danae Tapia-Rosero, Ana ESPOL Polytechnic University Department of Electrical and Computer Engineering Guayaquil Ecuador

ISBN: (纸本)9798350374575

Since arithmetic operations that involve uncertain or imprecise linguistic expressions are often mentally solved, multiple approaches have been developed to emulate them with fuzzy numbers. Each approach may provide different results, and some may depend on a specific context. It is common to compare and analyze these approaches to determine which one is the best in different contexts. These comparisons can be laborious and prone to errors. In this paper a context-free calculator for fuzzy arithmetic is proposed. To facilitate the analysis of comparisons, this calculator is capable of solving an arithmetic problem using multiple approaches while providing reports. The first report shows the solution of each approach while the second report shows their respective graphical representation. The calculator has nine different approaches for addition, subtraction and multiplication with the flexibility to incorporate new approaches for further study. © 2024 IEEE.

关键词： Open source software

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