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DistFlow Safe Reinforcement Learning Algorithm for Voltage Magnitude Regulation in Distribution Networks

Journal of Modern Power systems and Clean Energy 2025年第1期13卷 300-311页

作者： Shengren Hou Aihui Fu Edgar Mauricio Salazar Duque Peter Palensky Qixin Chen Pedro P.Vergara Intelligent Electrical Power Grids(IEPG)Group Delft University of TechnologyDelft 2628CDThe Netherlands Electrical Energy Systems(EES)Group Eindhoven University of TechnologyEindhovenThe Netherlands State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

The integration of distributed energy resources(DERs)has escalated the challenge of voltage magnitude regulation in distribution ***-based approaches,which rely on complex sequential mathematical formulations,cannot meet the real-time *** reinforcement learning(DRL)offers an alternative by utilizing offline training with distribution network simulators and then executing online without ***,DRL algorithms fail to enforce voltage magnitude constraints during training and testing,potentially leading to serious operational *** tackle these challenges,we introduce a novel safe-guaranteed reinforcement learning algorithm,the Dist Flow safe reinforcement learning(DF-SRL),designed specifically for real-time voltage magnitude regulation in distribution *** DF-SRL algorithm incorporates a Dist Flow linearization to construct an expert-knowledge-based safety ***,the DF-SRL algorithm overlays this safety layer on top of the agent policy,recalibrating unsafe actions to safe domains through a quadratic programming *** results show the DF-SRL algorithm consistently ensures voltage magnitude constraints during training and real-time operation(test)phases,achieving faster convergence and higher performance,which differentiates it apart from(safe)DRL benchmark algorithms.

关键词： Voltage regulation distribution network safe reinforcement learning energy management

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A DQN-Based Cache Strategy for Mobile Edge Networks

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Computers, Materials & Continua 2022年第5期71卷 3277-3291页

作者： Siyuan Sun Junhua Zhou Jiuxing Wen Yifei Wei Xiaojun Wang School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing100876China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing100854China Ningbo Sunny Intelligent Technology Co. LTDYuyao315400China Dublin City University Dublin 9Ireland

The emerging mobile edge networks with content caching capability allows end users to receive information from adjacent edge servers directly instead of a centralized data warehouse,thus the network transmission delay and system throughput can be improved *** the duplicate content transmissions between edge network and remote cloud can be reduced,the appropriate caching strategy can also improve the system energy efficiency of mobile edge networks to a great *** paper focuses on how to improve the network energy efficiency and proposes an intelligent caching strategy according to the cached content distribution model for mobile edge networks based on promising deep reinforcement learning *** deep neural network(DNN)and Q-learning algorithm are combined to design a deep reinforcement learning framework named as the deep-Q neural network(DQN),in which the DNN is adopted to represent the approximation of action-state value function in the Q-learning *** parameters iteration strategies in the proposed DQN algorithm were improved through stochastic gradient descent method,so the DQN algorithm could converge to the optimal solution quickly,and the network performance of the content caching policy can be *** simulation results show that the proposed intelligent DQN-based content cache strategy with enough training steps could improve the energy efficiency of the mobile edge networks significantly.

关键词： Mobile edge network edge caching energy efficiency

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A comprehensive survey of visible infrared person re-identification from an application perspective

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Multimedia Tools and Applications 2024年第42期83卷 90243-90270页

作者： Chang, Hua Xu, Xin Liu, Wei Lu, Lingyi Li, Weigang School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan430065 China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

Person re-identification (ReID) is a significant issue in computer vision, aiming to match the same pedestrian across various cameras. Recent research on this issue has successfully reached a satisfactory performance level in the daytime scenario. However, the performance of ReID in low illumination scenarios suffers a dramatic degradation due to the insufficient personal information captured by visible cameras in low or no light scenarios. To address this challenge, the adoption of novel camera technologies for more effective pedestrian data is imperative. Owing to the constraints of distance and usage scenarios in deploying depth cameras, practical infrared cameras are frequently utilized, spurring research in visible infrared person re-identification (VI-ReID). Significant progress has been made in the field of VI-ReID in recent years, but only a few reviews have categorized this problem based on methodology. This article offers a novel perspective by classifying VI-ReID according to application scenarios. Following our categorization scheme, the main advancements in deep learning for VI-ReID over the past five years have been grouped into three categories as follows: retrieval of infrared images using visible images (V→IR), retrieval of visible images using infrared images (IR→V), and joint retrieval of infrared and visible images (V→IR and IR→V). Next, this survey outlines the available datasets and evaluation metrics. After that, we categorize diverse methodologies under the proposed classification and assess their performance metrics across common datasets. Finally, we present two prospective avenues for future research in this domain, informed by the current state of advancement. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

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Integrated approach of predicting rock stability in high mountain valley underground caverns

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Underground Space 2024年第6期19卷 317-341页

作者： Fuyuan Tan Haosen Guo Pengzhi Pan Zhaofeng Wang Xufeng Liu Yangyi Zhou East China Jiaotong University Nanchang 467200China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan 430071China Key Laboratory of Liaoning Province on Deep Engineering and Intelligent Technology Northeastern UniversityShenyang 110819China University of Chinese Academy of Sciences Beijing 100049China

High mountain valleys are characterized by the development of intricate ground stress fields due to geological processes such as tectonic stress,river erosion,and rock *** processes introduce considerable stability concerns in the surrounding rock formations for underground engineering projects in these regions,highlighting the imperative need for rigorous stability assessments during the design phase to ensure construction *** paper introduces an innovative approach for the pre-evaluation of the stability of surrounding rocks in underground caverns situated within high mountain *** methodology comprises several pivotal ***,we conduct inverse calculations of the ground stress field in complex geological terrains,combining field monitoring and numerical ***,we ascertain stress-strength ratios of the surrounding rocks using various rock strength *** assess the stability characteristics of the surrounding rocks in the 1^(#)spillway cave within our project area,we employ numerical simulations to compute stress-strength ratios based on different rock strength ***,we undertake a comparative analysis,utilizing data from the 5^(#)Underground laboratory(Lab 5)of Jinping II Hydropower Station,aligning the chosen rock strength criterion with the damage characteristics of Lab 50s surrounding *** analysis serves as the cornerstone for evaluating other mechanical responses of the surrounding rocks,thereby validating the pre-evaluation *** pre-evaluation method takes into account the intricate geological evolution processes specific to high mountain *** also considers the influence of the initial geostress field within the geological range of underground *** comprehensive approach provides a robust foundation for the analysis and assessment of the stability of surrounding rocks,especially in high mountain valley areas,during the design phase of underground engi

关键词： High mountain valley Underground cavern Stability of surrounding rock On-site monitoring Stress-strength ratio Numerical simulation

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High-spatial-resolution phase-chaos Brillouin optical correlation domain sensor: theoretical analysis and experimental demonstration

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Journal of Lightwave technology 2025年第12期43卷 5957-5966页

作者： Niu, Lintao Wang, Yahui Tian, Yixiu Ma, Jinglian Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Taiyuan University of Technology College of Physics and Optoelectronic Engineering Taiyuan030024 China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan030032 China

The predicaments of micro-scale gain motivation and its high signal-to-noise ratio (SNR) extraction primarily restrict the practical measurement of a superior spatial resolution (SR) for stimulated Brillouin scattering sensors. A high-SNR phase-chaos laser Brillouin optical correlation domain analysis (PCL-BOCDA) is introduced to breakthrough the physical bottlenecks. The fundamental principle of gain excitation scale based on PCL linewidth is proposed, and a novel SR evolvement model is constructed. The significant impact of edge effects on SR measurement is thoroughly analyzed, and this approach is theoretically capable of achieving higher SR benefiting from the narrower gain range and feebler accumulation noise. Experiments with different linewidth PCLs are conducted and the results are confirmed to the simulated ones. Ultimately, an SR of 4.8 mm with a relative error of 4.3% is achieved over a 1.14 km sensing distance, representing a tenfold improvement over previous results. This advancement provides a competent approach for high-SR sensors and their application. © 1983-2012 IEEE.

关键词： Stimulated Brillouin scattering

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A semantic and emotion-based dual latent variable generation model for a dialogue system

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CAAI Transactions on Intelligence technology 2023年第2期8卷 319-330页

作者： Ming Yan Xingrui Lou Chien Aun Chan Yan Wang Wei Jiang State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijingChina School of Information and Communications Engineering Communication University of ChinaBeijingChina Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijingChina Department of Electrical and Electronic Engineering The University of MelbourneMelbourneVictoriaAustralia School of Data Science and Intelligent Media Communication University of ChinaBeijingChina

With the development of intelligent agents pursuing humanisation,artificial intelligence must consider emotion,the most basic spiritual need in human *** emotional dialogue systems usually use an external emotional dictionary to select appropriate emotional words to add to the response or concatenate emotional tags and semantic features in the decoding step to generate appropriate ***,selecting emotional words from a fixed emotional dictionary may result in loss of the diversity and consistency of the *** propose a semantic and emotion-based dual latent variable generation model(Dual-LVG)for dialogue systems,which is able to generate appropriate emotional responses without an emotional *** from previous work,the conditional variational autoencoder(CVAE)adopts the standard transformer ***,Dual-LVG regularises the CVAE latent space by introducing a dual latent space of semantics and *** content diversity and emotional accuracy of the generated responses are improved by learning emotion and semantic features ***,the average attention mechanism is adopted to better extract semantic features at the sequence level,and the semi-supervised attention mechanism is used in the decoding step to strengthen the fusion of emotional features of the *** results show that Dual-LVG can successfully achieve the effect of generating different content by controlling emotional factors.

关键词： conditional variational autoencoder dual latent space emotional responses latent variable generation

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Optimal Tracking Neuro-Control of Continuous Stirred Tank Reactor systems: A Dynamic Event-Driven Approach

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2117-2126页

作者： Yang, Xiong Zhou, Yingjiang Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin300072 China Nanjing University of Posts and Telecommunications College of Automation and College of Artificial Intelligence Nanjing210023 China

It is often challenging to design an optimal tracking controller for the continuous stirred tank reactor (CSTR) system due to its nonlinear nature and physical limitations. This article presents a dynamic event-driven optimal tracking neruo-control scheme for the CSTR system with asymmetric input constraints. Initially, an improved nonquadratic cost function is introduced for the CSTR system to tackle asymmetric control restrictions. Then, a dynamic event-driven mechanism together with the event-driven Hamilton-Jacobi-Bellman equation (ED-HJBE) is proposed. To solve the ED-HJBE, a critic neural network (CNN) is constructed within the critic learning framework. The CNN's weight vector is tuned by combining the gradient descent method and the concurrent learning technique. After that, uniform ultimate boundedness of the tracking error and the CNN's weight estimation error is assured based on the Lyapunov method. Finally, experiment studies are conducted to validate the present optimal tracking neuro-control strategy. © 2023 IEEE.

关键词： Reinforcement learning

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V2G Charging and Discharging Information Authentication Based on Blockchain technology 4

V2G Charging and Discharging Information Authentication Base...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Jiang, Yuan Du, Shuang Xu, Wenli Dong, Youxia Huzhou Vocational and Technical College Huzhou Key Laboratory of IoT Intelligent System Integration Technology Huzhou China Changxing Meteorological Bureau Huzhou China

ISBN: (纸本)9798350349252

Currently, traditional Public key Infrastructure (PKI) technology faces issues such as single points of failure and cumbersome certificate management in security authentication. The decentralized and tamper-proof characteristics of blockchain technology can provide feasible solutions to these problems. Therefore, this paper proposes a blockchain-based Vehicle-to-Grid (V2G) charging and discharging information authentication scheme. First, the background and significance of this study are explained, highlighting the importance of integrating blockchain with V2G. The system architecture for V2G charging and discharging information authentication based on blockchain technology is then designed, and the security requirements of the system are analyzed. Subsequently, to address the security issues present in the system, a blockchain-based information authentication scheme is proposed, which includes the design of vehicle charging and discharging information authentication and the design of the blockchain for vehicle charging and discharging information. This effectively ensures the security and accuracy of user information. Finally, the security of the proposed scheme is evaluated, and the results indicate that the proposed scheme meets the security requirements for V2G charging and discharging information authentication. © 2024 IEEE.

关键词： Vehicle-to-grid

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Carbody sway behaviour of railway vehicles due to track irregularity from rail alternate side wear

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Railway Engineering Science 2025年第1期33卷 27-42页

作者： Lai Wei Jing Zeng Ren Luo Feng Gan Jijun Gong Jun Jiang State Key Laboratory of Rail Transit Vehicle System Southwest Jiaotong UniversityChengdu 610031China China Railway Materials Operation and Maintenance Technology Co.Ltd. Beijing 100071China

Track irregularity from rail alternate side wear is manifested as uneven rail wear waveforms alternating in the left and right rails with equal intervals,which will cause carbody sway behaviour of railway vehicles and greatly influences the passenger *** this work,the carbody sway behaviour and mechanism due to track irregularity from rail alternate side wear and possible solutions to this issue were studied by the field testing and numerical calculation ***,the carbody sway of an urban rail transit train is introduced with full-scale field tests,through which the rail alternate side wear is characterized and the formatted track irregularity are ***,multibody vehicle dynamic models are developed to reproduce the carbody sway behaviour induced by the track irregularity from the rail alternate side *** creep forces acting on the wheel and rail are preliminarily discussed to study the influence of the carbody sway on the wear of the wheel flange and the rail ***,some potential solutions,*** the damping ratio of carbody rigid mode and rail grinding,are proposed to relieve this *** is concluded that an increased damping ratio of the carbody mode can alleviate the carbody sway and wheel–rail interactions,while properly maintaining track conditions can improve the vehicle performance.

关键词： Carbody sway Track irregularity Rail wear Creep force Carbody mode

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Mechanisms for the evolution of cell-to-cell variations and their impacts on fast-charging performance within a lithium-ion battery pack

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Journal of Energy Chemistry 2024年第12期99卷 11-22页

作者： Yufang Lu Xiaoru Chen Xuebing Han Dongxu Guo Yu Wang Xuning Feng Minggao Ouyang State Key Laboratory of Intelligent Green Vehicle and Mobility School of Vehicle and MobilityTsinghua UniversityBejing 100084China Research Institute of Tsinghua University in Shenzhen Shenzhen 518057.GuangdongChina Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology.Department of Chemical Engineering Tsinghua UniversityBeijing 100084China

Cell-to-cell variations(CtCV) compromise the electrochemical performance of battery packs, yet the evolutional mechanism and quantitative impacts of CtCV on the pack's fast-charging performance remain unexplored. This knowledge gap is vital for the proliferation of electric vehicles. This study underlies the relationship between CtCV and charging performance by assessing the pack's charge speed, final electric quantity, and temperature consistency. Cell variations and pack status are depicted using 2D parameter diagrams, and an m PnS configured pack model is built upon a decomposed electrode cell *** in three single electric parameters, i.e., capacity(Q), electric quantity(E), and internal resistance(R), and their dual interactions, i.e., E-Q and R-Q, are analyzed carefully. The results indicate that Q variations predominantly affect the final electric quantity of the pack, while R variations impact the charge speed most. With incremental variances in cell parameters, the pack's fast-charging capability first declines linearly and then deteriorates sharply as variations intensify. This research elucidates the correlations between pack charging capabilities and cell variations, providing essential insights for optimizing cell sorting and assembly, battery management design, and charging protocol development for battery packs.

关键词： Lithium-ion battery Battery pack Cell-to-cell variation Fast charging Performance evaluation

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