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arXiv 2024年

作者： Chen, Yuanbo Zheng, Kedi Gu, Yuxuan Wang, Jianxiao Chen, Qixin State Key Laboratory of Power Systems Department of Electrical Engineering Tsinghua University Beijing100084 China National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing100871 China

The grid-connected electric vehicles (EVs) serve as a promising regulating resource in the distribution grid with Vehicle-to-Grid (V2G) facilities. In the day-ahead stage, electric vehicle batteries (EVBs) need to be precisely dispatched and controlled to ensure high efficiency and prevent degradation. This article focuses on considering a refined battery model, i.e. the electrochemical model (EM), in the optimal dispatch of the local energy system with high penetration of EVs which replenish energy through V2G-equipped charge station and battery swapping station (BSS). In this paper, to utilize the EM efficiently, recursive EVB constraints and a corresponding matrix-based state update method are proposed based on EM power characterization. The charging EV state distribution is profiled and a multi-layer BSS model along with binary aggregation is proposed, in order to overcome the computation complexity of combining the refined battery constraints with the mixed integer optimization. Finally, a local energy system scenario is investigated for evaluation. The efficiency and effectiveness of EM consideration are assessed from the perspective of both the system and battery. Copyright © 2024, The Authors. All rights reserved.

关键词： Charging stations

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FPGA implementation of binary edwards curve point addition

Journal of Network Intelligence

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Journal of Network Intelligence 2021年第1期6卷 107-116页

作者： Pan, Jeng-Shyang Song, Pei-Cheng Yang, Qing-Yong Liao, Lyu-Chao Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Provincial Universities Key Laboratory of Industrial Control and Data Analysis Fujian University of Technology Fuzhou350118 China

Currently, information security is becoming more and more important. Elliptic Curve Cryptography (ECC) has attracted more attention due to its high security performance and short key length, and has been more and more used in the process of information encryption. This article provides the corresponding FPGA hardware design scheme for the binary Edwards curve in ECC. At the same time, four schemes are analyzed and compared for the multiplier module in the finite field module. Finally, using the relevant parameters of GF(2163) in the NIST standard, the behavior simulation experiment of the Point Addition module of the binary Edwards curve is carried out to prove the feasibility of the scheme. © 2021, Taiwan Ubiquitous Information. All rights reserved.

关键词： Field programmable gate arrays (FPGA)

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data Processing Technology for Network Abnormal Traffic Detection 4

Data Processing Technology for Network Abnormal Traffic Dete...

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4th International Conference on Machine Learning and Big data Analytics for IoT Security and Privacy, SPIoT 2023

作者： Wang, Kun Fu, Yu Duan, Xueyuan Xu, Jianqiao Liu, Taotao Department of Information Security Naval University of Engineering Wuhan430033 China School of Mathematics and Information Engineering Xinyang Vocational and Technical College Xinyang464000 China College of Computer and Information Technology Xinyang Normal University Xinyang464000 China Henan Key Laboratory of Analysis and Applications of Education Big Data Xinyang Normal University Xinyang464000 China

At present, the threats to network security are also increasing, among which abnormal traffic detection is the key link to ensure network security. Traditional detection methods based on signature or threshold are often difficult to adapt to the increasingly complex network environment and new attack methods. Therefore, this paper optimizes and improves the data processing technology, proposes a network ATD method based on particle swarm optimization(PSO) algorithm, and explores in detail the traffic data collection and pre-processing, the feature recognition of abnormal traffic, the application of PSO algorithm, real-time monitoring and response mechanism. The results of two sets of simulation experiments are as follows: compared with the traditional model, the accuracy rate of ATD of the improved algorithm is increased by 7.2% on average, and the detection time is reduced by 7.35s on average. This method not only enhances the adaptability of the model to new attacks, but also improves the degree of automation of detection. © 2024 The Authors.

关键词： Particle swarm optimization (PSO)

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Status and trends in the stability of the three largest ice shelves in Antarctica

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Science China Earth Sciences 2024年第8期67卷 2615-2632页

作者： Rongxing LI Guojun LI Lu AN Menglian XIA Da LV Yuan CHENG Aiguo ZHAO Tian CHANG Xiangbin CUI Shengkai ZHANG Shijie LIU Yixiang TIAN Weian WANG Center for Spatial Information Science and Sustainable Development Applications Tongji UniversityShanghai 200092China College of Surveying and Geo-informatics Tongji UniversityShanghai 200092China Postdoctoral Research Station of Shanghai Surveying and Mapping Institute Shanghai 200063China Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities Shanghai 200063China Institute for Conservation of Cultural Heritage School of Cultural Heritage and Information ManagementShanghai UniversityShanghai 200444China Polar Research Institute of China Shanghai 200136China Chinese Antarctic Center of Surveying and Mapping Wuhan UniversityWuhan 430079China

The Ross,Filchner-Ronne,and Amery ice shelves are the three largest ice shelves in Antarctica,playing a crucial role in supporting the Antarctic ice ***,current studies on the stability of the three largest ice shelves primarily focus on singular or limited factors,lacking a comprehensive assessment of multiple *** systematically and in-depth study the stability and trend of the three largest ice shelves,we comprehensively collected and analyzed key parameters,including elevation changes,basal melting,surface meltwater,major rifts propagation rate,suture zones,ice front area change rate,grounding lines,ice velocity,and mass ***,we selected the collapsed Larsen B Ice Shelf(LBIS),the rapidly changing and structurally weakened Pine Island Ice Shelf(PIIS),and the accelerating Totten Ice Shelf(TIS)as reference ice *** comparing and analyzing the key parameters between these reference ice shelves and the three largest ice shelves,we find the status and trends in the stability of the *** findings reveal that most key parameters of the three largest ice shelves present relatively minor variations compared to those of the reference ice ***,50%of the parameters are smaller than those of the accelerating TIS,88%are smaller than those of the rapidly changing PIIS,and all parameters are smaller than those of the collapsed ***,after analyzing parameters that are not smaller than those of the TIS,it is observed that they remain in a stable ***,the three largest ice shelves are currently undergoing natural changes that do not threaten their stability in the short ***,the evolution of the ice shelves under global climate change remains uncertain,making long-term observation and monitoring essential to assess their impact on sea level rise.

关键词： Three largest ice shelves in Antarctica key parameters Remote sensing monitoring Ice shelf stability Sea level change

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data Preprocessing Technology in Network Traffic Anomaly Detection

Data Preprocessing Technology in Network Traffic Anomaly Det...

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作者： Duan, Xueyuan Fu, Yu Wang, Kun Department of Information Security Naval University of Engineering Wuhan430033 China College of Computer and Information Technology Xinyang Normal University Xinyang464000 China Henan Key Laboratory of Analysis and Applications of Education Big Data Xinyang464000 China School of Mathematics and Information Engineering Xinyang Vocational and Technical College Xinyang464000 China

Computer network plays a very important role in today’s world. With the development of network technology and the increasing popularity of network topology, network management is facing huge challenges. Among them, finding network traffic anomalies is one of the most important tasks in network monitoring, and is an important technology in network intrusion, security monitoring, and performance maintenance. This paper aims to study data preprocessing techniques in network traffic anomaly detection. This paper firstly introduces the network traffic measurement characteristics completely, and then selects and applies the data preprocessing algorithm, constructs a complete data preprocessing framework, and conducts experiments for the abnormal detection of network multi-dimensional characteristic traffic and the abnormal detection of unit-level characteristic traffic. The superiority of the data preprocessing technology in this paper, by reducing the data, determines the data preprocessing threshold of this paper to ensure that the data preprocessing is maximized. Experiments show that the data preprocessing technology constructed in this paper has about 20% more data filtering than traditional data filtering, which shortens the amount of detection data. The threshold is around 0.6, and data preprocessing can maximize the reduction of data without destroying the integrity of the attacked data. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： data mining

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LECF: recommendation via learnable edge collaborative filtering

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Science China(Information Sciences) 2022年第1期65卷 116-130页

作者： Shitao XIAO Yingxia SHAO Yawen LI Hongzhi YIN Yanyan SHEN Bin CUI School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing Key Lab of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications School of Information Technology and Electrical Engineering The University of Queensland Department of Computer Science and Engineering Shanghai Jiao Tong University Department of Computer Science and Technology Peking University National Engineering Laboratory for Big Data Analysis and Applications Peking University

The core of recommendation models is estimating the probability that a user will like an item based on historical interactions. Existing collaborative filtering(CF) algorithms compute the likelihood by utilizing simple relationships between objects, e.g., user-item, item-item, or user-user. They always rely on a single type of object-object relationship, ignoring other useful relationship information in data. In this paper, we model an interaction between user and item as an edge and propose a novel CF framework, called learnable edge collaborative filtering(LECF). LECF predicts the existence probability of an edge based on the connections among edges and is able to capture the complex relationship in data. Specifically, we first adopt the concept of line graph where each node represents an interaction edge; then calculate a weighted sum of similarity between the query edge and the observed edges(i.e., historical interactions) that are selected from the neighborhood of query edge in the line graph for a recommendation. In addition, we design an efficient propagation algorithm to speed up the training and inference of LECF. Extensive experiments on four public datasets demonstrate LECF can achieve better performance than the state-of-the-art methods.

关键词： collaborative filtering recommender system implicit feedback edge-edge similarity line graph

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Zero-Order Optimization in Security Constrained Power System Scheduling 4

Zero-Order Optimization in Security Constrained Power System...

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4th IEEE International Conference on Electrical, Computer, and Energy Technologies, ICECET 2024

作者： An, Qi Wang, Jianxiao Wu, Shengyu Ren, Weikai Huang, Ruanming Li, Gengyin North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing China Peking University National Engineering Laboratory for Big Data Analysis and Applications Beijing China State Grid Energy Research Institute CO. LTD. Beijing China Institute of Energy Peking University Beijing China Planning Center State Grid Shanghai Electric Power Company Shanghai China

ISBN: (纸本)9798350395914

The security and resilience of power systems are gradually challenged. As a typical index measuring the security and resilience of power systems, the frequency stability issue is becoming prominent. Due to the increase in the complexity of power systems, the frequency stability boundary is gradually becoming fuzzy, leading to traditional analytical-modeling algorithms hardly applicable for frequency stability constrained dispatch. Existing data-driven methods for characterizing frequency stability boundary typically requires massive simulation calculations, leading to unnecessary computing power consumption. To this end, zeroth-order (ZO) optimization, which aims to solve optimization problems embedding non-analytic functions, is adopted for solving the frequency stability constrained dispatch in this paper. In contrast to traditional data-driven methods, we directly embed frequency stability simulation check into power system dispatch. The gradient of frequency stability simulation check is estimated through ZO optimization, thereby realizing the interaction optimization between power system dispatch and real-time simulation. In this way, the solution for the frequency stability constrained dispatch is modified towards the optimal point along the gradient descent direction. Cases studies based on IEEE-9 bus system verifies that, compared with traditional data-driven methods, the solution approach we propose could reduce the system cost while significantly improving the calculation efficiency. © 2024 IEEE.

关键词： Frequency stability

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Sharing Economy in Local Energy Markets

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Journal of Modern Power Systems and Clean Energy 2023年第3期11卷 714-726页

作者： Zhaoyuan Wu Jianxiao Wang Haiwang Zhong Feng Gao Tianjiao Pu Chin-Woo Tan Xiupeng Chen Gengyin Li Huiru Zhao Ming Zhou Qing Xia School of Economics and Management North China Electric Power UniversityBeijing 102206China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijing 100871China State Key Lab of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Industrial Engineering and Management College of EngineeringPeking UniversityBeijing 100871China China Electric Power Research Institute Beijing 100192China Department of Civil and Environmental Engineering Stanford UniversityPalo AltoCA 94305USA Engineering and Technology Institute Groningen University of Groningen9742 AG Groningenthe Netherlands

With an increase in the electrification of end-use sectors,various resources on the demand side provide great flexibility potential for system operation,which also leads to problems such as the strong randomness of power consumption behavior,the low utilization rate of flexible resources,and difficulties in cost *** the core idea of“access over ownership”,the concept of the sharing economy has gained substantial popularity in the local energy market in recent ***,we provide an overview of the potential market design for the sharing economy in local energy markets(LEMs)and conduct a detailed review of research related to local energy sharing,enabling technologies,and potential *** paper can provide a useful reference and insights for the activation of demand-side flexibility ***,this paper can also provide novel insights into the development and further integration of the sharing economy in LEMs.

关键词： Energy sharing flexibility potential local energy market information and communication technology sharing economy

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Load balance and time delay efficient algorithm for VNF service chain deployment based on DQN 18

Load balance and time delay efficient algorithm for VNF serv...

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18th International Conference on Computational Intelligence and Security, CIS 2022

作者： Xuan, Hejun Lin, Lidan Liu, Zhenghui Zhao, Xuelin Xinyang Normal University Department of Computer and Information Technology China Big Data Xinyang Normal University Henan Key Laboratory of Analysis and Applications of Education Xinyang Henan China Luo He Vocational Technology College Department of Information Engineering Luohe Henan China

ISBN: (纸本)9798350346275

In mobile edge computing, computing and storage resources are close to the network of the user device, which can effectively reduce network access and computing service delay. However, network function virtualization for mobile edge computing networks is more challenging due to the strong coupling of CPU resources, storage resources, and wireless resources. In order to solve the problems of load balance and long response time of user-oriented service function chain deployment algorithm in mobile edge computing networks, this paper proposed a load balance and time delay efficient algorithm (denoted as LBDQN) for virtual network function service chain deployment problem based Deep Q-LearningFirst, a global optimization model, which minimizes time delay and maximizes the load balance, is established. Then, a new real-time algorithm for VNF service chain deployment based on DQN is proposed. In this algorithm, an adaptive ϵ-greedy method is designed. In addition, a particle swarm optimization is used to optimize the neural network parameters. To demonstrate the efficiency of the proposed algorithm, some simulation experiments are conducted and the experimental results show that the algorithm can effectively reduce the time delay and improve the load balance than the compared algorithms. © 2022 IEEE.

关键词： Time delay

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Carbon-neutral pathway to mitigating transport-power grid cross-sector effects

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The Innovation 2024年第3期5卷 27-29页

作者： Jing Ma Huiwen Kong Jianxiao Wang Haiwang Zhong Bo Li Jie Song Daniel M.Kammen State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electrical and Electronic EngineeringNorth China Electric Power UniversityBeijing 102206China National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijing 100871China Peking University Ordos Research Institute of Energy Ordos 017000China State Key Laboratory of Power Systems and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijing 100084China School of Electrical Engineering Guangxi UniversityNanning 530004China Department of Industrial Engineering and Management College of EngineeringPeking UniversityBeijing 100871China Energy and Resources Group and Goldman School of Public PolicyUniversity of CaliforniaBerkeleyBerkeleyCA 94720USA

Dear Editor,The growing demand for transportation energy has brought increasing challenges to reducing greenhouse gas ***,many countries or regions have proposed solutions to achieve carbon-neutral transportation such as the rapid expansion of the global electric vehicle(EV)***,these benefits are not *** the goal of decarbonization in electricity is achieved,the“pseudo net zero emissions”effect of the transportation sector will inevitably be accompanied by a quiet shifting of carbon responsibility.1 This shift is undoubtedly fatal for both net zero emissions at the national level and carbon responsibility at the industry level;however,the corresponding effects have not yet been clarified.

关键词： neutral doubt shifting

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