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arXiv 2025年

作者： Shi, Jianxin Chen, Jinhao Wang, Yuandong Sun, Li Liu, Chunyang Xiong, Wei Wo, Tianyu Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Information Engineering College Capital Normal University Beijing100048 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China Didi Chuxing Beijing100094 China

In recent years, the field of autonomous driving has attracted increasingly significant public interest. Accurately forecasting the future behavior of various traffic participants is essential for the decision-making of Autonomous Vehicles (AVs). In this paper, we focus on both scenario-based and perception-based motion forecasting for AVs. We propose a formal problem formulation for motion forecasting and summarize the main challenges confronting this area of research. We also detail representative datasets and evaluation metrics pertinent to this field. Furthermore, this study classifies recent research into two main categories: supervised learning and self-supervised learning, reflecting the evolving paradigms in both scenario-based and perception-based motion forecasting. In the context of supervised learning, we thoroughly examine and analyze each key element of the methodology. For self-supervised learning, we summarize commonly adopted techniques. The paper concludes and discusses potential research directions, aiming to propel progress in this vital area of AV technology. © 2025, CC BY.

关键词： Self-supervised learning

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Path Planning for Distribution Network Robots with Adaptive Simulated Annealing-Enhanced Artificial Potential Field Method

Path Planning for Distribution Network Robots with Adaptive ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Baichao Zhang Xin Chen Jinge Chen Jinbin Li Xiaokai Wang Xu Jian School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan P. R. China Hubei Fangyuan Dongli Electric Power Science Research Co. Ltd Wuhan P. R. China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

In this paper, we propose a hybrid algorithm that combines an improved Artificial Potential Field (APF) method with the Simulated Annealing (SA) algorithm for path planning of an electric power operation robot manipulator in complex distribution grid environments. To address the unreachable target issue inherent in traditional APF, we introduce a distance regulation factor to optimize the repulsive function. This modification allows the manipulator to smoothly approach the target point as it nears, while the repulsion from obstacles gradually decreases. Additionally, to overcome the limitations of the traditional SA algorithm, such as its tendency to get trapped in local minimum solutions and its inefficiency in complex environments, we propose an adaptive temperature rise strategy. This strategy increases the temperature, enhancing the probability of escaping local optimal solutions. When the APF algorithm becomes trapped in a local optimum, the improved SA algorithm is applied to escape the local minimum. Once the local optimum is avoided, the algorithm switches back to APF to continue the path planning process. simulation results demonstrate that the proposed improved APF-SA algorithm adapts effectively to various complex environments, achieving shorter planning times and higher success rates compared to traditional APF and SA algorithms. It successfully resolves the unreachable target and local minimum problems associated with APF. Finally, the feasibility of the proposed APF-SA fusion algorithm is validated through experiments conducted on an electric power operation robot experimental platform for distribution grid applications.

关键词： electric potential Adaptation models Force Distribution networks Simulated annealing Manipulators Path planning Planning Collision avoidance Robots

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A safety risk assessment method for TBM tunnel construction based on attribute interval identification theory

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Scientific Reports 2025年第1期15卷 1-16页

作者： Wang, Bo Li, Qikai Xu, Zefan Niu, Shibin Nie, Xiangtian School of Water Conservancy North China University of Water Resources and Electric Power Zhengzhou 450046 China School of Management and Economlcs North China University of Water Resources and Electric Power Zhengzhou 450046 China Collaborative Innovation Center of Water Resources Efficient Utilization and Support Engineering Henan Province Zhengzhou 450046 China Henan Key Laboratory of Water Environment Simulation and Treatment Zhengzhou 450046 China

Based on the identification and analysis of safety risks in TBM tunnel construction, we construct a comprehensive safety risk dynamic evaluation index system tailored to this context. To account for the dynamic nature of safety risks during TBM tunnel construction, variable weight theory is incorporated, allowing for a more accurate reflection of the time-varying importance of risk indicators. Building on the theoretical framework of attribute interval recognition theory, we establish a TBM tunnel construction safety risk evaluation model grounded in attribute interval theory. This model effectively addresses the various uncertainties inherent in the risk evaluation process for TBM tunnel construction. It determines the evaluation level and attribute intervals for each individual indicator, and subsequently calculates the interval values for both the individual indicators and the composite attribute. Finally, a case study demonstrates the model’s effectiveness and practical applicability. © The Author(s) 2025.

关键词： Attribute interval recognition Risk assessment TBM Variable weight theory

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Differential Feature Fusion and Gated Coordinate Attention Mechanism for Few-Shot Object Detection of electrical Equipment Images

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Journal of engineering 2025年第1期2025卷

作者： Wu, Junpeng Zhou, Zhi Xian, Ran Tao, XinGuang Liu, Yang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China School of Electrical Engineering Northeast Electric Power University Jilin China

The over-dependence on the amount of labelled images in the process of deep learning-based object detection of electrical equipment images leads to the consumption of manpower and material resources. To solve this problem, this paper proposes a few-shot detection method of electrical equipment based on a two-stage fine-tuning approach and the improved YOLOv7 framework. First, an improved gated coordinate information attention (GCA) is introduced into the backbone part to reduce the negative impact of irrelevant background information on feature extraction. Second, in the neck part, an adaptive spatial feature fusion with difference information (ASFFDI) network is designed to improve the multi-scale feature extraction ability. Finally, the optimised α-SIoU loss function is used to improve the performance of the model. In addition, the two-stage fine-tuning training approach (TFA) is applied to the improved YOLOv7 model. The experimental results show that the average accuracy of the proposed method reaches 33.0%, 45.7% and 65.2%, respectively in 3 way-10 shot, 3 way-20 shot and 3 way-30 shot, which can realise few-shot detection of electrical equipment images. © 2025 The Author(s). The Journal of engineering published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： electric appliances

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control of Virtual Synchronous Generator for Frequency Regulation Using a Coordinated Self-adaptive Method

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CSEE Journal of power and Energy Systems 2024年第1期10卷 175-184页

作者： Hongwei Fang Zhiwei Yu School of Electrical and Information Engineering and Key Laboratory of Tianjin Electric Power System Simulation and Control Tianjin UniversityTianjin 300072China

power inverter adopting virtual synchronous generator(VSG)control can provide inertia support for distributed generation ***,it cannot take into account the dynamic regulation characteristics of ***,when the system encounters a sudden change in load or disturbance,the dynamic process of frequency regulation will be greatly *** view of this issue,an improved VSG control strategy based on a coordinated self-adaptive(CSA)method is *** time domain analysis method is used to study the influences of virtual inertia and damping parameter perturbation on the system steady and dynamic ***,in order to make the control strategy suitable for large load changes and suppress frequency variations beyond the limit,the secondary frequency modulation is introduced into the control *** the coordinated adaptive control of virtual inertia,virtual damping and frequency modulation,the dynamic performance of vSG frequency regulation can be obviously *** and experiment results have verified the effectiveness of the proposed CSA control strategy.

关键词： Coordinated self-adaptive method frequency regulation time domain analysis virtual synchronous generator

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Continuous Attribute Reduction Method Based on an Automatic Clustering Algorithm and Decision Entropy 36

Continuous Attribute Reduction Method Based on an Automatic ...

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第36届中国控制会议

作者： Hairong Sun Rui Wang Bixia Xie Yao Tian School of Control and Computer Engineering North China Electric Power University Hebei Engineering Research Center of Simulation & Optimized Control for Power Generation

ISBN: (纸本)9781538629185

The data in the process of power plant are mostly *** at the problems existing in the discretization of the continuous attributes with associated relationship,a strategy combining k-means clustering algorithm and the degree of compatibility of the decision table was *** degree of compatibility was taken as judgment conditions to determine whether a new cluster type is added,while ensuring that the degree of compatibility can be *** method take full account of the relationship among *** automatic clustering is realized when discretizing the continuous attributes,which makes the clustering results effective and *** attribute reduction algorithm based on approximate decision entropy is used to extract the main relations of the system,and the dimensionality of the data set can be effectively *** improved scheme is applied to continuous data of main steam temperature system of thermal power plant,and the validity of the method is verified.

关键词： Automatic clustering Continuous attribute Attribute reduction Decision Entropy Degree of compatibility

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Study on Fuzzy control of Circulating Fluidized Bed Temperature 3

Study on Fuzzy Control of Circulating Fluidized Bed Temperat...

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2017 3rd IEEE International Conference on control Science and Systems engineering (ICCSSE)

作者： Hai Rong Sun Peng Sun School of Control and Computer Engineering North China Electric Power University Hebei Engineering Research Center of Simulation & Optimized Control for Power Generation

ISBN: (纸本)9781538604854

As the pollution of the modern society, the circulating fluidized bed boiler, typical of new type, efficiency and low pollution, is booming. Nevertheless, its combustion process is more sophisticated than the common one. As that, it is difficult to build an accurate digital model. As the control effect, the traditional PID is less easy to be effective. The bed temperature is an important parameter in the operation of the circulating fluidized bed boiler, and is the key to the failurefree operation. The fuzzy controller was designed to the bed temperature and was proofed through the simulation experiment of the Matlab. The result has demonstrated that for the control of the sophisticated system, fuzzy control is the best way to achieve the intended goal, compared with the PID the common one.

关键词： circulating fluidized bed bed temperature fuzzy controller

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Optimal Configuration Planning of Multi-energy Microgrid Based on Source-load-temperature Scenarios Deep Joint Generation

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CSEE Journal of power and Energy Systems 2023年第3期9卷 1090-1102页

作者： Nantian Huang Wenting Wang Guowei Cai School of Electrical Engineering Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Northeast Electric Power University)Jilin 132012China

An optimal configuration method of a multi-energy microgrid system based on the deep joint generation of sourceload-temperature scenarios is proposed to improve the multienergy complementation and the reliability of energy supply in extreme ***,based on the historical meteorological data,the typical meteorological clusters and extreme temperature types are ***,to reflect the uncertainty of energy consumption and renewable energy output in different weather types,a deep joint generation model using a radiation-electric load-temperature scenario based on a denoising variational autoencoder is established for each weather *** the same time,to cover the potential high energy consumption scenarios with extreme temperatures,the extreme scenarios with fewer data samples are ***,the scenarios are reduced by clustering *** normal days of different typical scenarios and extreme temperature scenarios are determined,and the cooling and heating loads are determined by ***,the optimal configuration of a multi-energy microgrid system is carried *** show that the optimal configuration based on the extreme scenarios and typical scenarios can improve the power supply reliability of the *** proposed method can accurately capture the complementary potential of energy *** the economy of the system configuration is improved by 14.56%.

关键词： Deep joint generation denoising variational autoencoders multi-energy microgrid system optimal configuration planning

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A Trust-Based Personalized Differential Privacy Guarantees for Online Social Networks

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IEEE Transactions on Network and Service Management 2025年

作者： Chen, Jiajun Hu, Chunqiang Sheng, Weihong Li, Ruinian Zhao, Ruifeng Yu, Jiguo Chongqing University College of Computer Science Chongqing401331 China Chongqing University School of Big Data and Software Engineering Chongqing401331 China Bowling Green State University Computer Science Department United States Electric Power Dispatching and Control Center of Guangdong Power Grid Co. Ltd Guangzhou China University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu611731 China Qilu University of Technology Big Data Institute Jinan250353 China

Online social networks have emerged as a significant data source, but the extensive collection and utilization of personal information have given rise to profound concerns regarding privacy. From a legislative and policy perspective, and in alignment with the concept of privacy as control, users have the right to control their personal privacy information. However, users often encounter challenges in terms of understanding and effectively managing their privacy settings to align with their specific privacy requirements. To address this issue, in this paper, we incorporate the concept of trust and propose a trust-based personalized differential privacy model for online social networks, denoted as TPDP, which relies on a trusted central server to facilitate its operation. Specifically, when a user requests access to another user's personal information, the TPDP mechanism provides a privacy response, where the privacy level is determined based on the direct and indirect trust values among users, calculated automatically by the trusted central server. Furthermore, the proposed TPDP model offers user-to-user personalized differential privacy protection from the perspectives of network structures, trust-related factors, and trust propagation patterns. Finally, we validate the model's feasibility and assess the privacy-utility trade-off, as well as its robustness against attacks, through theoretical analysis and performance evaluation. © 2004-2012 IEEE.

关键词： Differential privacy

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Integrated energy microgrid bi-level game scheduling optimization taking into account electricity-heat-hydrogen enriched compressed natural gas coupling and shared energy storage

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International Journal of electrical power & Energy Systems 2025年 169卷

作者： Changgang Wang Xiaoning Sun Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China School of Electrical Engineering Northeast Electric Power University Jilin 132012 China

Hydrogen-enriched compressed natural gas (HCNG) is a promising technology capable of significantly reducing carbon emissions in conventional gas units. Its integration into microgrids enhances the coupling and complementarity of diverse energy sources. Shared energy storage systems, which play a crucial role in improving energy utilization, have garnered increasing attention in recent research. However, the deployment of HCNG technology involves multiple stakeholders, posing challenges in balancing their respective benefits. To address this, we propose a novel scheduling method for Integrated Energy Management that accounts for electricity-heat-HCNG coupling and shared energy storage services. First, we model the proton exchange membrane electrolyzer and HCNG energy coupling device, incorporating HCNG loads on the demand side to enhance hydrogen production and utilization efficiency. Additionally, tiered carbon trading mechanisms, integrated demand response strategies, and shared energy storage are introduced to optimize carbon reduction on both the demand and storage sides while effectively constraining energy emissions. The strategic interactions between integrated energy microgrid operators and load aggregators are modeled using a Stackelberg game approach, and the existence and uniqueness of equilibrium solutions are rigorously proven. Finally, the proposed model is solved using the Black-winged Kite algorithm in conjunction with the CPLEX *** studies demonstrate the effectiveness of the proposed method, showing revenue increases of 9.15% for integrated energy microgrid operators and 8.29% for load aggregators, alongside a reduction in carbon emissions by 8.76%.

关键词： Integrated energy microgrid HCNG Stackelberg game Carbon trading Demand respond

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