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42nd Chinese control Conference, CCC 2023

作者： Dou, Lintao Wei, Haoyu Huang, Jian Pan, Lulu Shao, Haibin Li, Dewei College of Intelligent Science National University of Defense Technology Changsha410003 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581543

This paper examines the event-triggered consensus of the multi-agent system on matrix-weighted networks, where the interdependencies among higher-dimensional states of neighboring agents are characterized by matrix-weighted edges in the network. Specifically, a novel distributed dynamic event-triggered coordination strategy is proposed for this category of generalized networks, in which an auxiliary system is employed for each agent to dynamically adjust the triggering threshold, which plays an essential role in guaranteeing that the triggering time sequence does not exhibit Zeno behavior. Distributed event-triggered control protocols are proposed to guarantee leaderless consensus for multi-agent systems on matrix-weighted networks, respectively. Remarkably, the spectrum of matrix-valued weights is crucial in event-triggered mechanism design for matrix-weighted networks, generalizing those results only applicable for scalar-weighted networks. The proposed approach allows each agent to broadcast and receive information only at its triggering instants. Finally, simulation examples are provided to demonstrate the theoretical results. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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Effect of Battery Energy Storage system Frequency Regulation on Frequency Characteristic of Power systems

Effect of Battery Energy Storage System Frequency Regulation...

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2022 IEEE International Conference on Power systems and Electrical Technology, PSET 2022

作者： Deng, Lijun Huang, Libin Cai, Haiqing Hu, Yun Liao, Mengjun Huang, Yunhui China Southern Power Grid Research Institute Co. Ltd Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Wuhan University of Technology Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Wuhan China

ISBN: (纸本)9781665489157

This paper investigates the impact of battery energy storage system (BESS) frequency regulation on frequency characteristic of power systems. To begin with, a model of BESS participating in frequency regulation of power systems is established for analyzing effects of BESS control dynamics on grid frequency characteristic. And the analysis model is proved by comparison with time domain model. Furthermore, grid frequency characteristic analysis with including BESS frequency regulation is studied. Virtual inertia control and virtual inertia frequency control of BESS are investigated for Participate in power grid frequency regulation. Finally, Influence of energy storage inertia and primary frequency regulation control on system frequency characteristics are investigated in Matlab/Simulink. © 2022 IEEE.

关键词： Battery storage

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Application of deep reinforcement learning in power system scheduling strategy simulation 4

Application of deep reinforcement learning in power system s...

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4th International Conference on Energy, Power and Electrical Engineering, EPEE 2024

作者： Hu, Binjiang Huang, Libin Hu, Yufeng Zhang, Jie Guo, Haiping Lu, Yuanhong Hong, Zeqi Zhang, Jingyue Luo, Hui Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Electric Power Research Institute China Southern Power Grid State Key Laboratory of Hvdc Guangzhou China National Energy Power Grid Technology R&d Centre Guangzhou China Electric Power Research Institute China Southern Power Grid Csg Key Laboratory for Power System Simulation Guangzhou China

ISBN: (纸本)9798331518066

With the increasing scale and complexity of power system, the current scheduling strategy methods often have the problems of limited adaptability and unsatisfactory results. Therefore, a power system scheduling method using DQN (Deep Q Network) is introduced in this study. This method uses neural network model to learn and optimize scheduling strategy, and has strong adaptability and enhanced global optimization ability. Comparative evaluations with genetic algorithms and particle swarm algorithms on IEEE-118 and SG-126 datasets show that the proposed method has significant advantages in terms of cumulative reward and stable runtime. © 2024 IEEE.

关键词： Deep reinforcement learning

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Design and Implementation of Power system Simulation Platform Based on Cloud Computing 4

Design and Implementation of Power System Simulation Platfor...

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4th International Conference on Energy, Power and Electrical Engineering, EPEE 2024

作者： Lu, Yuanhong Guo, Haiping Zhao, Yanjun Huang, Libin Hu, Binjiang Luo, Hui Zhang, Jingyue National Energy Power Grid Technology R&d Centre Guangzhou China State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798331518066

Power system simulation involves simulating the operating states and dynamic processes of power systems using mathematical models and computer technology to analyze and predict system behavior. Traditional simulation methods struggle to meet the needs of large-scale, complex power grids due to significant demands for computational resources. Cloud computing, with its high scalability, resource pooling, and on-demand services, is ideally suited for the extensive simulation calculations required by modern power systems. Despite its advantages, the application of cloud computing in power system simulation poses challenges related to data security and privacy, particularly in collaborative simulations involving multiple power entities. This paper presents the design and implementation of a cloud computing-based power system simulation platform. The proposed platform leverages the distributed computing capabilities of cloud computing, integrates federated learning to ensure data privacy, and utilizes advanced power system simulation technologies. This approach significantly enhances simulation efficiency and accuracy while providing data security and privacy protection. The platform offers reliable decision support for power system planning, operation, and control. © 2024 IEEE.

关键词： Cloud platforms

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Human Reliability Analysis of Professional Theater Based on CREAM

Human Reliability Analysis of Professional Theater Based on ...

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Culture-Oriented Science and Technology (CoST), International Conference on

作者： Huiqin Wang Huiqi Wang Hui Ren Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

In the context of human/equipment interaction processes, human error has become a significant factor influencing performance risk in professional theaters. To address this issue, the Cognitive Reliability and Error Analysis Method (CREAM) is integrated with fuzzy inference to assess the human reliability of theater staff and predict the probability of human error (HEP). Additionally, Grey Relational Analysis (GRA) is introduced to determine the weights of Common Performance Conditions (CPCs) within CREAM. Through this methodological framework, human reliability analysis of theater operators is conducted, enabling the prediction of human error rates across various scenarios. Subsequently, corresponding measures are provided, culminating in an effective solution to enhance performance safety within theatrical environments.

关键词： Fuzzy logic Costs Error analysis Error probability Measurement uncertainty Safety management Lighting

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Collaborative Mission Planning for UAV Swarms Launched from Aerial Carriers

Collaborative Mission Planning for UAV Swarms Launched from...

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International Conference on Guidance, Navigation and control, ICGNC 2024

作者： Yuan, Mingzhou Dong, Bo Yao, Weiran School of Astronautics Harbin Institute of Technology Harbin150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China Beijing100043 China

ISBN: (纸本)9789819622115

This paper takes the aerial carriers to launch UAV swarms as the background, aims to minimize the total flight distance of the UAV swarms, and proposes a clustering-launching-planning solution framework. Aiming at the scenario where UAVs adopt Dubins curve trajectories, a Dubins-KMeans clustering algorithm based on the Dubins curve length as the similarity measure is proposed. To ensure the shortest distance for air carriers to traverse each cluster, a two-part genetic algorithm is used to solve this MTSP problem and find the optimal order for air carriers to traverse each cluster. Ultimately, the energy efficiency of the entire unmanned system is optimized. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Genetic algorithms

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Smooth quadrotor trajectory generation for tracking a moving target in cluttered environments

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Science China(Information Sciences) 2021年第7期64卷 132-147页

作者： Lele XI Zhihong PENG Lei JIAO Ben M.CHEN School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Peng Cheng Laboratory Department of Mechanical and Automation Engineering The Chinese University of Hong Kong

In this paper, we present a trajectory generation method of a quadrotor, based on the optimal smoothing B-spline, for tracking a moving target with consideration of relative tracking pattern or limited field of view of the onboard sensor in cluttered environments. Compared to existing methods, safe flying zone,vehicle physical limits, and smoothness are fully considered to guarantee flight safety, kinodynamic feasibility, and tracking performance. To tackle the cluttered environments, a parallel particle swarm optimization algorithm is applied to find the feasible waypoints that the generated trajectory should be as close to as possible, with consideration of the target's future state as well as obstacles to trade off the tracking performance and flight safety. Then, a sequential motion planning method, considering the above constraints, is applied and embedded into a cost function for solving the problem of robust tracking trajectory generation for the quadrotor via a convex optimization approach. The feasibility and effectiveness of the proposed method are verified by numerical simulations.

关键词： quadrotor target tracking trajectory generation B-spline convex optimization

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An Adaptive Physics-Informed Neural Network with Two-Stage Learning Strategy to Solve Partial Differential Equations

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Numerical Mathematics(Theory,Methods and Applications) 2023年第2期16卷 298-322页

作者： Shuyan Shi Ding Liu Ruirui Ji Yuchao Han School of Automation and Information Engineering Xi‘an University of TechnologyXi‘an 710048P.R.China National&Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi‘an 710048P.R.China Xi’an University of Technology Shannxi Key Laboratory of Complex System Control and Intelligent Information ProcessingXi‘an 710048P.R.China

Physics-Informed Neural Network(PINN)represents a new approach to solve Partial Differential Equations(PDEs).PINNs aim to solve PDEs by integrating governing equations and the initial/boundary conditions(I/BCs)into a loss ***,the imbalance of the loss function caused by parameter settings usually makes it difficult for PINNs to converge,*** they fall into local *** other words,the presence of balanced PDE loss,initial loss and boundary loss may be critical for the *** addition,existing PINNs are not able to reveal the hidden errors caused by non-convergent boundaries and conduction errors caused by the PDE near the ***,these problems have made PINN-based methods of limited use on practical *** this paper,we propose a novel physics-informed neural network,*** adaptive physics-informed neural network with a two-stage training *** algorithm adds spatio-temporal coefficient and PDE balance parameter to the loss function,and solve PDEs using a two-stage training process:pre-training and formal *** pre-training step ensures the convergence of boundary loss,whereas the formal training process completes the solution of PDE by balancing various loss *** order to verify the performance of our method,we consider the imbalanced heat conduction and Helmholtz equations often appearing in practical *** Klein-Gordon equation,which is widely used to compare performance,reveals that our method is able to reduce the hidden *** results confirm that our algorithm can effectively and accurately solve models with unbalanced loss function,hidden errors and conduction *** codes developed in this manuscript are publicy available at https://***/callmedrcom/ATPINN.

关键词： Physics informed neural networks partial differential equations two-stage learning scientific computing

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Preventive control Method of Improving Transient Voltage Stability for Power system Based on the Attention of CNN

Preventive Control Method of Improving Transient Voltage Sta...

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Sustainable Power and Energy Conference (iSPEC)

作者： Zhendong Li Jiongcheng Yan Yutian Liu Li Li Hanbing Qu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Jinan Power Supply Company Jinan China

The widespread integration of renewable generation and the changes in load structure bring significant challenges to the transient voltage stability of large-scale power systems. In order to achieve fast decision of preventive control for improving transient voltage stability, this paper proposes a preventive control method based on the attention of Convolutional Neural Network (CNN). An optimization decision model is established, which not only considers multiple traditional constraints but also introduces the model attention indicator based on Gradient-weighted Class Activation Mapping (Grad-CAM), enabling a more targeted improvement of transient voltage stability. The proposed indicator is capable of extracting the knowledge learned by CNN-based transient voltage assessment model, and utilizing it to guide the optimization decision-making of preventive control. Simulation results of provincial grid of eastern China demonstrate that the optimized control scheme can effectively enhance the transient voltage stability of power systems.

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Longitudinal Comparison Protection Method for AC/DC Hybrid Distribution Network Based on Waveform Similarity

Longitudinal Comparison Protection Method for AC/DC Hybrid D...

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International Conference on Power system Technology (POWERCON)

作者： Zhengfei Lu Wei Cong Anlong Zhang Yingqi Huang Yu Zhou Zeqian Wang Shenzhen Power Supply Company China Southern Power Grid Shenzhen China Key Laboratory of Power System Intelligent Dispatch and Control(Shandong University) Jinan China

With the maturity of DC transmission and distribution technology, the future distribution network will gradually develop in the direction of AC/DC hybrid distribution network (AC/DC-HDN). The unique fault coupling characteristics of AC/DC-HDN challenge the adaptability of protection methods. Based on the analysis of the fault coupling characteristics of AC/DC-HDN, this paper proposes a longitudinal comparison protection method for AC/DC-HDN based on waveform similarity. The method chiefly employs electrical quantity of the measurement point to calculate reference voltage of the corresponding reference point. Determine whether the fault location is located between measurement point and reference point or outside by determining whether the wave-form of the measured voltage is similar to that of the reference voltage or not. The longitudinal protection makes a decision on whether the fault occurs internal or external by comparing the results. Finally, the correctness of this protection method was verified by setting different location faults in PSCAD. The method can accurately determine whether the fault occurs internal or external, has a certain resistance to transition resistance, is not affected by unmeasurable load branches, and has good coping ability for calculation errors caused by noise interference.

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