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6th International Conference on Energy, Electrical and Power Engineering, CEEPE 2023

作者： Ge, Junyu Yu, Dayang Wang, Mingqiang Liang, Caishuai Key Laboratory of Power System Intelligent Dispatch and Control Jinan China

ISBN: (纸本)9798350348279

There is a significant gap between the academic research and practical application of urban distribution network planning. In general, the distribution network planning in academic research does not consider the impact of real street layout on planning, which makes most distribution network models difficult to apply in practice. In addition, the planning of substations and feeders in urban distribution network planning is often carried out separately, which often leads to suboptimal planning results. The objective function that is often used in academia is also difficult to meet the needs of field planners. Aiming at the above problems, this paper proposes a joint planning model of substations and feeders in urban distribution network considering real street layout, fully considers the influence of real street layout on feeders and substations planning. The model uses the minimum load moment as the objective function and further improves it. The proposed model is recast as a mixed integer linear programming (MILP) problem, and it can be solved by the state-of-art commercial solver. The effectiveness and validity of the proposed model are illustrated on a 16-block test system. © 2023 IEEE.

关键词： Electric substations

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A Hierarchical controller for Connected Truck Platoon: Analysis and Verification

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IEEE Transactions on intelligent Transportation systems 2025年第6期26卷 7465-7475页

作者： Li, Yongfu Fan, Junhong Huang, Longwang Huang, Gang Hua, Wei Wu, Wei Yu, Shuyou Shi, Shuming Gao, Xinbo Chongqing University of Posts and Telecommunications Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing School of Automation Chongqing400065 China Zhejiang University School of Electrical Engineering Hangzhou310027 China Zhejiang Lab Hangzhou311121 China Chongqing Jiaotong University Chongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation System Chongqing400074 China Changsha University of Science and Technology School of Traffic and Transportation Engineering Changsha410114 China Jilin University Department of Control Science and Engineering Changchun130012 China Jilin University Transportation College Changchun130012 China

This paper proposes a novel hierarchical controller for connected truck platoons. To this end, the predecessor following topology is used to characterize the communication connectivity between connected trucks. Then, a longitudinal efficient controller consisting of upper-level and lower-level controllers is proposed. In particular, the upper-level controller is designed based on the kinematic model to handle the car-following interactions between connected trucks and delays in communication and input. The lower-level controller comprises a feedforward and a feedback control law. The feedforward control law converts the desired acceleration from the upper-level controller into the vehicle throttle or braking pressure using the inverse dynamic model, while the feedback control law compensates for the control error caused by unknown vehicle parameters. In addition, in the linear region, the internal stability is analyzed based on the second-order kinematic model using s-domain analysis and linearization method, respectively. Then, the string stability is proved. The influence of parameters on the stability performance is extensively discussed using the stability diagram. Finally, the feasibility of the proposed controller is verified via co-simulations in PreScan and TruckSim, in terms of acceleration, velocity, and spacing error profiles. © 2025 IEEE.

关键词： Feedback control

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system Strength Assessment Based on Multi-task Learning

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CSEE Journal of Power and Energy systems 2024年第1期10卷 41-50页

作者： Baoluo Li Shiyun Xu Huadong Sun Zonghan Li Lin Yu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250014China China Electric Power Research Institute Beijing 100192China

Increase in permeability of renewable energy sources(RESs)leads to the prominent problem of voltage stability in power system,so it is urgent to have a system strength evaluation method with both accuracy and practicability to control its access scale within a reasonable ***,a hybrid intelligence enhancement method is proposed by combining the advantages of mechanism method and data driven ***,calculation of critical short circuit ratio(CSCR)is set as the direction of intelligent enhancement by taking the multiple renewable energy station short circuit ratio as the quantitative ***,the construction process of CSCR dataset is proposed,and a batch simulation program of samples is developed accordingly,which provides a data basis for subsequent ***,a multi-task learning model based on progressive layered extraction is used to simultaneously predict CSCR of each RESs connection point,which significantly reduces evaluation error caused by weak *** performance and anti-noise performance of the proposed method are verified on the CEPRI-FS-102 bus system,which provides strong technical support for real-time monitoring of system strength.

关键词： Critical short circuit ratio hybrid intelligence enhancement multi-task learning system strength

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Multiplexed model predictive attitude control for nadir-pointing satellite using only magnetorquers

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control Engineering Practice 2025年 162卷

作者： Yang, Sen Ling, Keck Voon Wang, Zhenhua Li, Huiping School of Astronautic Harbin Institute of Technology Harbin150001 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150001 China School of Marine Science and Technology Northwestern Polytechnical University Xi'an710072 China

Due to the low failure risk of magnetorquers, the control strategy based on magnetic actuators can significantly enhance the reliability of the satellite attitude control system. In light of this advantage, this paper conducts research on model predictive control (MPC) algorithm for nadir-pointing satellites equipped only with magnetorquers. Firstly, to facilitate controller design, the linear time-varying (LTV) model for nadir-pointing satellites is derived by linearizing the nonlinear equations around the operating point. Then, leveraging this linearized representation, an LTV multiplexed MPC (MMPC) method with exponential weighting is proposed. The MMPC scheme allows for faster sampling rates and quicker responses to disturbances, thereby enhancing the overall performance of the satellite attitude control system while retaining the benefits of MPC. Finally, compared with a state-of-the-art SMPC method, the proposed method is particularly advantageous in situations where computational resources are limited, specifically for satellites that rely only on onboard computing capabilities. © 2025

关键词： Nonlinear equations

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Multi-stage Provincial Power Expansion Planning and Multi-market Trading Equilibrium

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Journal of Modern Power systems and Clean Energy 2024年第5期12卷 1652-1665页

作者： Guangsheng Pan Zhongfan Gu Yuanyuan Sun Kaiqi Sun Wei Gu the School of Electrical Engineering Southeast UniversityNanjingChina Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education School of Electrical EngineeringShandong UniversityJinanChina

Decarbonization in the power sector is one of the critical factors in achieving carbon neutrality,and the top-level design needs to be carried out from the perspective of power planning.A multi-stage provincial power expansion planning(PPEP)model is proposed to simulate the power expansion planning at different stages of the power systems rich in renewable energy *** model covers 16 types of power supply,considering macro-policy demands and micro-operation *** stand-alone capacity aggregation model for coal-based units within the PPEP model allows for accurate construction and retirement with different stand-alone ***,the soft dynamic time warping(soft-DTW)based K-medoids technique is adopted to generate typical scenarios for balancing the model accuracy and solution ***,a multi-market trading equilibrium(MMTE)mechanism is proposed to address the differences in the levelized cost of energy between the coal-based and renewable-based units by participating in energy and ancillary service *** the coalbased units take on the task of providing ancillary services from renewable-based units in the ancillary service market,the MMTE mechanism can effectively equalize the profits of both by having renewable-based units purchase ancillary services from coal-based units and pay for them,thus improving the motivation of coal-based units.A case study in Xinjiang province,China,verifies the effectiveness of the planning results of the PPEP model and the profit equilibrium realization of the MMTE mechanism.

关键词： Power expansion planning market design ancillary service market renewable energy generation energy market

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Multi-stage Dynamic Post-disaster Recovery Strategy for Distribution Networks Considering Integrated Energy and Transportation Networks

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CSEE Journal of Power and Energy systems 2021年第2期7卷 408-420页

作者： Xinyi Jiang Jian Chen Ming Chen Zhen Wei Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250061China State Grid Qingdao Power Supply Company Qingdao 266002China

To improve the resilience of distribution networks(DNs),a multi-stage dynamic recovery strategy is proposed in this paper,which is designed for post-disaster DN considering an integrated energy system(IES)and transportation network(TN).First,the emergency response quickly increases the output of gas turbines(GTs)in the natural gas network(NGN),and responsively reconfigures the DN in microgrids,to maximize the amount of loads to be *** single-commodity flow model is adopted to construct spanning tree ***,in the second stage of energy storage recovery,mobile energy storage systems(MESSs)are deployed to cover the shortages of power demands,i.e.,to further restore the loads after evaluating the load recovery *** Floyd algorithm based dynamic traffic assignment(DTA)is selected to obtain the optimal path of the *** the third stage,the outputs of various post-disaster recovery measures are adjusted to achieve an economically optimized *** studies demonstrate the effectiveness of the proposed dynamic post-disaster recovery strategy.

关键词： Dynamic post-disaster recovery dynamic transportation network integrated energy system resilience distribution

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Distributionally Robust Transmission Expansion Planning Considering Uncertainty of Contingency Probability

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Journal of Modern Power systems and Clean Energy 2022年第4期10卷 894-901页

作者： Weilun Wang Mingqiang Wang Xueshan Han Ming Yang Qiuwei Wu Ran Li Key Laboratory of Power System Intelligent Dispatch and Control Ministry of EducationShandong UniversityJinan 250002China Department of Electrical Engineering Technical University of DenmarkRegion HovedstadenDenmark

The outage of power system equipment is one of the most important factors that affect the reliability and economy of power *** is crucial to consider the influence of contingencies elaborately in planning *** this paper,a distributionally robust transmission expansion planning model is proposed in which the uncertainty of contingency probability is *** uncertainty of contingency probability is described by uncertainty interval based on the outage rate of single *** epigraph reformulation and Benders decomposition are applied to solve the proposed ***,the feasibility and effectiveness of the proposed model are illustrated on the IEEE RTS system and the IEEE 118-bus system.

关键词： Benders decomposition distributionally robust equipment outage rate transmission expansion planning

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Safe RL-based Adaptive Cooperative Game control of Wing Deformation and Flight State Tracking for Morphing Hypersonic Vehicles

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Wang, Jun-Wei Wang, Feng Wu, Huai-Ning Liu, Zhou-Yang University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Hangzhou International Innovation Institute Hangzhou311115 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

This study addresses the issue of adaptive cooperative game control (ACGC) design for wing deformation and flight state tracking of morphing hypersonic vehicles (MHVs) with variable wing shapes, input constraints and state constraints. To access a better flight control performance, the wing deformation parameter is extended in this work as an auxiliary control input. An oriented-coordinated-control nonlinear differential equation model is first established to describe the complicated longitudinal flight state tracking error dynamics of the MHV. Then, a control barrier function (CBF) is introduced and incorporated into the value function as a risk penalty term of state security constraint. Based on the differential game (DG) theory, the optimal coordinated control problem for the MHV with input constraints and state constraints is treated as a constrained cooperative DG that is further formulated as a Hamilton-Jacobi-Bellman (HJB) equation with barrier and hyperbolic functions. A safe RL algorithm is proposed to solve the above HJB equation and an online Pareto joint control strategy is achieved thereby. Hereafter the stability analysis of the closed-loop state tracking error system is done by the Lyapunov technique. Meanwhile, both state and input constraints are met during the the parameter learning regulation process. At last, a simulation study is performed to support the proposed safe RL-ACGC algorithm. © 2025 IEEE.

关键词： Hyperbolic functions

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Exact Soft-Covering Exponent

Exact Soft-Covering Exponent

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IEEE International Symposium on Information Theory (ISIT)

作者： Yagli, Semih Cuff, Paul Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Ministry of Education Jinan China

ISBN: (纸本)9781538647813

This work establishes the exact exponent for the soft-covering phenomenon of a memoryless channel under the total variation metric. The exponent, established herein, is a strict improvement (in both directions) on bounds found in the literature. This complements the recent literature establishing the exact exponent under the relative entropy metric;however, the proof techniques have significant differences, neither bound trivially implies the other. This result implies new and improved bounds for various problems that use soft-covering as their achievability argument, including new lower bounds for the resolvability exponent and the secrecy exponent in the wiretap channel.

关键词： Soft-covering lemma channel resolvability random coding exponent total variation distance

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Logistics Demand Forecasting and Scheduling Optimization Using K-Means Clustering and Deep Q-Network

Logistics Demand Forecasting and Scheduling Optimization Usi...

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Electronics, Energy systems and Power Engineering (EESPE), IEEE International Conference on

作者： Kun Liang Hang Zhang School of Management Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

With the rapid development of e-commerce and supply chain management, logistics demand forecasting and scheduling optimization have become key links in improving logistics efficiency and service quality. To meet this challenge, this paper proposes a logistics demand forecasting and scheduling optimization method that combines K-Means clustering with deep Q network (DQN). Cluster analysis is used to reduce data complexity, and deep reinforcement learning is used to achieve intelligent scheduling. First, the background, challenges and research motivation of logistics demand forecasting and scheduling optimization are introduced. Secondly, the research results in related fields are reviewed, and the shortcomings of current research are pointed out. Then, the K-Means clustering algorithm, deep $\mathbf{Q}$ network theory and specific models of logistics demand prediction and scheduling optimization are elaborated. Then, the performance of the proposed method is designed and tested. The experimental results show that the proposed method can significantly improve the accuracy of logistics demand prediction, up to 0.93, optimize scheduling strategies, reduce logistics costs, and improve customer satisfaction.

关键词： Training Accuracy Costs Computational modeling Customer satisfaction Demand forecasting Clustering algorithms Predictive models Scheduling Logistics

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