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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 981-990页

作者： Ning Li Yujie Cao Xiaokang Liu Yan Zhang Ruotong Wang Lin Jiang Xiao-Ping Zhang School of electrical engineering Xi'an University of Technology the department of Electronics Information and Bioengineering Xi'an Jiaotong University the department of electrical engineering and Electronics University of Liverpool the department of Electronic Electrical and Systems Engineering University of Birmingham

Two-level totem-pole power factor correction(PFC) converters in critical conduction mode(CRM) suffer from the wide regulation range of switching frequency. Besides, in highfrequency applications, the number of switching times increases, resulting in significant switching losses. To solve these issues, this paper proposes an improved modulation strategy for the single-phase three-level neutral-point-clamped(NPC) converter in CRM with PFC. By optimizing the discharging strategy and switching state sequence, the switching frequency and its variation range have been efficiently reduced. The detailed performance analysis is also presented regarding the switching frequency, the average switching times, and the effect of voltage gain. A 2 k W prototype is built to verify the effectiveness of the proposed modulation strategy and analysis results. Compared with the totem-pole PFC converter, the switching frequency regulation range of the three-level PFC converter is reduced by 36.48% and the average switching times is reduced by 45.10%. The experimental result also shows a 1.2% higher efficiency for the three-level PFC converter in the full load range.

关键词： Switches Switching frequency Control systems Topology Bridge circuits Inductors Customer relationship management

Asymmetrical Fault Current Calculation Method and Influencing Factors Analysis of Droop-Controlled Inverters

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 562-573页

作者： Huimin Zhao Zhikang Shuai Jun Ge An Luo Weimin Wu Z.John Shen College of electrical and information engineering Hunan UniversityChangsha 410006China electrical engineering department Shanghai Maritime UniversityShanghai 201306China department of electrical and Computer engineering Ilinois Institute of TechnologyChicagoIL 60616 USA

Since the fault dynamic of droop-controlled inverter is different from synchronous generators (SGs), protection devices may become invalid, and the fault overcurrent may damage power electronic devices and threaten the safety of the microgrid. Therefore, it is imperative to conduct a comprehensive fault analysis of the inverter to guide the design of protection schemes. However, due to the complexity of droop control strategy, existing literatures have simplified asymmetric fault analysis of droop-controlled inverters to varying degrees. Therefore, accurate fault analysis of a droop-controlled inverter is needed. In this paper, by analyzing the control system, an accurate fault model is established. Based on this, a calculation method for instantaneous asymmetrical fault current is proposed. In addition, the current components and current characteristics are analyzed. It was determined that fault currents are affected by control loops, fault types, fault distance and nonlinear limiters. In particular, the influences of limiters on the fault model, fault current calculation and fault current characteristics were analyzed. Through detailed analysis, it was found that dynamics of the control loop cannot be ignored, the fault type and fault distance determine fault current level, and part of the limiters will totally change the fault current trend. Finally, calculation and experimental results verify the correctness of the proposed method.

关键词： Asymmetrical fault analysis droop control fault current calculation method limiter transient fault characteristics

Multi-modal visual tracking:Review and experimental comparison

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Computational Visual Media 2024年第2期10卷 193-214页

作者： Pengyu Zhang Dong Wang Huchuan Lu Faculty of Electronic information and electrical engineering Dalian University of TechnologyDalian 116024Chin

Visual object tracking has been drawing increasing attention in recent years,as a fundamental task in computer vision.To extend the range of tracking applications,researchers have been introducing information from multiple modalities to handle specific scenes,with promising research prospects for emerging methods and benchmarks.To provide a thorough review of multi-modal tracking,different aspects of multi-modal tracking algorithms are summarized under a unified taxonomy,with specific focus on visibledepth(RGB-D)and visible-thermal(RGB-T)tracking.Subsequently,a detailed description of the related benchmarks and challenges is provided.Extensive experiments were conducted to analyze the effectiveness of trackers on five datasets:PTB,VOT19-RGBD,GTOT,RGBT234,and VOT19-RGBT.Finally,various future directions,including model design and dataset construction,are discussed from different perspectives for further research.

关键词： visual tracking object tracking multi-modal fusion RGB-T tracking RGB-D trackin

A study of novel real-time power balance strategy with virtual asynchronous machine control for regional integrated electric-thermal energy systems

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Science China Technological Sciences 2024年第7期67卷 2074-2086页

作者： WANG Rui LI Ming-Jia WANG YiBo SUN QiuYe ZHANG PinJia College of information Science and engineering Northeastern University School of Mechanical engineering Beijing Institute of Technology department of electrical engineering Tsinghua University

The development of regional integrated electric-thermal energy systems(RIETES) is considered a promising direction for modern energy supply systems. These systems provide a significant potential to enhance the comprehensive utilization and efficient management of energy resources. Therein, the real-time power balance between supply and demand has emerged as one pressing concern for system stability operation. However, current methods focus more on minute-level and hour-level power optimal scheduling methods applied in RIETES. To achieve real-time power balance, this paper proposes one virtual asynchronous machine(VAM) control using heat with large inertia and electricity with fast response speed. First, the coupling timescale model is developed that considers the dynamic response time scales of both electric and thermal energy systems. Second, a real-time power balance strategy based on VAM control can be adopted to the load power variation and enhance the dynamic frequency response. Then, an adaptive inertia control method based on temperature variation is proposed, and the unified expression is further established. In addition, the small-signal stability of the proposed control strategy is validated. Finally, the effectiveness of this control strategy is confirmed through MATLAB/Simulink and HIL(Hardware-in-the-Loop) experiments.

关键词： regional integrated electric-thermal energy systems real-time power balance virtual asynchronous machine adaptive inertia small-signal stability

Hybrid robust fault detection and isolation of satellite reaction wheel actuators

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Journal of Control and Decision 2024年第1期11卷 117-131页

作者： H.Abbasi Nozari S.J.Sadati Rostami Paolo Castaldi Silvio Simani Faculty of electrical and Computer engineering Babol Noshirvani University of TechnologyBabolIran department of electrical Electronic and Information EngineeringUniversity of BolognaCesenaItaly department of engineering University of FerraraFerraraItaly

In this paper,a combined robust fault detection and isolation scheme is studied for satellite system subject to actuator faults,external disturbances,and parametric uncertainties.The proposed methodology incorporates a residual generation module,including a bank of filters,into an intelligent residual evaluation module.First,residual filters are designed based on an improved nonlinear differential algebraic approach so that they are not affected by external disturbances.The residual evaluation module is developed based on the suggested series and parallel forms.Further,a new ensemble classification scheme defined as blended learning integrates heterogeneous classifiers to enhance the performance.A wide range of simulations is carried out in a high-fidelity satellite simulator subject to the constant and time-varying actuator faults in the presence of disturbances,manoeuvres,uncertainties,and noises.The obtained results demonstrate the effectiveness of the proposed robust fault detection and isolation method compared to the traditional nonlinear differential algebraic approach.

关键词： Robust fault detection and isolation reaction wheels blended learning series and parallel fault detection and isolation forms satellite attitude control system

Two simple memristive maps with adaptive energy regulation ano digital signal process verification

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Journal of Zhejiang University-Science A(Applied Physics & engineering) 2024年第5期25卷 382-394页

作者： Feifei YANG Lujie REN Jun MA Zhigang ZHU College of electrical and information engineering Lanzhou University of TechnologyLanzhou 730050China department of Physics Lanzhou University of TechnologyLanzhou 730050China School of information Science and engineering Dalian Polytechnic UniversityDalian 116034China

Mathematical models can produce desired dynamics and statistical properties with the insertion of suitable nonlinear terms,while energy characteristics are crucial for practical application because any hardware realizations of nonlinear systems are relative to energy flow.The involvement of memristive terms relative to memristors enables multistability and initial-dependent property in memristive systems.In this study,two kinds of memristors are used to couple a capacitor or an inductor,along with a nonlinear resistor,to build different neural circuits.The corresponding circuit equations are derived to develop two different types of memristive oscillators,which are further converted into two kinds of memristive maps after linear transformation.The Hamilton energy function for memristive oscillators is obtained by applying the Helmholz theorem or by mapping from the field energy of the memristive circuits.The Hamilton energy functions for both memristive maps are obtained by replacing the gains and discrete variables for the memristive oscillator with the corresponding parameters and variables.The two memristive maps have rich dynamic behaviors including coherence resonance under noisy excitation,and an adaptive growth law for parameters is presented to express the self-adaptive property of the memristive maps.A digital signal process(DSP)platform is used to verify these results.Our scheme will provide a theoretical basis and experimental guidance for oscillator-to-map transformation and discrete map-energy calculation.

关键词： Hamilton energy Discrete memristor Self-adaptive regulation Digital signal process(DSP)implementation

Generalized load graphical forecasting method based on modal decomposition

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Global Energy Interconnection 2024年第2期7卷 166-178页

作者： Lizhen Wu Peixin Chang Wei Chen Tingting Pei College of electrical and information engineering Lanzhou University of TechnologyLanzhou 730050P.R.China School of electrical Data engineering University of Technology SydneyNSW2007Australia

In a“low-carbon”context,the power load is affected by the coupling of multiple factors,which gradually evolves from the traditional“pure load”to the generalized load with the dual characteristics of“load+power supply.”Traditional time-series forecasting methods are no longer suitable owing to the complexity and uncertainty associated with generalized loads.From the perspective of image processing,this study proposes a graphical short-term prediction method for generalized loads based on modal decomposition.First,the datasets are normalized and feature-filtered by comparing the results of Xtreme gradient boosting,gradient boosted decision tree,and random forest algorithms.Subsequently,the generalized load data are decomposed into three sets of modalities by modal decomposition,and red,green,and blue(RGB)images are generated using them as the pixel values of the R,G,and B channels.The generated images are diversified,and an optimized DenseNet neural network was used for training and prediction.Finally,the base load,wind power,and photovoltaic power generation data are selected,and the characteristic curves of the generalized load scenarios under different permeabilities of wind power and photovoltaic power generation are obtained using the density-based spatial clustering of applications with noise algorithm.Based on the proposed graphical forecasting method,the feasibility of the generalized load graphical forecasting method is verified by comparing it with the traditional time-series forecasting method.

关键词： Load forecasting Generalized load Image processing DenseNet Modal decomposition

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Data-driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 874-885页

作者： Wenlong Liao Dechang Yang Qi Liu Yixiong Jia Chenxi Wang Zhe Yang Wind engineering and Renewable Energy Laboratory Ecole Polytechnique Federale de Lausanne (EPFL) the College of information and electrical engineering China Agricultural University the College of electrical engineering and Automation Shandong University of Science and Technology the department of electrical and Electronic engineering (Energy Digitalization Laboratory) The University of Hong Kong the department of electrical engineering The Hong Kong Polytechnic University

Reactive power optimization of distribution networks is traditionally addressed by physical model based methods, which often lead to locally optimal solutions and require heavy online inference time consumption. To improve the quality of the solution and reduce the inference time burden, this paper proposes a new graph attention networks based method to directly map the complex nonlinear relationship between graphs(topology and power loads) and reactive power scheduling schemes of distribution networks, from a data-driven perspective. The graph attention network is tailored specifically to this problem and incorporates several innovative features such as a self-loop in the adjacency matrix, a customized loss function, and the use of max-pooling layers. Additionally, a rulebased strategy is proposed to adjust infeasible solutions that violate constraints. Simulation results on multiple distribution networks demonstrate that the proposed method outperforms other machine learning based methods in terms of the solution quality and robustness to varying load conditions. Moreover, its online inference time is significantly faster than traditional physical model based methods, particularly for large-scale distribution networks.

关键词： Distribution networks Reactive power Load modeling Transformers Machine learning algorithms Inference algorithms Static VAr compensators

Learning-based user association and dynamic resource allocation in multi-connectivity enabled unmanned aerial vehicle networks

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Digital Communications and Networks 2024年第1期10卷 53-62页

作者： Zhipeng Cheng Minghui Liwang Ning Chen Lianfen Huang Nadra Guizani Xiaojiang Du department of information and Communication engineering Xiamen UniversityXiamen361005China School of electrical and Computer engineering University of Texas at ArlingtonArlingtonTX7619USA department of electrical and Computer engineering Stevens Institute of TechnologyHobokenNJ07030USA

Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G.Besides,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective solutions.To this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground users.The goal was to mitigate co-channel interference while maximizing long-term system utility.The problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this problem.Extensive simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.

关键词： UAV-user association Multi-connectivity Resource allocation Power control Multi-agent deep reinforcement learning

An Optimization Model for Reliability Improvement and Cost Reduction Through EV Smart Charging

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 608-620页

作者： Jinping Zhao Ali Arefi Alberto Borghetti Gerard Ledwich School of engineering and Energy Murdoch UniversityPerthAustralia department of electrical Electronicand Information EngineeringUniversity of BolognaBologna40126Italy School of electrical engineering and Robotics Queensland University of TechnologyBrisbaneQLD 4000Australia

There is a general concern that the increasing penetration of electric vehicles(EVs)will result in higher aging failure probability of equipment and reduced network reliability.The electricity costs may also increase,due to the exacerbation of peak load led by uncontrolled EV charging.This paper proposes a linear optimization model for the assessment of the benefits of EV smart charging on both network reliability improvement and electricity cost reduction.The objective of the proposed model is the cost minimization,including the loss of load,repair costs due to aging failures,and EV charging expenses.The proposed model incorporates a piecewise linear model representation for the failure probability distributions and utilizes a machine learning approach to represent the EV charging load.Considering two different test systems(a 5-bus network and the IEEE 33-bus network),this paper compares aging failure probabilities,service unavailability,expected energy not supplied,and total costs in various scenarios with and without the implementation of EV smart charging.

关键词： Aging failure electric vehicle(EV) EV charging power system reliability expected energy not supplied distribution network.

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