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Transient Stability Analysis of Converter-based Islanded Microgrids Based on Iterative Equal Area Criterion Considering Reactive Power Loop Dynamics and Varying Damping

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Journal of Modern Power systems and Clean Energy 2024年第4期12卷 1170-1182页

作者： Xilin Li Jingyi Zhang Zhen Tian Xiaoming Zha Wei Wang Meng Huang Chong Shao Hubei Key Laboratory of Power Equipment&System Security for Integrated Energy School of Electrical Engineering and AutomationWuhan UniversityWuhanChina NARI Technology Co. Ltd.NanjingChina State Grid Gansu Electric Power Company LanzhouChina

With the rapid increase in the installed capacity of renewable energy in modern power systems,the stable operation of power systems with considerable power electronic equipment requires further *** converter-based islanded microgrid(CIM)systems equipped with grid-following(GFL)and grid-forming(GFM)voltage-source converters(VSCs),it is challenging to maintain stability due to the mutual coupling effects between different VSCs and the loss of voltage and frequency support from the power *** previous studies,quantitative transient stability analysis was primarily used to assess the active power loop of ***,frequency and voltage dynamics are found to be strongly coupled,which strongly affects the estimation result of stability *** addition,the vary-ing damping terms have not been fully *** bridge these gaps,this paper investigates the transient stability of CIM consid-ering reactive power loop dynamics and varying ***,an accuracy-enhanced nonlinear model of the CIM is derived based on the effects of reactive power loop and post-disturbance frequency jump *** these effects will eliminates the risk of *** reactive power loop dynamics make the model coefficients be no longer constant and thus vary with the power *** evaluate quantitatively the effects of re-active power loop and varying damping on the transient stability of CIM,an iterative criterion based on the equal area criterion theory is *** addition,the effects of parameters on the stable boundary of power system are analyzed,and the dynamic interaction mechanisms are *** and experiment results verify the merits of the proposed method.

关键词： Transient stability converter iterative criterion reactive power loop post-disturbance frequency jump

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The Study of Materials for Electric Field Protection of Power Transformer Testing 9

The Study of Materials for Electric Field Protection of Powe...

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9th International Conference on Engineering, Applied Sciences, and technology, ICEAST 2023

作者： Meesuk, Peerawat Bunpakdee, Prajak Sorn-In, Sirirat Bansomdejchaopraya Rajabhat Univrtsity Electrical Engineering and Automation Control System Program Faculty of Engineering and Industrial Technology Bangkok Thailand

ISBN: (纸本)9798350322040

This paper proposes the analysis of the material can be protected from transformer testing and presents a mathematical model of the power transformer. In this research, transformers were study in four protective materials, wood, rubber, glass and acrylic that are used in between the electric field measurement and the transformer. By simulating the test results of a transformer with a voltage of 230 kV. Computer-based simulation utilizing the finite element method (FEM) is exploited as a tool for visualizing electric fields distribution volume a power transformer. The simulation results showed that the material with the best protection against the electric field was wood insulation and the best installation location was a distance of 5 m from the transformer. © 2023 IEEE.

关键词： Finite element method

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A Protection Scheme for Multi-Terminal HVDC Grids Using Local Transient Voltage Characteristics 17

A Protection Scheme for Multi-Terminal HVDC Grids Using Loca...

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17th International Conference on Protection and automation in Power system, IPAPS 2023

作者： Khaleghi-Abbasabadi, Ali Mehrabi-Kooshki, Mohammad Jamali, Sadegh Iran University of Science and Technology Center of Excellence for Power System Automation and Operation School of Electrical Engineering Tehran Iran

ISBN: (纸本)9798350311532

This paper proposes a novel single-end protection scheme to satisfy the operating speed, sensitivity, and selectivity required in the protection of HVDC grids based on the modular multilevel converter (MMC). In this regard, the fault voltage characteristics are analyzed at the early stage of internal and external faults to implement the protection scheme. It is shown that the existence of smoothing inductors at both sides of the MMC-HVDC transmission line causes the attenuation of the high-frequency components of the fault traveling wave head under external faults. Whereas, the generated fault traveling wave under internal faults contains plenty of high-frequency features. Putting this into perspective, an improved complementary ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is used to extract the highest frequency oscillations of initial fault voltage. Afterward, the high-frequency energy of the initial fault voltage is calculated by adopting the Hilbert transform (HT). As a result, the high-frequency energy calculated via ICEEMDAN-HT forms the fault identification criterion. To assess the proposed protection scheme, a four-Terminal half-bridge MMC-HVDC system is modeled in the PSCAD environment. According to simulation results, the proposed protection method is capable of detecting remote faults up to 300 Ω transition resistance within 1.1 ms only by acquiring local voltage data. Furthermore, the proposed method exhibits reliable performance under external faults and noise interferences. © 2023 IEEE.

关键词： Empirical mode decomposition

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Optimal Tracking Neuro-Control of Continuous Stirred Tank Reactor systems: A Dynamic Event-Driven Approach

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2117-2126页

作者： Yang, Xiong Zhou, Yingjiang Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin300072 China Nanjing University of Posts and Telecommunications College of Automation and College of Artificial Intelligence Nanjing210023 China

It is often challenging to design an optimal tracking controller for the continuous stirred tank reactor (CSTR) system due to its nonlinear nature and physical limitations. This article presents a dynamic event-driven optimal tracking neruo-control scheme for the CSTR system with asymmetric input constraints. Initially, an improved nonquadratic cost function is introduced for the CSTR system to tackle asymmetric control restrictions. Then, a dynamic event-driven mechanism together with the event-driven Hamilton-Jacobi-Bellman equation (ED-HJBE) is proposed. To solve the ED-HJBE, a critic neural network (CNN) is constructed within the critic learning framework. The CNN's weight vector is tuned by combining the gradient descent method and the concurrent learning technique. After that, uniform ultimate boundedness of the tracking error and the CNN's weight estimation error is assured based on the Lyapunov method. Finally, experiment studies are conducted to validate the present optimal tracking neuro-control strategy. © 2023 IEEE.

关键词： Reinforcement learning

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Characteristic Optimization Based on Combined Statistical Indicators and Random Forest Theory

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CSEE Journal of Power and Energy systems 2024年第6期10卷 2657-2666页

作者： Qingzhen Liu Chao Cai Lei Wu Renwu Yan School of Electric Engineering and Automation Fuzhou UniversityFuzhou 350116China Quanzhou Electric Power Supply Company State Grid Fujian Electric Power CompanyQuanzhou 362000China Electrical and Computer Engineering Department Stevens Institute of TechnologyHobokenNJ07030USA Department of Power System Fujian University of TechnologyFuzhou 350116China

In order to effectively utilize the dielectric response characteristics of transformers to diagnose the insulation state,this paper proposes a two-level hybrid optimization method for analyzing time-domain dielectric response *** optimization algorithm is based on the combined statistical indicators(CSI)and random forest(RF)*** initial feature space set is formed with 23 time-domain *** the first-level stage,statistical indices correlation,distance,and information indicators are integrated to assess the synthesis score of the characteristics,while highly redundant and lowclass discrimination characteristics are eliminated from the initial space *** the second-level stage,the Random Forest based outside bagging data theory is introduced to evaluate the least important characteristics,and the characteristics with low importance indices are excluded to obtain the final optimal feature space *** proposed method is carried out on 82 sets of data from actual dielectric response tests on oil-paper insulation ***,the final optimal feature space set,along with several other data sets,is tested via different diagnosis *** results show that the optimal feature space set obtained via the proposed method outperforms other feature space sets in terms of better adaptability and diagnosis accuracy.

关键词： Feature space optimization integrated statistical indicators oil-paper insulation state random forest time domain characteristic two-level algorithm

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A Novel Bi-Level VSC-DC Transmission Expansion Planning Method of VSC-DC for Power system Flexibility and Stability Enhancement

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Energy Engineering 2024年第11期121卷 3161-3179页

作者： Weigang Jin Lei Chen Shencong Zheng Yuqi Jiang Yifei Li Hongkun Chen Support Center of Power System Technology Central China Branch of State Grid Corporation of ChinaWuhan430077China Hubei Engineering and Technology Research Center forAC/DC Intelligent Distribution Network School of Electrical Engineering and AutomationWuhan UniversityWuhan430072China

Investigating flexibility and stability boosting transmission expansion planning(TEP)methods can increase the renewable energy(RE)consumption of the power *** this study,we propose a bi-level TEP method for voltage-source-converter-based direct current(VSC-DC),focusing on flexibility and stability ***,we established the TEP framework of VSC-DC,by introducing the evaluation indices to quantify the power system flexibility and ***,we propose a bi-level VSC-DC TEP model:the upper-level model acquires the optimal VSC-DC planning scheme by using the improved moth flame optimization(IMFO)algorithm,and the lower-level model evaluates the flexibility through time-series production ***,we applied the proposedVSC-DC TEPmethod to the modified IEEE-24 and IEEE-39 test systems,and obtained the optimalVSCDC planning *** results verified that the proposed method can achieve excellent RE curtailment with high flexibility and ***,the well-designed IMFO algorithm outperformed the traditional particle swarm optimization(PSO)and moth flame optimization(MFO)algorithms,confirming the effectiveness of the proposed approach.

关键词： VSC-DC transmission expansion planning renewable energy consumption line delivery flexibility short-circuit ratio improved moth flame optimization algorithm

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Cataract Surgical Instruments Segmentation Free of Motion Blur Influence 24

Cataract Surgical Instruments Segmentation Free of Motion Bl...

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13th International Conference on Bioinformatics and Biomedical Science, ICBBS 2024

作者： Sun, Xuebin Wang, Jinxi Yang, Xiaofei School of Electrical Automation and Information Engineering Tianjin University Tianjin China Department of Aerospace Laser Technology and System Shanghai Institute of Optics and Fine Mechanics Shanghai China

ISBN: (纸本)9798400717956

Most of the existing cataract surgical instrument segmentation algorithms fail to consider the motion blur caused by the surgeon's hand movement or defocused camera. Most prior deblurring methods are oriented to visual tasks to merely recover the structure information from motion-blurred images. However, during surgical instrument segmentation, it is important to obtain the exact location of the surgical instruments at the current time to pave the way for subsequent downstream tasks, such as tracking and position estimation. In this work, we propose a spatiotemporal (ST) information-based network, consisting of the deblurring module and a subsequent segmentation module, for cataract surgical instrument segmentation free of motion blur influence to address the missing gap in the existing literature. The ST recurrent network with a series of ST-LSTM and gradient highway units removes the motion blur, which then enables for accurate semantic segmentation. The ST network model subsequently captures the temporal and spatial correlation for semantic segmentation. Experimental results quantitatively and qualitatively demonstrate that our method outperforms the state-of-the-art on our self-constructed dataset and the CaDIS benchmark dataset. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Semantic Segmentation

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Speed Fluctuation Suppression of Current Scaling Errors Based on Improved Iterative Learning Control Method 26

Speed Fluctuation Suppression of Current Scaling Errors Base...

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26th International Conference on electrical Machines and systems, ICEMS 2023

作者： Mu, Haoyi Yu, Guodong Li, Shaobin Zhu, Pengcheng Xu, Yongxiang School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9798350317589

In recent years, there has been a growing demand for high-precision speed control of permanent magnet synchronous motor (PMSM), drawing significant attention to the issue of inherent current measurement errors in drive control. This paper presents a novel approach to mitigate periodic speed fluctuations using an expert system-based iterative learning control (ILC) method. The proposed method employs an expert system to dynamically adjust the weight values of the memory factor during online updates. This ensures the calculated relaxation factor optimally suppresses speed fluctuations across all operating conditions. Furthermore, the stability and parameter tuning aspects are analyzed from the perspective of transfer functions, and the feasibility of the proposed method is demonstrated through simulation. © 2023 IEEE.

关键词： Errors

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POSITIONING ACCURACY ANALYSIS FOR AN ELECTROMECHANICAL COUPLED ROBOTIC JOINT MODULE UNDER UNCERTAINTIES 14

POSITIONING ACCURACY ANALYSIS FOR AN ELECTROMECHANICAL COUPL...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024

作者： Wu, Jun Wang, He Wang, Qiyu Qu, Hongchen Xiahou, Tangfan Chen, Cen Liu, Yu School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Center for System Reliability and Safety University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China

ISBN: (纸本)9781837242672

The robotic joint module is a typical mechatronic system that inevitably faces uncertainties from various fields. These uncertainties significantly influence its positioning accuracy. In this article, we develop a positioning accuracy analysis of a robotic joint module under such uncertainties. First, a comprehensive electromechanical coupling model is constructed by considering the information exchange rules between mechanical and electronic components. Subsequently, a positioning accuracy analysis is performed, taking into account uncertainties from different fields. A variance-based sensitivity analysis method is employed to represent the contribution of these uncertainties. Finally, simulations are carried out to evaluate the effectiveness of the proposed method. © The Institution of Engineering & technology 2024.

关键词： Sensitivity analysis

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Lightweight Neural Network-Based Infrared Image and Anomalous Heat Region Recognition for electrical Equipment 18th

Lightweight Neural Network-Based Infrared Image and Anomalou...

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18th Annual Conference of China Electrotechnical Society, ACCES 2023

作者： Han, Zhikai Zhang, Jinglei Jia, Xin School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory of Complex System Control Theory and Application Tianjin300384 China

ISBN: (纸本)9789819710676

In order to accurately and quickly recognize electrical devices and abnormal heating parts under infrared conditions, we propose a lightweight neural network-based method for identifying electrical devices and their abnormal heating parts. First, we construct a fast target detection network for real-time detection. Second, we propose an efficient feature retention module to avoid the feature loss problem in multi-layer convolutional operations. In addition, we introduce an attention mechanism based on the coordinate information interaction strategy to localize the target more accurately. Finally, we use a lightweight weighted bidirectional feature pyramid network to improve the detection accuracy at different scales. Experimental results on a dataset of 12109 electrical infrared images containing six types of electrical devices and anomalously heated areas show that the proposed method achieves good results, with an average recognition accuracy of 93.9% and a processing speed of 222 frames/second. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Infrared imaging

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