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10th International Conference on engineering, Applied Sciences, and Technology, ICEAST 2024

作者： Yutthagowith, Peerawut Mai-Eiam, Thanatorn Nimsanong, Phethai King Mongkut's Institute Of Technology Ladkrabang School Of Engineering Bangkok Thailand Metropolitan Electricity Authority Power System Control Department Bangkok Thailand

ISBN: (纸本)9798350385946

This paper presents designs for ultra-high-frequency (UHF) electromagnetic sensors based on printed circuit board (PCB) antennas for partial discharge (PD) detection in gas-insulated substations (GIS) applications. The sensors were designed to meet the requirement of narrowband/wideband UHF measuring systems for the UHF PD detection in GIS. The PD signals in the physical characteristic of the high-frequency electromagnetic (EM) wave were detected using the designed UHF antennas, which include the inset-fed rectangular microstrip patch (IFRMP) antennas, known for their narrowband characteristics that offer high interference signal rejection to improve signal-to-noise ratio and the two arm Archimedean spiral (TAAS) antennas, recognized for their broadband frequency spectrum capability. Because UHF PD signals are typically detected using various field sensor designs, both IFRMP and TAAS antennas were designed for three different models under calculation and simulation using MATLAB to apply in different operating frequency bands within the UHF range of PD detection (300 MHz-3 GHz). The designed UHF antennas have very characteristics, i.e. portable, lightweight, and attractive for practical applications with a low fabrication cost. Additionally, they are more convenient to install on the insulating flange compared to some types of external antenna sensors. In terms of antenna performance, they exhibit parameters like return loss (parameter S11) less than -10 dB and voltage standing wave ratio (VSWR) less than 2 within a close range of the designed operating frequency. Using the designed antennas, the phase-resolved PD (PRPD) patterns, the statistical magnitudes and waveforms of detected UHF signal have been obtained from laboratory testing for the sensitivity verification to help users in the effective application of the UHF PD detection. © 2024 IEEE.

关键词： Signal detection

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Correction of Time-varying PMU Phase Angle Deviation with Unknown Transmission Line Parameters

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CSEE Journal of power and Energy systems 2023年第1期9卷 315-325页

作者： Ancheng Xue He Kong Feiyang Xu Junbo Zhao Naichao Chang Joe H.Chow Haiyan Hong State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China Department of Electrical and Computer Engineering University of ConnecticutStorrs06268USA National Electric Power Dispatching and Control Center Beijing 100031China Department of Electrical Computerand Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNY 12180USA

Phasor measurement units(PMUs)provide useful data for real-time monitoring of the smart ***,there may be time-varying deviation in phase angle differences(PADs)between both ends of the transmission line(TL),which may deteriorate application performance based on *** address that,this paper proposes two robust methods of correcting time-varying PAD deviation with unknown parameters of TL(ParTL).First,the phenomena of time-varying PAD deviation observed from field PMU data are *** general formulations for PAD estimation are then *** simplify the formulations,estimation of PADs is converted into the optimal problem with a single ParTL as the variable,yielding a linear estimation of *** latter is used by second-order Taylor series expansion to estimate PADs *** reduce the impact of possible abnormal amplitude data in field data,the IGG(institute of Geodesy&Geophysics,Chinese Academy of Sciences)weighting function is *** using both simulated and field data verify the effectiveness and robustness of the proposed methods.

关键词： Correction line parameters parameter identification phasor measurement time-varying phase angle difference deviation

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Effect of ambient pressures on laser-induced breakdown spectroscopy signals

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Frontiers of physics 2024年第4期19卷 243-256页

作者： Kaifan Zhang Weiran Song Zongyu Hou Zhe Wang State Key Laboratory of Power System Operation and Control Tsinghua-Rio Tinto Joint Research Centre for ResourcesEnergy and Sustainable DevelopmentInternational Joint Laboratory on Low Carbon Clean Energy InnovationInstitute for Carbon NeutralityDepartment of Energy and Power EngineeringTsinghua UniversityBeijing 100084China Shanxi Research Institute for Clean Energy Tsinghua UniversityTaiyuan 030032China

Laser-induced breakdown spectroscopy(LIBS)is regarded as the future superstar for analytical chemistry and widely applied in various *** the quality of LIBS signal is fundamental to achieving accurate quantification and large-scale commercialization of *** propose control methods that improve LIBS signal quality,it is essential to have a comprehensive understanding of the influence of key parameters,such as ambient gas pressure,temperature,and sample temperature on LIBS *** date,extensive research has been carried ***,different researchers often yield significantly different experimental results for LIBS,preventing the formation of consistent *** greatly prevents the understanding of influencing laws of key parameters and the improvement of LIBS quantitative *** ambient gas pressure as an example,this paper compares the effects of ambient gas pressure under different optimization conditions,reveals the influence of spatiotemporal window caused by inherent characteristics of LIBS signal sources,i.e.,intense temporal changes and spatial non-uniformity of laser-induced plasmas,on the impact patterns of key *** the perspective of plasma spatiotemporal evolution,the paper elucidates the influence patterns of ambient gas pressure on LIBS signals,clarifying seemingly contradictory research results in the literature.

关键词： laser-induced breakdown spectroscopy spatiotemporal window pressure condition signal uncertainty plasma modulation

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Inter-Provincial Transaction Model in Two-Level ElectricityMarket Considering Carbon Emission and Consumption Responsibility Weights

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Energy engineering 2023年第10期120卷 2393-2416页

作者： Chunlei Jiao HongyanHao Ming Li Rifucairen Fu Yichun Liu Shunfu Lin Ronghui Liu Electric New Power System Technology Research Institute The Electric Power Research Institute of State Grid Xinjiang Electric Power Co.Ltd.Urumqi830000China Power Dispatch Control Center State Grid Xinjiang Electric Power Co.Ltd.Urumqi830063China College of Electrical Engineering Shanghai University of Electric PowerShanghai200090China

In the context of the joint operation of China’s intra-provincial markets and inter-provincial trading,how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key *** combined operation of intra-provincial and inter-provincial markets provides a new way for provincial power companies to optimize and clear the intra-provincial power market,complete the intra-provincial consumption responsibility weight index,and consume renewable energy across provinces and *** paper combines power generation and consumption within the province,uses inter-provincial renewable energy trading tomeet the load demand within the province and completes the index of intra-provincial consumption responsibility *** intra-provincial market trading and inter-provincial market clearing are respectively taken as the upper and lower levels of the *** the two-level electricity market operation framework,the upper-level model aims to minimize the expected total operating cost within the province considering the carbon emission cost and the weight of the consumption responsibility,while the lower-level model aims to minimize the inter-provincial renewable energy purchasing ***,the influence of inter-provincial transaction mechanism,risk aversion coefficient,voucher price,and responsibility weight on operating cost is *** is used to verify that the proposed model can meet the requirements of the provincial load power consumption and the consumption responsibility weight index,and promote the consumption of renewable energy.

关键词： Consumption responsibility weights electricity market carbon emission transactions between provinces

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Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

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Plasma Science and Technology 2024年第7期26卷 148-156页

作者：吕一涵宋惟然侯宗余王哲 State Key Laboratory of Power System Operation and Control International Joint Laboratory on Low Carbon Clean Energy InnovationDepartment of Energy and Power EngineeringTsinghua UniversityBeijing 100084People’s Republic of China School of Energy and Electrical Engineering Qinghai UniversityXining 810016People’s Republic of China Tsinghua University Shanxi Research Institute Clean EnergyTaiyuan 030032People’s Republic of China

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal ***,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification *** this work,we propose a hybrid variable selection method to improve the performance of LIBS *** variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash ***,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model *** proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline *** is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline *** results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,*** LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,*** results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the acc

关键词： laser-induced breakdown spectroscopy(LIBS) coal ash content quantitative analysis variable selection empirical knowledge partial least squares regression(PLSR)

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Neural Network Approaches for Magnetization Surface Prediction in Switched Reluctance Motors: Classical, Radial Basis Function, and Physics-Informed Models 3

Neural Network Approaches for Magnetization Surface Predicti...

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3rd IEEE International Conference on Problems of Informatics, Electronics and Radio engineering, PIERE 2024

作者： Demidova, Galina Bogdanov, Andrey Iaremenko, Andrei Xirong, Zhu Chen, Hao Anuchin, Alecksey Moscow Power Engineering Institute Electric Drive Department Moscow Russia Itmo University Faculty of Control System and Robotics Saint-Petersburg Russia School of Electrical and Power Engineering China University of Mining and Technology Xuzhou China

ISBN: (纸本)9798331516321

This paper investigates the prediction of magnetization surfaces in Switched Reluctance Motors using three distinct methods: classical Neural Networks, Radial Basis Function networks, and Physics-Informed Neural Networks. The study utilizes experimental data from a 7.5 kW SRM to assess the performance of these approaches, with all methods implemented in Python. Among the methods analyzed, PINN demonstrates the highest accuracy in predicting the magnetization surfaces, effectively capturing the underlying physical behavior of the motor. The computational costs of each method are evaluated, providing insights into training times, inference speeds, and floating-point operations per sample. The findings reveal that while NN offers a reasonable balance between performance and efficiency, the RBF method excels in training speed but shows limitations in capturing the physical dynamics of the system. In contrast, the PINN not only delivers superior predictive performance but also emphasizes the significance of incorporating physical principles into machine learning frameworks. The results highlight the applicability of these methods across various types of SRMs, suggesting their potential for enhancing control strategies in electrical and power engineering applications. © 2024 IEEE.

关键词： Radial basis function networks

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Mechanism and Methods for Fault Recovery of Grid-Forming Inverter by Graphical Illustration

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IEEE Transactions on power systems 2025年第2期40卷 1973-1976页

作者： Yang, Jialun Ye, Hua Wang, Yantuan Liu, Yutian Li, Yujun Du, Zhengchun Shandong Research Institute of Industrial Technology Jinan250061 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China Xi'an Jiaotong University Department of Electrical Engineering Xi'an710049 China

The existing priority-based current limiting control (CLC) for grid-forming (GFM) inverters may lead to failures in fault recovery, including being locked in CLC and mode oscillation between CLC and constant voltage control (CVC). To resolve these problems, this letter first reveals the fault recovery mechanism of droop controlled GFM inverters by illustrating the conditions of three fault recovery states in the phasor diagram. Then, two methods including determination of the optimal range of current angle and upper limit of saturation block are presented to guarantee successful fault recovery of GFM inverters. The correctness of theoretical analyses is verified and validated by multiple experimental tests. © 1969-2012 IEEE.

关键词： Fault current limiters

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A data selection method for matrix effects and uncertainty reduction for laser-induced breakdown spectroscopy

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Plasma Science and Technology 2023年第7期25卷 82-89页

作者：龙杰宋惟然侯宗余王哲 State Key Laboratory of Power System Operation and Control Systems International Joint Laboratory on Low Carbon Clean Energy InnovationDepartment of Energy and Power EngineeringTsinghua UniversityBeijing 100084People’s Republic of China Shanxi Research Institute for Clean Energy Tsinghua UniversityTaiyuan 030032People’s Republic of China

Severe matrix effects and high signal uncertainty are two key bottlenecks for the quantitative performance and wide applications of laser-induced breakdown spectroscopy(LIBS).Based on the understanding that the superposition of both matrix effects and signal uncertainty directly affects plasma parameters and further influences spectral intensity and LIBS quantification performance,a data selection method based on plasma temperature matching(DSPTM)was proposed to reduce both matrix effects and signal *** selecting spectra with smaller plasma temperature differences for all samples,the proposed method was able to build up the quantification model to rely more on spectra with smaller matrix effects and signal uncertainty,therefore improving final quantification *** applied to quantitative analysis of the zinc content in brass alloys,it was found that both accuracy and precision were improved using either a univariate model or multiple linear regression(MLR).More specifically,for the univariate model,the root-mean-square error of prediction(RMSEP),the determination coefficients(R^(2))and relative standard derivation(RSD)were improved from 3.30%,0.864 and 18.8%to 1.06%,0.986 and 13.5%,respectively;while for MLR,RMSEP,R^(2)and RSD were improved from 3.22%,0.871 and 26.2%to 1.07%,0.986 and 17.4%,*** results prove that DSPTM can be used as an effective method to reduce matrix effects and improve repeatability by selecting reliable data.

关键词： laser-induced breakdown spectroscopy(LIBS) quantification uncertainty univariate/multivariate analysis matrix effects temperature matching

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A Spatial-Temporal Forecasting Method for Electric Vehicle Charging Load Based on GDC-LSTM User Travel Characteristics Analysis 7

A Spatial-Temporal Forecasting Method for Electric Vehicle C...

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7th IEEE Student Conference on Electric Machines and systems, SCEMS 2024

作者： Li, Chengze Zhao, Yan Liang, Yisong Yu, Kaixiang Zhao, Qihang Yuan, Bin School of Electric Power Shenyang institute of engineering Shenyang China Shenyang institute of engineering Key Laboratory of Regional Multi-energy System Integration and Control of Liaoning Province Shenyang China School of New Energy Shenyang Institute of Engineering Shenyang China

ISBN: (纸本)9798350366945

In this study, a spatio-temporal prediction model for EV charging loads is proposed based on the Graph diffusion convolution-Long short-term memory network (GDC-LSTM). This model integrates diverse sources of information, including weather conditions, day types, and temperatures. Firstly, the GDC-LSTM is employed to predict EV traffic flow data, capturing the travel patterns of EV users. Subsequently, a real-time model for EV power consumption is developed, and the floyd shortest path algorithm is optimized by introducing real-time road saturation data.. Finally, employing the Monte Carlo method, spatio-temporal distributions of various EV charging loads are forecasted and mapped onto distribution network nodes. The effectiveness of the methodology is verified by demonstrating the model's ability to predict EV travel behavior and load distribution through a case study in the main urban area of Chengdu, and evaluating the impact of load access on distribution network node voltages. © 2024 IEEE.

关键词： Prediction models

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Multi-Objective Coordination and Stability control of High Proportion Wind power system Based on K-Domain Tuning Damping 19th

Multi-Objective Coordination and Stability Control of High P...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Zhang, Qingtao Gao, Diju Zhang, Dan Cai, Haiqing Gu, Haohan Chen, Wei Wu, Wencong Chen, Zhihao Institute of Logistics Engineering Shanghai Maritime University Shanghai China Institute of Logistic Science and Engineering Shanghai Maritime University Shanghai China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9789819608966

With the further development of "double high" characteristics of power system, the traditional stability problem dominated by synchronous generator has gradually evolved into a new stability problem dominated by power electronic equipment control. In addition, different types of failure problems can occur in wind power systems. In order to achieve multi-objective coordinated and stable operation of high proportion wind power system, a damping control method with parameters tuning is proposed, which includes the design of filtering link and proportional amplification link. Among them, the key parameters of the proportional link are adjusted. Finally, the feasibility of the proposed control method is verified by simulation tests. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Electric power system stability

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