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Metal-free Optical Pressure Sensor with High Sensitivity and Extensive Range

CSEE Journal of power and Energy systems 2024年第3期10卷 1291-1300页

作者： Mao Ji Meng Huang Haomin Lyu Sheng Shi Bo Qi Chengrong Li State Key Laboratory of Alternate Electrical power system with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China IEEE CSEE

Pressure monitoring of a transformer oil tank can grasp the pressure change process caused by gas production when severe internal defects occur and take timely measures to ensure the safe operation of the *** pressure sensors generally use metal encapsulation or have an air cavity structure,threatening the transformer’s insulation if it is directly used inside the *** this end,this paper proposes a method for developing a high-sensitivity,large-range,and metallizationfree optical pressure sensing device with temperature *** grating is encapsulated by fluorosilicone rubber and supplemented by an epoxy resin shielding shell on the *** the same time,a double-grating vertical arrangement is adopted to improve pressure measurement sensitivity,further avoiding the influence of temperature rise caused by a defect of the transformer on the measurement result of the *** addition,by optimizing the geometric structure of the internal sensitizing element,pre-stretching length of the fiber grating,gap distance,and other parameters,probe size can be reduced while ensuring the sensor’s *** show the proposed method can meet the requirements of sensor fabrication with different sensitivities and ranges,and to a certain extent,both high sensitivity and extensive ranges can be taken into *** sensitivity of the fabricated prototype is 15 pm/kPa,and the range is about 0.2 *** the same time,the metal-free feature of the sensor makes it suitable for use in various oil-immersed power *** records oil pressure changes caused by oil discharge breakdown,making it sensitive to small pressure changes in early failures.

关键词： Highly sensitive extensive range optical sensing no metallization pressure perception temperature compensation transformer

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Low-Carbon Dispatching for Virtual power Plant with Aggregated Distributed Energy Storage Considering Spatiotemporal Distribution of Cleanness Value

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Journal of Modern power systems and Clean Energy 2024年第2期12卷 346-358页

作者： Hongchao Gao Tai Jin Guanxiong Wang Qixin Chen Chongqing Kang Jingkai Zhu State Key Laboratory of power system Operation and Control Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Sichuan Energy Internet Research Institute Tsinghua University Chengdu 200016China power Dispatching and Control center of Shanghai Municipal Electric power Company Shanghai 200122China IEEE

The scale of distributed energy resources is increasing,but imperfect business models and value transmission mechanisms lead to low utilization ratio and poor *** address this issue,the concept of cleanness value of distributed energy storage(DES)is proposed,and the spatiotemporal distribution mechanism is discussed from the perspectives of electrical energy and *** on this,an evaluation system for the environmental benefits of DES is constructed to balance the interests between the aggregator and the power system ***,an optimal low-carbon dispatching for a virtual power plant(VPP)with aggregated DES is constructed,where-in energy value and cleanness value are both *** achieve the goal,a green attribute labeling method is used to establish a correlation constraint between the nodal carbon potential of the distribution network(DN)and DES behavior,but as a cost,it brings multiple nonlinear ***,a solution method based on the convex envelope(CE)linear re-construction method is proposed for the multivariate nonlinear programming problem,thereby improving solution efficiency and ***,the simulation verification based on the IEEE 33-bus DN is *** simulation results show that the multidimensional value recognition of DES motivates the willingness of resource users to ***,resolving the impact of DES on the nodal carbon potential can effectively alleviate overcompensation of the cleanness value.

关键词： Distributed energy storage virtual power plant(VPP) spatiotemporal distribution low-carbon dispatching

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Massively parallel algorithms for fully dynamic all-pairs shortest paths

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Frontiers of Computer Science 2024年第4期18卷 201-203页

作者： Chilei WANG Qiang-Sheng HUA Hai JIN Chaodong ZHENG National Engineering Research center for Big Data technology and system Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China State Key Laboratory for Novel Software technology Nanjing UniversityNanjing 210023China

1 Introduction In recent years,the Massively Parallel Computation(MPC)model has gained significant ***,most of distributed and parallel graph algorithms in the MPC model are designed for static graphs[1].In fact,the graphs in the real world are constantly *** size of the real-time changes in these graphs is smaller and more *** graph algorithms[2,3]can deal with graph changes more efficiently[4]than the corresponding static graph ***,most studies on dynamic graph algorithms are limited to the single machine ***,a few parallel dynamic graph algorithms(such as the graph connectivity)in the MPC model[5]have been proposed and shown superiority over their parallel static counterparts.

关键词： dynamic shortest gained

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Fault Diagnosis Method of Rolling Bearing Based on MSCNN-LSTM

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Computers, Materials & Continua 2024年第6期79卷 4395-4411页

作者： Chunming Wu Shupeng Zheng Key Laboratory of Modern power system Simulation and Control&Renewable Energy technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Ministry of Education Northeast Electric Power UniversityJilin132012China

Deep neural networks have been widely applied to bearing fault diagnosis systems and achieved impressive success *** address the problem that the insufficient fault feature extraction ability of traditional fault diagnosis methods results in poor diagnosis effect under variable load and noise interference scenarios,a rolling bearing fault diagnosis model combining Multi-Scale Convolutional Neural Network(MSCNN)and Long Short-Term Memory(LSTM)fused with attention mechanism is *** adaptively extract the essential spatial feature information of various sizes,the model creates a multi-scale feature extraction module using the convolutional neural network(CNN)learning *** learning capacity of LSTM for time information sequence is then used to extract the vibration signal’s temporal feature *** parallel large and small convolutional kernels teach the system spatial local *** gathers temporal global features to thoroughly and painstakingly mine the vibration signal’s characteristics,thus enhancing model ***,bearing fault diagnosis is accomplished by using the SoftMax *** experiment outcomes demonstrate that the model can derive fault properties entirely from the initial vibration *** can retain good diagnostic accuracy under variable load and noise interference and has strong generalization compared to other fault diagnosis models.

关键词： Bearing fault diagnosis convolutional neural network short-long-term memory network feature fusion

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Impact Force Localization and Reconstruction via ADMM-based Sparse Regularization Method

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Chinese Journal of Mechanical Engineering 2024年第3期37卷 170-188页

作者： Yanan Wang Lin Chen Junjiang Liu Baijie Qiao Weifeng He Xuefeng Chen National Key Lab of Aerospace power system and Plasma technology Xi’an Jiaotong UniversityXi’an 710049China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China

In practice,simultaneous impact localization and time history reconstruction can hardly be achieved,due to the illposed and under-determined problems induced by the constrained and harsh measuring *** l_(1) regularization can be used to obtain sparse solutions,it tends to underestimate solution amplitudes as a biased *** address this issue,a novel impact force identification method with l_(p) regularization is proposed in this paper,using the alternating direction method of multipliers(ADMM).By decomposing the complex primal problem into sub-problems solvable in parallel via proximal operators,ADMM can address the challenge *** mitigate the sensitivity to regularization parameters,an adaptive regularization parameter is derived based on the K-sparsity ***,an ADMM-based sparse regularization method is developed,which is capable of handlingl_(p) regularization with arbitrary p values using adaptively-updated *** effectiveness and performance of the proposed method are validated on an aircraft skin-like composite ***,an investigation into the optimal p value for achieving high-accuracy solutions vial_(p) regularization is *** turns out that?_(0.6)regularization consistently yields sparser and more accurate solutions for impact force identification compared to the classicl_(1) regularization *** impact force identification method proposed in this paper can simultaneously reconstruct impact time history with high accuracy and accurately localize the impact using an under-determined sensor configuration.

关键词： Impact force identification Non-convex sparse regularization Alternating direction method of multipliers Proximal operators

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Assessment and Enhancement of FRC of power systems Considering Thermal power Dynamic Conditions

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CSEE Journal of power and Energy systems 2024年第4期10卷 1371-1383页

作者： Feng Hong Yalei Pang Weiming Ji Lu Liang Fang Fang Junhong Hao Jizhen Liu State Key Laboratory of Alternate Electric power system with Renewable Energy Sources and School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China State Key Laboratory of Alternate Electric power system with Renewable Energy Sources School of Energy Power and Mechanical EngineeringNorth China Electric Power UniversityBeijing 102206China

Frequency stability and security have been a vital challenge as large-scale renewable energy is integrated into power *** contrast,the proportion of traditional thermal power units decreases during the decarbonization transformation process,resulting in poor frequency *** paper aims to explore the potential of frequency regulation support,dynamic assessment,and capacity promotion of thermal power plants in the transition *** the dynamic characteristics of the main steam working fluid under different working conditions,a nonlinear observer is constructed by extracting the main steam pressure and valve opening degree *** real-time frequency modulation capacity of thermal power units can provide a dynamic state for the power grid.A dynamic adaptive modification for primary frequency control(PFC)of power systems,including wind power and thermal power,is proposed and *** power dynamic allocation factor is adaptively optimized by predicting the speed droop ratio,and the frequency modulation capability of the system is improved by more than 11%under extreme ***,through the Monte Carlo simulation of unit states of the system under various working conditions,the promotion of the frequency regulation capacity with high wind power penetration(WPP)is verified.

关键词： Dynamic evaluation frequency regulation power system predictive modeling wind penetration

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Improved Proximal Policy Optimization Algorithm for Sequential Security-constrained Optimal power Flow Based on Expert Knowledge and Safety Layer

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Journal of Modern power systems and Clean Energy 2024年第3期12卷 742-753页

作者： Yanbo Chen Qintao Du Honghai Liu Liangcheng Cheng Muhammad Shahzad Younis State Key Laboratory of Alternate Electrical power system with Renewable Energy Sources and School of Electrical&Electronic Engineering North China Electric Power UniversityBeijing 102206China School of Engineering Xining UniversityXining 810008Chinaand Key Laboratory of Smart Operation of New Energy Power SystemMinistry of EducationQinghai UniversityXining 810016China China Electric power Research Institute Nanjing 210003China National University of Sciences and technology Islamabad44000Pakistan

In recent years,reinforcement learning(RL)has emerged as a solution for model-free dynamic programming problem that cannot be effectively solved by traditional optimization *** has gradually been applied in the fields such as economic dispatch of power systems due to its strong selflearning and self-optimizing ***,existing economic scheduling methods based on RL ignore security risks that the agent may bring during exploration,which poses a risk of issuing instructions that threaten the safe operation of power ***,we propose an improved proximal policy optimization algorithm for sequential security-constrained optimal power flow(SCOPF)based on expert knowledge and safety layer to determine active power dispatch strategy,voltage optimization scheme of the units,and charging/discharging dispatch of energy storage *** expert experience is introduced to improve the ability to enforce constraints such as power balance in training process while guiding agent to effectively improve the utilization rate of renewable ***,to avoid line overload,we add a safety layer at the end of the policy network by introducing transmission constraints to avoid dangerous actions and tackle sequential SCOPF *** results on an improved IEEE 118-bus system verify the effectiveness of the proposed algorithm.

关键词： Sequential security-constrained optimal power flow(SCOPF) expert experience safety layer renewable energy safe reinforcement learning

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Unveiling of Terahertz Emission from Ultrafast Demagnetization and the Anomalous Hall Effect in a Single Ferromagnetic Film

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Chinese Physics Letters 2024年第4期41卷 45-50页

作者：蓝志强李章顺徐浩然刘凡金钻明彭滟朱亦鸣 Terahertz technology Innovation Research Institute Terahertz Spectrum and Imaging Technology Cooperative Innovation CenterShanghai Key Lab of Modern Optical SystemUniversity of Shanghai for Science and TechnologyShanghai 200093China

Using THz emission spectroscopy,we investigate the elementary spin dynamics in ferromagnetic single-layer Fe on a sub-picosecond *** demonstrate that THz radiation changes its polarity with reversal of the magnetization applied by the external magnetic *** addition,it is found that the sign of THz polarity excited from different sides is defined by the thickness of the Fe layer and Fe/dielectric *** on the thickness and symmetry dependences of THz emission,we experimentally distinguish between the two major contributions:ultrafast demagnetization and the anomalous Hall *** experimental results not only enrich understanding of THz electromagnetic generation induced by femtosecond laser pulses but also provide a practical way to access laser-induced ultrafast spin dynamics in magnetic structures.

关键词： magnetic magnetization polarity

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An Improved Solov2 Based on Attention Mechanism and Weighted Loss Function for Electrical Equipment Instance Segmentation

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Computers, Materials & Continua 2024年第1期78卷 677-694页

作者： Junpeng Wu Zhenpeng Liu Xingfan Jiang Xinguang Tao Ye Zhang Key Laboratory of Modern power system Simulation and Control&Renewable Energy technology Ministry of EducationNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China Baishan power Supply Company State Grid Jilin Electric Power CoLtd.Jilin134300China

The current existing problem of deep learning framework for the detection and segmentation of electrical equipment is dominantly related to low *** of the reliable,safe and easy-to-operate technology provided by deep learning-based video surveillance for unmanned inspection of electrical equipment,this paper uses the bottleneck attention module(BAM)attention mechanism to improve the Solov2 model and proposes a new electrical equipment segmentation ***,the BAM attention mechanism is integrated into the feature extraction network to adaptively learn the correlation between feature channels,thereby improving the expression ability of the feature map;secondly,the weighted sum of CrossEntropy Loss and Dice loss is designed as the mask loss to improve the segmentation accuracy and robustness of the model;finally,the non-maximal suppression(NMS)algorithm to better handle the overlap problem in instance *** results show that the proposed method achieves an average segmentation accuracy of mAP of 80.4% on three types of electrical equipment datasets,including transformers,insulators and voltage transformers,which improve the detection accuracy by more than 5.7% compared with the original Solov2 *** segmentation model proposed can provide a focusing technical means for the intelligent management of power systems.

关键词： Deep learning electrical equipment attention mechanism weighted loss function

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Improvement in hydrogen storage performance of MgH_(2) by vanadium doped with ZIF-8 derived a single-atom catalyst V-N-C

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Rare Metals 2024年第6期43卷 2623-2635页

作者： Fei-Fan Hong Wei-Tao Shi Ruo-Lin Zhao Yi Fan Zi-Qi Liu Si-Zhi Ding Hai-Zhen Liu Wen-Zheng Zhou Jin Guo Zhi-Qiang Lan Guangxi Novel Battery Materials Research center of Engineering technology and center on Nanoenergy Research Guangxi Colleges and Universities Key Laboratory of Blue Energy and Systems IntegrationCarbon Peak and Neutrality Science and Technology Development InstituteSchool of Physical Science and TechnologyGuangxi UniversityNanning 530004China Nanning Engineering technology Research center for power Transmission system of New Energy Vehicle Transportation CollegeNanning UniversityNanning 530200China

Herein,the successful preparation of a singleatom catalyst V-N-C using vanadium-doped zeolitic imidazolate framework(ZIF)-8 as a precursor is *** experimental results showed that the V-N-C had a good promoting effect on the hydrogen storage performance of MgH_(2),and the optimal addition amount of V-N-C was 10wt%.The hydrogenation and dehydrogenation apparent activation energies of 10 wt%V-N-C-catalyzed MgH_(2)were reduced by 44.9 and 53.5 kJ·mol^(-1),respectively,compared to those of additive-free MgH_(2).The 10 wt%V-N-C-catalyzed MgH_(2)could reabsorb 5.92 wt%of hydrogen in 50 min at 150℃,with a capacity retention rate of 99.1%after 30 cycles of hydrogen absorption and *** analysis showed that V-N-C was partially transformed into VN and metallic V when it was milled with MgH_(2);the in-situ-formed VN and metallic V played an important role in improving the hydrogen storage performance of MgH_(2).This approach provides a potential solution for obtaining high-performance Mg-based hydrogen storage materials through synergistic interactions between V,N and C.

关键词： MgH_(2) Hydrogen storage materials Catalyst Hydrogen storage perormance

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