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Journal of Mountain Science 2024年第1期21卷 84-99页

作者： QIN Zipeng TIAN Yan GAO Siyuan ZHOU Jianfen HE Xiaohui HE Weizhong GAO Jingquan School of water co.servancy and Environment engineering Zhejiang University of Water Resources and Electric PowerHangzhou 310018China Department of Civil engineering Imperial College LondonLondonSW71BFEngland Lanxi water Affairs Bureau Lanxi 321102China Zhejiang water co.servancy engineering consulting co. LtdHangzhou 310051China

The stability of the ancient flood co.trol levees is mainly influenced by water level fluctuations, groundwater co.centration and rainfalls. This paper takes the Lanxi ancient levee as a research object to study the evolution laws of its seepage, displacement and stability before and after reinforcement with the upside-down hanging wells and grouting curtain through numerical simulation methods co.bined with experiments and observations. The study results indicate that the filled soil is less affected by water level fluctuations and groundwater co.centration after reinforcement. A high groundwater level is detrimental to the levee's long-term stability, and the drainage issues need to be fully co.sidered. The deformation of the reinforced levee is effectively co.trolled since the fill deformation is mainly borne by the upside-down hanging wells. The safety factors of the levee before reinforcement vary significantly with the water level. The minimum value of the safety factors is 0.886 during the water level decreasing period, indicating a very high risk of the instability. While it reached 1.478 after reinforcement, the stability of the ancient levee is improved by a large margin.

关键词： Stability analysis Multiple factors Antiseepage reinforcement Upside-down hanging well Grouting curtain Ancient levee

A Wind power Prediction Framework for Distributed power Grids

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Energy engineering 2024年第5期121卷 1291-1307页

作者： Bin Chen Ziyang Li Shipeng Li Qingzhou Zhao Xingdou Liu power Grid Design Institute Shandong Electric Power Engineering Consulting Institute Co.Ltd.Jinan250013China School of Electrical engineering Shandong UniversityJinan250012China

To reduce carbon emissions,clean energy is being integrated into the power *** power is co.nected to the grid in a distributed form,but its high variability poses a challenge to grid *** article co.bines wind turbine monitoring data with numerical weather prediction(NWP)data to create a suitable wind power prediction framework for distributed ***,high-precision NWP of the turbine range is achieved using weather research and forecasting models(WRF),and Kriging interpolation locates predicted meteorological data at the turbine ***,a preliminary predicted power series is obtained based on the fan’s wind speed-power co.version curve,and historical power is reco.structed using variational mode deco.position(VMD)filtering to form input variables in chronological ***,input variables of a single turbine enter the temporal co.volutional network(TCN)to co.plete initial feature extraction,and then integrate the outputs of all TCN layers using Long Short Term Memory Networks(LSTM)to obtain power prediction sequences for all turbine *** proposed method was tested on a wind farm co.nected to a distributed power grid,and the results showed it to be superior to existing typical methods.

关键词： Wind power prediction distributed power grid WRF mode deep learning variational mode deco.position

Optimal Location and Sizing ofMulti-Resource Distributed Generator Based onMulti-Objective Artificial Bee co.ony Algorithm

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Energy engineering 2024年第2期121卷 499-521页

作者： Qiangfei Cao Huilai Wang Zijia Hui Lingyun Chen Eco.omic and Technological Research Institute State Grid Shanxi Electric Power Co.Ltd.Xi’an710075China Central Southern China Electric power Design Institute co. Ltd.China Power Engineering Consulting GroupWuhan430074China

Distribution generation(DG)technology based on a variety of renewable energy technologies has developed rapidly.A large number of multi-type DG are co.nected to the distribution network(DN),resulting in a decline in the stability of DN *** is urgent to find a method that can effectively co.nect multi-energy DG to ***(PV),wind power generation(WPG),fuel cell(FC),and micro gas turbine(MGT)are co.sidered in this paper.A multi-objective optimization model was established based on the life cycle co.t(LCC)of DG,voltage quality,voltage fluctuation,system network loss,power deviation of the tie-line,DG pollution emission index,and meteorological index weight of ***-objective artificial bee co.ony algorithm(MOABC)was used to determine the optimal location and capacity of the four kinds of DG access DN,and co.pared with the other three heuristic *** tests based on IEEE 33 test node and IEEE 69 test node show that in IEEE 33 test node,the total voltage deviation,voltage fluctuation,and system network loss of DN decreased by 49.67%,7.47%and 48.12%,respectively,co.pared with that without DG *** the IEEE 69 test node,the total voltage deviation,voltage fluctuation and system network loss of DN in the MOABC co.figuration scheme decreased by 54.98%,35.93%and 75.17%,respectively,co.pared with that without DG co.figuration,indicating that MOABC can reasonably plan the capacity and location of *** the maximum trade-off between DG eco.omy and DN operation stability.

关键词： Distributed generation distribution network life cycle co.t multi-objective artificial bee co.ony algorithm voltage stability

Enhanced wear prediction of tunnel boring machine disc cutters for accurate remaining useful life estimation using a hybrid model

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Frontiers of Structural and Civil engineering 2024年第4期18卷 642-662页

作者： Xinghai ZHOU Yakun ZHANG Guofang GONG Huayong YANG Qiaosong CHEN Yuxi CHEN Zhixue SU The State Key Laboratory of Fluid power&Mechatronic Systems Zhejiang UniversityHangzhou 310027China Guangzhou Rail Transit co.struction engineering consulting co. Ltd.Guangzhou 510000China China Railway engineering Equipment Group co. Ltd.Zhengzhou 450016China

In tunnel co.struction with tunnel boring machines(TBMs),accurate prediction of the remaining useful life(RUL)of disc cutters is critical for timely maintenance and replacement to avoid delays and co.t *** paper introduces a novel hybrid model,integrating fundamental and data-driven approaches,to enhance wear prediction of TBM disc cutters and enable accurate RUL *** fundamental model is improved by inco.porating co.posite wear mechanisms and load estimation techniques,showcasing superior prediction accuracy co.pared to single-mechanism ***,the hybrid model innovatively inco.porates a data-driven supplementary residual term into the improved fundamental model,leading to a high-performance wear prediction *** actual field data from a highway tunnel project in Shenzhen,the performance of the hybrid model is rigorously tested and co.pared with pure fundamental and data-driven *** hybrid model outperforms the other models,achieving the highest accuracy in predicting TBM disc cutter wear(mean absolute error(MAE)=0.53,root mean square error(RMSE)=0.64).Furthermore,this study thoroughly analyzes the hybrid model’s generalization capability,revealing significant impacts of geological co.ditions on prediction *** model’s generalization capability is also improved by expanding and updating the data *** RUL estimation results provided by the hybrid model are straightforward and effective,making it a valuable tool by which co.struction staff can monitor TBM disc cutters.

关键词： tunnel boring machine disc cutter wear prediction remaining useful life field data hybrid model

High-precision parallel co.puting model of solute transport based on GPU acceleration

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Journal of Hydrodynamics 2024年第1期36卷 202-212页

作者： Shang-hong Zhang Rong-qi Zhang Wen-da Li Xi-yan Yang Yang Zhou School of water Resources and Hydropower engineering North China Electric Power UniversityBeijing102206China Hubei Key Laboratory of Intelligent Yangtze and Hydroelectric Science China Yangtze Power Co.Ltd.Yichang443133China

The scenario simulation analysis of water environmental emergencies is very important for risk prevention and co.trol,and emergency *** quickly and accurately simulate the transport and diffusion process of high-intensity pollutants during sudden environmental water pollution events,in this study,a high-precision pollution transport and diffusion model for unstructured grids based on co.pute Unified Device Architecture(CUDA)is *** finite volume method of a total variation diminishing limiter with the Kong proposed r-factor is used to reduce numerical diffusion and oscillation errors in the simulation of pollutants under sharp co.centration co.ditions,and graphics processing unit acceleration technology is used to improve co.putational *** advection diffusion process of the model is verified numerically using two benchmark cases,and the efficiency of the model is evaluated using an engineering *** results demonstrate that the model perform well in the simulation of material transport in the presence of sharp ***,it has high co.putational *** acceleration ratio is 46 times the single-thread acceleration effect of the original *** efficiency of the accelerated model meet the requirements of an engineering application,and the rapid early warning and assessment of water pollution accidents is achieved.

关键词： Pollution transport and diffusion model parallel co.puting co.pute Unified Device Architecture(CUDA) pollution event

Vibration and noise mechanism of a 110 kV transformer under DC bias based on finite element method

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Global Energy Interco.nection 2024年第4期7卷 503-512页

作者： Ziyang Li Xujun Lang Bo Yang Xiaolin Liu Hao Wang Zhang Li Shandong Electric power engineering consulting Institute co. Ltd.Jinan 250013P.R.China School of Electrical engineering Shandong UniversityJinan 250061P.R.China

Global energy and environmental issues are beco.ing increasingly problematic,and the vibration and noise problem of 110 kV transformers,which are the most widely distributed,have attracted widespread attention from both inside and outside the *** bias is one of the main co.tributing factors to vibration noise during the normal operation of *** clarify the vibration and noise mechanism of a 110 kV transformer under a DC bias,a multi-field co.pling model of a 110 kV transformer was established using the finite element *** electromagnetic,vibration,and noise characteristics during the DC bias process were co.pared and quantified through field circuit co.pling in parallel with the power frequency of AC,harmonic,and DC power *** was found that a DC bias can cause significant distortions in the magnetic flux density,force,and displacement distributions of the co.e and *** co.tributions of the DC bias effect to the co.e and winding are different at Kdc=*** this point,the co.e approached saturation,and the increase in the co.e force and displacement ***,the saturation of the co.e increased the leakage flux,and the stress and displacement of the winding increased *** sound field distribution characteristics of the 110 kV transformer under a DC bias are related to the force *** the DC bias co.fficient was 1.25,the noise sound pressure level reached 73.6 dB.

关键词： Transformer DC bias Vibration Noise

Cyber-Physical Resilience Enhancement for power Transmission Systems with Energy Storage Systems

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CSEE Journal of power and Energy Systems 2024年第2期10卷 844-855页

作者： Wenhao Zhang Dongyang Rui Weihong Wang Yang Guo Zhaoxia Jing Wenhu Tang School of Electric power engineering South China University of TechnologyGuangzhou 510640China Guangzhou Zhiguang Electric co. Ltd and Zhiguang Research Institute(Guangzhou)Co.LtdGuangzhou 510765China

In a power system, when extreme events occur, such as ice storm, large scale blackouts may be unavoidable. Such small probability but high risk events have huge impact on power systems. Most resilience research in power systems only co.siders faults on the physical side, which would lead to overly idealistic results. This paper proposes a two-stage cyber-physical resilience enhancement method co.sidering energy storage (ES) systems. The first stage calculates optimal planning of ES systems, and the seco.d stage assesses resilience and enhancement of ES systems during the disaster. In the proposed model, cyber faults indirectly damage the system by disabling monitoring and co.trol function of co.trol center. As a result, when detection and response process of physical faults are blocked by cyber failures, serious load shedding occurs. Such a cyber-physical co.pling mechanism of fault, response, restoration process is demonstrated in the modified IEEE Reliable Test System-79 (RTS-79). Simulation results show co.pared with the physical-only system, the cyber-physical system has a more accurate but degraded resilient performance. Besides, ES systems setting at proper place effectively enhance resilience of the cyber-physical transmission system with less load Shedding.

关键词： Cyber-physical faults energy storage systems resilience enhancement transmission systems

Effects of BN on the Mechanical and Thermal Properties of PP/BN co.posites

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Journal of Wuhan University of Technology(Materials Science) 2024年第2期39卷 345-352页

作者：陈厚振王艳芝 NAN Yu WANG Xu YUE Xianyang ZHANG Yifei FAN Huiling School of Textiles Zhongyuan University of TechnologyZhengzhou 451191China Kaifeng power Supply co.pany State Grid Henan Electric Power CompanyKaifeng 475000China School of Materials Science and engineering Zhejiang University of TechnologyHangzhou 310014China Zhengzhou Hengtian co.per co. Ltd.Zhengzhou 451100China

In order to explore the thermal co.ductivity of polypropylene(PP)/hexagonal boron nitride(BN) co.posites,PP co.posites filled with different proportions of BN were prepared through extrution co.pounding,injection moulding and co.pression *** co.posites were filled with BN particles of 5 and 20 μm respectively,and their mass fractions in co.posites were *** of BN was varied from 0 to 25wt% in steps of 5wt%.The effects of BN filler on mechanical properties of the co.posites were *** thermal behaviors were studied using DSC and TGA,and the thermal co.ductivity was also investigated by Laser Flash Device and the Model of 3D Heat co.duction *** experimental results show that impact strength of PP/BN can be enhanced with the addition of BN,but that co.posites exhibit lower breaking elongation & tensile strength when co.pared to unfilled *** is found that mass fraction of BN influenced the final thermal stability and degree of crystallization of PP matrix,the degree of crystallization of PP with 15wt% of 20 μm BN can be improved by 25% than neat ***,crystallization temperatures of PP co.posites are elevated by about 10 ℃.The thermal co.ductivity results demonstrate that the maximum value of the thermal co.ductivity is achieved from PP/BN with 20wt% of 20 μm BN,higher than that of pure PP by 95.65%,close to the simulation one.

关键词： thermal properties polypropylene co.posites hexagonal boron nitride

Research on co.denser Deterioration Evolution Trend Based on ANP-EWM Fusion Health Degree

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co.puter Modeling in engineering & Sciences 2024年第4期139卷 679-698页

作者： Hong Qian Haixin Wang Guangji Wang Qingyun Yan co.lege of Automation engineering Shanghai University of Electric PowerShanghai200090China Shanghai Key Laboratory of power Station Automation Technology Shanghai200072China Empower Information Technology(Shanghai)co. Ltd.Shanghai201508China China Nuclear power engineering Design co. Ltd.Shenzhen518052China

This study presents a proposed method for assessing the co.dition and predicting the future status of co.densers operating in seawater over an extended *** aim is to address the problems of scaling and co.rosion,which lead to increased loss of co.d *** method involves utilising a set of multivariate feature parameters associated with the co.denser as input for evaluation and trend *** methodology offers a precise means of determining the optimal timing for co.denser cleaning,with the ultimate goal of improving its overall *** proposed approach involves the integration of the analytic network process with subjective expert experience and the entropy weightmethod with objective big data analysis to develop a fusion health *** mathematical model is co.structed quantitatively using the improved Mahalanobis ***,a co.prehensive prediction model is developed by integrating the improved Informer model and Markov error *** model takes into acco.nt the health status of the equipment and several influencing factors,includingmultivariate feature *** model facilitates the objective examination and prediction of the progression of equipment deterioration *** present study involves the co.putation and verification of the field time series data,which serves to demonstrate the accuracy of the co.denser health-related models proposed in this *** models effectively depict the real co.dition and temporal variations of the equipment,thus offering a valuable method for determining the precise cleaning time required for the co.denser.

关键词： co.denser health degree improved Mahalanobis distance GC-Informer model Markov error co.rection

Feature Selection Using Tree Model and Classification Through co.volutional Neural Network for Structural Damage Detection

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Acta Mechanica Solida Sinica 2024年第3期37卷 498-518页

作者： Zihan Jin Jiqiao Zhang Qianpeng He Silang Zhu Tianlong Ouyang Gongfa Chen School of Civil and Transportation engineering Guangdong University of TechnologyGuangzhou510006China Guangdong Tianxin Electric power engineering Testing co. LtdGuangzhou510663China

Structural damage detection(SDD)remains highly challenging,due to the difficulty in selecting the optimal damage features from a vast amount of *** this study,a tree model-based method using decision tree and random forest was employed for feature selection of vibration response signals in *** datasets were obtained by numerical experiments and vibration experiments,*** features extracted using this method were input into a co.volutional neural network to determine the location of structural *** indicated a 5%to 10%improvement in detection accuracy co.pared to using original datasets without feature selection,demonstrating the feasibility of this *** proposed method,based on tree model and classification,addresses the issue of extracting effective information from numerous vibration response signals in structural health monitoring.

关键词： Feature selection Structural damage detection Decision tree Random forest co.volutional neural network