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Probabilistic analysis of tunnel face seismic stability in layered rock masses using Polynomial Chaos Kriging metamodel

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Journal of Rock Mechanics and Geotechnical engineering 2024年第7期16卷 2678-2693页

作者： Jianhong Man Tingting Zhang Hongwei Huang Daniel Dias Department of Geotechnical engineering Key Laboratory of Geotechnical and Underground Engineering of Ministry of EducationCollege of Civil EngineeringTongji UniversityShanghai200092China grenoble Alpes 3SR LabCNRS UMR 5521Grenoble38000France

Face stability is an essential issue in tunnel design and *** rock masses are typical and ubiquitous;uncertainties in rock properties always *** view of this,a comprehensive method,which combines the Upper bound Limit analysis of Tunnel face stability,the Polynomial Chaos Kriging,the Monte-Carlo Simulation and Analysis of Covariance method(ULT-PCK-MA),is proposed to investigate the seismic stability of tunnel faces.A two-dimensional analytical model of ULT is developed to evaluate the virtual support force based on the upper bound limit *** efficient probabilistic analysis method PCK-MA based on the adaptive Polynomial Chaos Kriging metamodel is then implemented to investigate the parameter uncertainty *** input parameters,including geological strength indices,uniaxial compressive strengths and constants for three rock formations,and the horizontal seismic coefficients,are treated as random *** effects of these parameter uncertainties on the failure probability and sensitivity indices are *** addition,the effects of weak layer position,the middle layer thickness and quality,the tunnel diameter,the parameters correlation,and the seismic loadings are investigated,*** results show that the layer distributions significantly influence the tunnel face probabilistic stability,particularly when the weak rock is present in the bottom *** efficiency of the proposed ULT-PCK-MA is validated,which is expected to facilitate the engineering design and construction.

关键词： Tunnel face stability Layered rock masses Polynomial Chaos Kriging(PCK) Sensitivity index Seismic loadings

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Market Equilibrium Based on Cloud-edge Collaboration

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 96-104页

作者： Tong Cheng Haiwang Zhong Qing Xia the State Key laboratory of Power Systems the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

Market participants can only bid with lagged information disclosure under the existing market mechanism,which can lead to information asymmetry and irrational market behavior,thus influencing market *** promote rational bidding behavior of market participants and improve market efficiency,a novel electricity market mechanism based on cloudedge collaboration is proposed in this *** market information,called residual demand curve,is published to market participants in real-time on the cloud side,while participants on the edge side are allowed to adjust their bids according to the information disclosure prior to closure *** proposed mechanism can encourage rational bids in an incentive-compatible way through the process of dynamic equilibrium while protecting participants’*** paper further formulates the mathematical model of market equilibrium to simulate the process of each market participant’s strategic bidding behavior towards equilibrium.A case study based on the IEEE 30-bus system shows the proposed market mechanism can effectively guide bidding behavior of market participants,while condensing exchanged information and protecting privacy of participants.

关键词： Cloud-edge collaboration market mechanism residual demand curve strategic bidding

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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)Lausanne 1015Switzerland the College of Information and electrical engineering China Agricultural UniversityBeijing 100083China the College of electrical engineering and Automation Shandong University of Science and TechnologyQingdao 266590China the Department of electrical and Electronic engineering(Energy Digitalization laboratory) The University of Hong KongHong KongChina the Department of electrical engineering The Hong Kong Polytechnic UniversityHong KongChina

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 *** 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 *** 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 ***,a rulebased strategy is proposed to adjust infeasible solutions that violate *** 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 ***,its online inference time is significantly faster than traditional physical model based methods,particularly for large-scale distribution networks.

关键词： Reactive power optimization graph neural network distribution network machine learning data-driven

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Sensing the heavy water concentration in an H_(2)O-D_(2)O mixture by solid-solid phononic crystals

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Chinese Physics B 2024年第4期33卷 493-498页

作者： Mohammadreza Rahimi Ali Bahrami Optoelectronic and Nanophotonics Research laboratory(ONRL) Faculty of Electrical EngineeringSahand University of TechnologyTabrizIran

A new method based on phononic crystals is presented to detect the concentration of heavy water(D_(2)O)in an H_(2)O-D_(2)O *** have been obtained and analyzed in the concentration range of 0%-10%and 90%-100%D_(2)O.A proposed structure of tungsten scatterers in an aluminum host is *** order to detect the target material,a cavity region is considered as a sound wave resonator in which the target material with different concentrations of D_(2)O is *** changing the concentration of D_(2)O in the H_(2)O-D_(2)O mixture,the resonance frequency undergoes a frequency *** 1%change in D_(2)O concentration in the H_(2)O-D_(2)O mixture causes a frequency change of about 120 *** finite element method is used as the numerical method to calculate and analyze the natural frequencies and transmission spectra of the proposed *** performance evaluation index shows a high Q factor up to 1475758 and a high sensitivity up to 13075,which are acceptable values for sensing *** other figures of merit related to the detection performance also indicate high-quality performance of the designed sensor.

关键词： phononic crystals sensor H_(2)O-D_(2)O mixture cavity

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A Least-squares-based Iterative Method with Better Convergence for PF/OPF in Integrated Transmission and Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 953-962页

作者： Kunjie Tang Shufeng Dong Yonghua Song College of electrical engineering Zhejiang UniversityHangzhou 310027China State Key laboratory of Internet of Things for Smart City and Department of electrical and Computer engineering University of MacaoMacao SARChina IEEE

The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first *** that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is *** with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are ***,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power *** experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark ***,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional ***,in some cases,where conventional methods diverge,these LSI methods can still converge.

关键词： Fixed-point theory integrated transmission and distribution networks least-squares-based iterative method master-slave-splitting method optimal power flow power flow

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Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 51-65页

作者： Yonghua Song Ge Chen Hongcai Zhang State Key laboratory of Internet of Things for Smart City and Department of electrical and Computer engineering University of MacaoMacao 999078China School of electrical and Computer engineering Purdue UniversityWest LafayetteIN 47907 USA

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks(ADNs)to facilitate integration of distributed renewable *** to unavailability of network topology and line impedance in many distribution networks,physical model-based methods may not be applicable to their *** tackle this challenge,some studies have proposed constraint learning,which replicates physical models by training a neural network to evaluate feasibility of a decision(i.e.,whether a decision satisfies all critical constraints or not).To ensure accuracy of this trained neural network,training set should contain sufficient feasible and infeasible ***,since ADNs are mostly operated in a normal status,only very few historical samples are ***,the historical dataset is highly imbalanced,which poses a significant obstacle to neural network *** address this issue,we propose an enhanced constraint learning ***,it leverages constraint learning to train a neural network as surrogate of ADN's ***,it introduces Synthetic Minority Oversampling Technique to generate infeasible samples to mitigate imbalance of historical *** incorporating historical and synthetic samples into the training set,we can significantly improve accuracy of neural ***,we establish a trust region to constrain and thereafter enhance reliability of the *** confirm the benefits of the proposed method in achieving desirable optimality and feasibility while maintaining low computational complexity.

关键词： Deep learning demand response distribution networks imbalanced data optimal power flow

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Distributed Stochastic Scheduling of Massive Backup Batteries in Cellular Networks for Operational Reserve and Frequency Support Ancillary Services

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 393-404页

作者： Kun Li Jiakun Fang Xiaomeng Ai Shichang Cui Rongkang Zhao Jinyu Wen State Key laboratory of Advanced Electromagnetic engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074China IEEE

Base station(BS)backup batteries(BSBBs),with their dispatchable capacity,are potential demand-side resources for future power *** enhance the power supply reliability and post-contingency frequency security of power systems,we propose a two-stage stochastic unit commitment(UC)model incorporating operational reserve and post-contingency frequency support provisions from massive BSBBs in cellular networks,in which the minimum backup energy demand is considered to ensure BS power supply *** energy,operational reserve,and frequency support ancillary services are co-optimized to handle the power balance and post-contingency frequency security in both forecasted and stochastic variable renewable energy(VRE)***,we propose a dedicated and scalable distributed optimization framework to enable autonomous optimizations for both dispatching center(DC)and *** BS model parameters are stored and processed locally,while only the values of BS decision variables are required to upload to DC under the proposed distributed optimization framework,which safeguards BS privacy *** studies on a modified IEEE 14-bus system demonstrate the effectiveness of the proposed method in promoting VRE accommodation,ensuring post-contingency frequency security,enhancing operational economics,and fully utilizing BSBBs'energy and power ***,the proposed distributed optimization framework has been validated to converge to a feasible solution with near-optimal performance within limited ***,numerical results on the Guangdong 500 kV provincial power system in China verify the scalability and practicality of the proposed distributed optimization framework.

关键词： Base station backup battery operational reserve frequency security distributed optimization privacy

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Bifunctional TiO_(2-x)nanofibers enhanced gel polymer electrolyte for high performance lithium metal batteries

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Journal of Energy Chemistry 2024年第2期89卷 437-448,I0011页

作者： Yixin Wu Zhen Chen Yang Wang Yu Li Chunxing Zhang Yihui Zhu Ziyu Yue Xin Liu Minghua Chen Key laboratory of engineering Dielectric and Applications(Ministry of Education) School of Electrical and Electronic EngineeringHarbin University of Science and TechnologyHarbin 150080HeilongjiangChina

Exploration of advanced gel polymer electrolytes(GPEs)represents a viable strategy for mitigating dendritic lithium(Li)growth,which is crucial in ensuring the safe operation of high energy density Li metal batteries(LMBs).Despite this,the application of GPEs is still hindered by inadequate ionic conductivity,low Li^(+)transference number,and subpar physicochemical ***,Ti O_(2-x)nanofibers(NF)with oxygen vacancy defects were synthesized by a one-step process as inorganic fillers to enhance the thermal/mechanical/ionic-transportation performances of composite *** characterizations and theoretical calculations reveal that the oxygen vacancies on the surface of Ti O_(2-x)NF accelerate the dissociation of Li PF_6,promote the rapid transfer of free Li^(+),and influence the formation of Li F-enriched solid electrolyte ***,the composite GPEs demonstrate enhanced ionic conductivity(1.90m S cm^(-1)at room temperature),higher lithium-ion transference number(0.70),wider electrochemical stability window(5.50 V),superior mechanical strength,excellent thermal stability(210℃),and improved compatibility with lithium,resulting in superior cycling stability and rate performance in both Li||Li,Li||Li Fe PO_(4),and Li||Li Ni_(0.8)Co_(0.1)Mn_(0.1)O_(2)***,the synergistic influence of nanofiber morphology and enriched oxygen vacancy structure of fillers on electrochemical properties of composite GPEs is comprehensively investigated,thus,it is anticipated to shed new light on designing high-performance GPEs LMBs.

关键词： Nanofibers fillers Oxygen vacancies Gel polymer electrolytes Lithium metal batteries

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Multi-time Collaborative Restoration for Integrated electrical-gas Distribution Systems Based on Rolling Optimization

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 660-671页

作者： Jingyang Yun Zheng Yan Yun Zhou Peichao Zhang Weidong Hu Key laboratory of Control of Power Transmission and Conversion of Ministry of Education Department of Electrical EngineeringShanghai Jiao Tong University

This paper proposes a multi-time collaborative restoration model for integrated electricity-gas distribution sys-tems(IEGDSs)considering multiple resources after extreme weather *** on the linearized power flow constraints of the unbalanced electrical distribution system(EDS)and gas distribution system(GDS),this problem can be formulated as a mixed-integer linear programming(MILP)*** improve the efficiency and veracity of the solution,a rolling optimiza-tion based two-stage method is developed with the first stage solved by a linear approximation model,and the second stage solved by real-time updated rolling *** solving the MILP problem using rolling optimization,the proposed model and solution method achieve efficient and reliable collaborative restoration of IEGDS considering multiple resources and unbal-anced operation characteristics of *** effectiveness of the proposed model and method is validated by using an IEGDS made of a 37-bus unbalanced EDS and 11-node *** Terms-Electricity-gas system,mix-integer linear programming,power system restoration.

关键词： Electricity-gas system mix-integer linear programming power system restoration

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Neural-network-based fully distributed formation control for nonlinear multi-agent systems with event-triggered communication

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Science China(Technological Sciences) 2024年第1期67卷 209-220页

作者： ZHU GuoLiang LIU KeXin GU HaiBo LÜJinHu School of Automation Science and electrical engineering Beihang UniversityBeijing 100191China Zhongguancun laboratory Beijing 100094China

This paper investigates the consensus-based formation control problem for multi-agent systems with unknown nonlinear *** achieve the desired formation,we propose two formation controllers to achieve the desired formation,one based on system states and the other on system *** proposed controllers utilize adaptive gains to avoid global information and neural networks to estimate and compensate for *** proposed event-triggered schemes avoid continuous communication among agents and exclude the Zeno *** analysis reveals that formation errors are bounded,and numerical simulations are used to validate the effectiveness of the proposed approaches.

关键词： formation control neural network adaptive control event-triggered communication multi-agent systems

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