检索结果-南通市图书馆

Effects of cross-Kerr coupling on transmission spectrum of double-cavity optomechanical system

在线全文

学校读者我要写书评

暂无评论

Chinese physics B 2024年第6期33卷 390-396页

作者：陈立滕秦立国田立君黄接辉周南润龚尚庆 school of Mathematics Physics and StatisticsShanghai University of Engineering ScienceShanghai 201620China Department of physics Shanghai UniversityShanghai 200444China school of electrical engineering Shanghai University of Engineering ScienceShanghai 201620China school of physics East China University of Science and TechnologyShanghai 200237China

We theoretically study the transmission spectrum of the cavity field in a double-cavity optomechanical system with cross-Kerr(CK) effect. The system consists of two tunneling coupling optomechanical cavities with a mechanical resonator as a coupling interface. By doping CK medium into the mechanical resonator, CK couplings between the cavity fields and the mechanical resonator are introduced. We investigate the effects of CK coupling strength on the transmission spectrum of the cavity field, including the transmission rate, nonreciprocity and four-wave mixing(FWM). We find that the transmission spectrum of the probe field can show two obvious transparent windows, which can be widened by increasing the CK coupling strength. For the transmission between the two cavity fields, the perfect nonreciprocity and reciprocity are present and modulated by CK coupling and phase difference between two effective optomechanical couplings. In addition, the effects of the optomechanical and CK couplings on FWM show that the single peak of FWM is split into three symmetrical peaks due to the introduction of the CK effect.

关键词： cross-Kerr transmission rate nonreciprocity four-wave mixing

Periodic event-triggered secure consensus for networked mechanical systems under Denial-of-Service attacks

在线全文

学校读者我要写书评

暂无评论

Control Theory and Technology 2024年第1期22卷 1-13页

作者： Shiqi Zheng Zhipeng Li Chao Zhai Peng Shi school of Automation China University of GeosciencesWuhan430074HubeiChina school of electrical and Electronic engineering The University of AdelaideAdelaideSA5005Australia school of Electronic Electrical Engineering and PhysicsFujian University of TechnologyFuzhou350100FujianChina

This paper concentrates on the secure consensus problem of networked mechanical/Euler–Lagrange systems.First,a new periodic event-triggered(PET)secure distributed observer is proposed to estimate the leader information.The proposed distributed observer only relies on the PET data from its neighbors,which can significantly reduce the communication and computational burden.More importantly,it is secure in the sense that it can work normally regardless of the Denial-of-Service(DoS)attacks.Second,based on the proposed distributed observer,an adaptive fuzzy control law is proposed for each Euler–Lagrange system.A PET mechanism is integrated into the controller,which can reduce the control update.This is helpful for both energy saving and fault tolerance of actuators.Moreover,the PET mechanism naturally makes the controller easy to be implemented in digital platform.The property of fuzzy logic systems and Gronwall inequality are skillfully utilized to show the stability of the closed-loop system.Finally,the proposed control scheme is verified on real Euler–Lagrange systems,which contain a robot manipulator and several servo motors.

关键词： Output regulation Mechanical/Euler-Lagrange systems Periodic event-triggered mechanism Denial-of-Service attacks

Analysis of China's Electricity Price and Electricity Burden of Basic Industries under the Carbon Peak Target before 2030

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

CSEE Journal of Power and Energy Systems 2024年第2期10卷 481-491页

作者： Yue Qiu Suyang Zhou Wei Gu Xiao-Ping Zhang school of electrical engineering Southeast UniversityNanjingChina school of Electronic Electrical and System EngineeringUniversity of BirminghamU.K.

The Chinese government is deepening reformation of electricity prices during the 14th Five Year Plan period and has set a carbon emission reduction target of reaching carbon peak before 2030.In this context,will the carbon emission target influence electricity pricing and will electricity price influence competitiveness of Chinese main industries are two questions needing to be answered.This paper compares China's electricity price level with the selected major countries in the world,and four typical industries are selected to evaluate their electricity burden respectively.Then,the correlation between residential electricity price and industrial electricity price and the influencing factors is analyzed,from the perspectives of scale,structure and technology.According to the model obtained by regression analysis,the electricity price level and corresponding residential and industrial electricity burden in 2025 and 2030 are forecasted.Index Terms-Electricity burden,industrial electricity price,regression analysis,residential electricity price.

关键词： Electricity burden industrial electricity price regression analysis residential electricity price

Research of caged dynamics of clusters center atoms in Pd_(82)Si_(18) amorphous alloy

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese physics B 2024年第4期33卷 623-629页

作者：邓永和陈贝祁清华李兵兵高明文大东王小云彭平 school of Computational Science and Electronics Hunan Institute of EngineeringXiangtan 411104China school of physics and Mechanical&electrical engineering Jishou UniversityJishou 416000China school of Materials Science and engineering Hunan UniversityChangsha 410082China

To date,there is still a lack of a comprehensive explanation for caged dynamics which is regarded as one of the intricate dynamic behaviors in amorphous alloys.This study focuses on Pd_(82)Si_(18)as the research object to further elucidate the underlying mechanism of caged dynamics from multiple perspectives,including the cage's lifetime,atomic local environment,and atomic potential energy.The results reveal that Si atoms exhibit a pronounced cage effect due to the hindrance of Pd atoms,resulting in an anomalous peak in the non-Gaussian parameters.An in-depth investigation was conducted on the caged dynamics differences between fast and slow Si atoms.In comparison to fast Si atoms,slow Si atoms were surrounded by more Pd atoms and occupied lower potential energy states,resulting in smaller diffusion displacements for the slow Si atoms.Concurrently,slow Si atoms tend to be in the centers of smaller clusters with coordination numbers of 9 and 10.During the isothermal relaxation process,clusters with coordination numbers 9 and 10 have longer lifetimes,suggesting that the escape of slow Si atoms from their cages is more challenging.The findings mentioned above hold significant implications for understanding the caged dynamics.

关键词： caged dynamics Pd_(82)Si_(18) amorphous alloy fast and slow atoms clusters lifetime

A Projection and Decomposition Approach for Multi-agent Coordinated Scheduling in Power Systems

在线全文

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 991-996页

作者： Haifeng Qiu Zhigang Li Hongjun Gao Hung Dinh Nguyen Veerapandiyan Veerasamy Hoay Beng Gooi IEEE the school of electrical and Electronic engineering Nanyang Technological University school of Electric Power engineering South China University of Technology the College of electrical engineering Sichuan University

Aiming at multi-agent coordinated scheduling problems in power systems under uncertainty, a generic projection and decomposition(P&D) approach is proposed in this letter. The canonical min-max-min two-stage robust optimization(TSRO) model with coupling constraints is equivalent to a concise robust optimization(RO) model in the version of mixed-integer linear programming(MILP) via feasible region projection. The decentralized decoupling of the non-convex MILP problem is realized through a dual decomposition algorithm, which ensures the fast convergence to a high-quality solution in the distributed optimization. Numerical tests verify the superior performance of the proposed P&D approach over the existing distributed TSRO method.

关键词： Uncertainty Couplings Power systems Optimization Computational modeling Convergence Processor scheduling

Coordinated Dispatch Based on Distributed Robust Optimization for Interconnected Urban Integrated Energy and Transmission Systems

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 840-851页

作者： Wei Xu Yufeng Guo Tianhui Meng Yingwei Wang Jilai Yu the school of electrical engineering and Automation Harbin Institute of Technology

To improve the economic efficiency of urban integrated energy systems(UIESs) and mitigate day-ahead dispatch uncertainty, this paper presents an interconnected UIES and transmission system(TS) model based on distributed robust optimization. First, interconnections are established between a TS and multiple UIESs, as well as among different UIESs, each incorporating multiple energy forms. The Bregman alternating direction method with multipliers(BADMM) is then applied to multi-block problems, ensuring the privacy of each energy system operator(ESO). Second, robust optimization based on wind probability distribution information is implemented for each ESO to address dispatch uncertainty. The column and constraint generation(C&CG) algorithm is then employed to solve the robust model. Third, to tackle the convergence and practicability issues overlooked in the existing studies, an external C&CG with an internal BADMM and corresponding acceleration strategy is devised. Finally, numerical results demonstrate that the adoption of the proposed model and method for absorbing wind power and managing its uncertainty results in economic benefits.

关键词： Heating systems Convex functions Optimization Uncertainty Pipelines Distributed algorithms Convergence

Deterministic and Robust Volt-var Control Methods of Power System Based on Convex Deep Learning

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 719-729页

作者： Qing Ma Changhong Deng IEEE the school of electrical engineering and Automation Wuhan University

Volt-var control(VVC) is essentially a non-convex optimization problem due to the non-convexity of power flow(PF) constraints, resulting in the difficulty in obtaining the optimum without convexity conversion. The existing second-order cone method for the convexity conversion often leads to a sharp increase in PF constraints and optimization variables, which in turn increases the optimization difficulty or even leads to optimization failure. This paper first proposes a deterministic VVC method based on convex deep learning power flow(DLPF). This method uses the input convex neural network(ICNN) to establish a single convex mapping between state parameters and node voltage to complete the convexity conversion while the optimization variables only correspond to reactive power equipment, which can ensure the global optimum with extremely fast computation speed. To cope with the impact brought by the uncertainty of distributed energy and omit the additional worst scenario search of traditional robust VVC, this paper proposes robust VVC method based on convex deep learning interval power flow(DLIPF), which continues to adopt ICNN to establish another convex mapping between state parameters and node voltage interval. Combining DLIPF with DLPF, this method decreases the modeling and optimization difficulty of robust VVC significantly. Test results on 30-bus, 118-bus, and 200-bus systems prove the correctness and rapidity of the proposed methods.

关键词： Optimization Reactive power Mathematical models Deep learning Uncertainty Load flow Programming

Day-ahead Voltage-stability-constrained Network Topology Optimization with Uncertainties

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 730-741页

作者： Dingli Guo Lei Wang Ticao Jiao Ke Wu Wenjing Yang the school of electrical and Electronic engineering Shandong University of Technology

A day-ahead voltage-stability-constrained network topology optimization(DVNTO) problem is proposed to find the day-ahead topology schemes with the minimum number of operations(including line switching and bus-bar splitting) while ensuring the sufficient hourly voltage stability margin and the engineering operation requirement of power systems. The AC continuation power flow and the uncertainty from both renewable energy sources and loads are incorporated into the formulation. The proposed DVNTO problem is a stochastic, largescale, nonlinear integer programming problem. To solve it tractably, a tailored three-stage solution methodology, including a scenario generation and reduction stage, a dynamic period partition stage, and a topology identification stage, is presented. First, to address the challenges posed by uncertainties, a novel problem-specified scenario reduction process is proposed to obtain the representative scenarios. Then, to obtain the minimum number of necessary operations to alter the network topologies for the next 24-hour horizon, a dynamic period partition strategy is presented to partition the hours into several periods according to the hourly voltage information based on the voltage stability problem. Finally, a topology identification stage is performed to identify the final network topology scheme. The effectiveness and robustness of the proposed three-stage solution methodology under different loading conditions and the effectiveness of the proposed partition strategy are evaluated on the IEEE 118-bus and 3120-bus power systems.

关键词： Power system stability Switches Uncertainty Stability criteria Network topology Topology Renewable energy sources

Optimal Operation Strategy Analysis with Scenario Generation Method Based on Principal Component Analysis,Density Canopy,and K-medoids for Integrated Energy Systems

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 89-100页

作者： Bingtuan Gao Yunyu Zhu Yuanmei Li school of electrical engineering Southeast UniversityNanjingChina

The operation of integrated energy systems(IESs)is confronted with great challenges for increasing penetration rate of renewable energy and growing complexity of energy forms.Scenario generation is one of ordinary methods to alleviate the system uncertainties by extracting several typical scenarios to represent the original high-dimensional data.This paper proposes a novel representative scenario generation method based on the feature extraction of panel data.The original high-dimensional data are represented by an aggregated indicator matrix using principal component analysis to preserve temporal variation.Then,the aggregated indicator matrix is clustered by an algorithm combining density canopy and K-medoids.Together with the proposed scenario generation method,an optimal operation model of IES is established,where the objective is to minimize the annual operation costs considering carbon trading cost.Finally,case studies based on the data of Aachen,Germany in 2019 are performed.The results indicate that the adjusted rand index(ARI)and silhouette coefficient(SC)of the proposed method are 0.6153 and 0.6770,respectively,both higher than the traditional methods,namely K-medoids,K-means++,and density-based spatial clustering of applications with noise(DBSCAN),which means the proposed method has better accuracy.The error between optimal operation results of the IES obtained by the proposed method and all-year time series benchmark value is 0.1%,while the calculation time is reduced from 11029 s to 188 s,which verifies that the proposed method can be used to optimize operation strategy of IES with high efficiency without loss of accuracy.

关键词： Scenario generation principal component analysis(PCA) density canopy K-medoids integrated energy system