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High Voltage 2022年第2期7卷 302-313页

作者： Yongliang Liang Zhongyi Zhang Ke‐Jun Li Yu‐Chuan Li School of electrical engineering Shandong UniversityJinanChina Department of Electrical&Electronic Engineering Imperial College LondonSouth Kensington CampusLondonUK

Online monitoring of gases dissolved in transformer oil is widely applied.Improving the performance of dissolved gas analysis(DGA)‐based fault diagnosis methods by exploring new features of time‐series data has become an appealing topic.In this study,a new type of correlation features between characteristic gases was extracted from time‐series data based on the maximal information coefficient(MIC),and a fuzzy inference system was established.After the introduction of the principle of the MIC and a method for calculating the MIC‐based correlation features,the dominant symptom features that can be used to classify fault types were extracted through the receiver operating characteristic curve.Then,fuzzy rules were learnt,and a fuzzy inference system was designed.In addition,to improve the feasibility of the method,the Newton interpolation method was used for adaptation to the existing sampling cycle.The diagnostic results of the test data show that the proposed method has excellent per-formance and outperforms some prevailing traditional rule‐based methods as well as some artificial intelligent methods.The results also show that by exploring new cor-relation features from time‐series data based on the MIC,the performance of DGA‐based methods can be improved.

关键词： fault diagnosis coefficient

Optical RAM and integrated optical memories:a survey

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Light(Science & Applications) 2020年第1期9卷 1117-1132页

作者： Theoni Alexoudi George Theodore Kanellos Nikos Pleros department of Informatics Aristotle University of ThessalonikiThessalonikiGreece Department of Electrical&Electronic Engineering University of BristolBristolUK

The remarkable achievements in the area of integrated optical memories and optical random access memories(RAMs)together with the rapid adoption of optical interconnects in the Datacom and Computercom industries introduce a new perspective for information storage directly in the optical domain,enabling fast access times,increased bandwidth and transparent cooperation with optical interconnect lines.This article reviews state-of-the-art integrated optical memory technologies and optical RAM cell demonstrations describing the physical mechanisms of several key devices along with their performance metrics in terms of their energy,speed and footprint.Novel applications are outlined,concluding with the scaling challenges to be addressed toward allowing light to serve as both a datacarrying and data-storage medium.

关键词： RAM transparent scaling

Characteristics of pantograph‐catenary arc under low air pressure and strong airflow

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High Voltage 2022年第2期7卷 369-381页

作者： Zhilei Xu Guoqiang Gao Wenfu Wei Zefeng Yang Wenhan Xie Keliang Dong Yaguang Ma Yan Yang Guangning Wu School of electrical engineering Southwest Jiaotong UniversityChengduChina department of Research and Development Chengdu Guojia Electrical Engineering Co.LtdChengduChina School of electrical&electronic engineering Nanyang Technological UniversitySingaporeSingapore

Pantograph‐catenary arc fault is the primary factor threatening the stability of the power transmission for high‐speed railway.The motion characteristics of the pantograph‐catenary arc under low air pressure and strong airflow is significantly different from the case under atmospheric pressure.In this paper,an experimental platform of panto-graph‐catenary arc was built to investigate arc root position‐time and arc column lon-gitudinal drift height‐time characteristic curves under different air pressures and airflow velocites.Via analysing the corresponding results,it can be found that there are different arc root-arc column traction mechanisms at different stages of arc development.The arcing time and arc root stagnation time under low air pressure are significantly longer than the case under atmospheric pressure,resulting in more serious electrode ablation.The arc column longitudinal drift velocity and height are greater with the increase of airflow velocity.Two typical irregular arc motion phenomena-arc root jumping and arc reignition are observed.To clarify the internal mechanism of the above phenomenon,a magnetohydrodynamics(MHD)model of the pantograph‐catenary arc was lauched,the influence mechanism of the pantograph‐catenary arc temperature and voltage are studied,and the physical process of arc temperature oscillation is analysed.The research results provide theoretical support for arc protection in high‐altitude areas.

关键词： oscillation traction column

Data-driven Power Flow Method Based on Exact Linear Regression Equations

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Journal of Modern Power Systems and Clean Energy 2022年第3期10卷 800-804页

作者： Yanbo Chen Chao Wu Junjian Qi State Key Laboratory of Alternate electrical Power System with Renewable Energy Sources School of Electrical&Electronic EngineeringNorth China Electric Power UniversityBeijing 102206China department of electrical and Computer engineering Stevens Institute of TechnologyHobokenNJ 07030USA

Power flow(PF)is one of the most important calculations in power systems.The widely-used PF methods are the Newton-Raphson PF(NRPF)method and the fast-decoupled PF(FDPF)method.In smart grids,power generations and loads become intermittent and much more uncertain,and the topology also changes more frequently,which may result in significant state shifts and further make NRPF or FDPF difficult to converge.To address this problem,we propose a data-driven PF(DDPF)method based on historical/simulated data that includes an offline learning stage and an online computing stage.In the offline learning stage,a learning model is constructed based on the proposed exact linear regression equations,and then the proposed learning model is solved by the ridge regression(RR)method to suppress the effect of data collinearity.In online computing stage,the nonlinear iterative calculation is not needed.Simulation results demonstrate that the proposed DDPF method has no convergence problem and has much higher calculation efficiency than NRPF or FDPF while ensuring similar calculation accuracy.

关键词： Data driven exact linear regression equation Fast-decoupled power flow Newton-Raphson method

Uncertainty Management in Power System Operation

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CSEE Journal of Power and Energy Systems 2015年第1期1卷 28-35页

作者： Chaoyi Peng Shunbo Lei Yunhe Hou Felix Wu Department of Electrical&Electronic Engineering The University of Hong Kong

This paper summarizes the prevailing power system operation methods for managing the uncertainty brought by large-scale integration of renewables and active load demand.From the perspective of power system operations,uncertainty management is an important problem.In this paper,the mathematical models used for handling uncertainty are discussed,along with the pros and cons as well as future development efforts of four different operation methods.The study concludes that it is difficult to adopt a universal operation theory for mitigating the uncertainty in power system operations.Instead,it is necessary to choose the most feasible operation method that matches the specific operation requirement.

关键词： Management power system operation robust optimization stochastic optimization uncertainty

Failure investigation and asset management of combined measuring instrument transformers

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High Voltage 2021年第1期6卷 61-70页

作者： ShengJi Tee Qiang Liu Zhongdong Wang Fikri Hafid Pierre Tournet Department of Electrical&Electronic Engineering The University of ManchesterManchesterUK Research&Development Réseau de Transport d'ElectricitéParisFrance

Asset management of instrument transformers(ITs)has gained momentum in recent years due to their large population in the network and the potential adverse impacts of their increasing number of failures.This study investigates the failure cause of a family of combined measuring ITs via temperature profile simulations and consideration of moisture migration behaviour in an oil‐impregnated paper insulation system.The tem-perature difference experienced by an IT,particularly throughout summer,together with a relative saturation hysteresis phenomenon could have caused a lower dielectric strength that led to failures.The study also offers insights into factors influencing the probability of failures through analysis on the lifetime data from both graphical survival function plots and statistical Cox model.In‐service age,operating voltage level and environment appear to have an influence on failure rate.

关键词： instrument gained insulation

VANET Jamming and Adversarial Attack Defense for Autonomous Vehicle Safety

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Computers, Materials & Continua 2022年第5期71卷 3589-3605页

作者： Haeri Kim Jong-Moon Chung department of Vehicle Convergence engineering Yonsei UniversitySeoul03722Korea School of electrical&electronic engineering Yonsei UniversitySeoul03722Korea

The development of Vehicular Ad-hoc Network(VANET)technology is helping Intelligent Transportation System(ITS)services to become a reality.Vehicles can use VANETs to communicate safety messages on the road(while driving)and can inform their location and share road condition information in real-time.However,intentional and unintentional(e.g.,packet/frame collision)wireless signal jamming can occur,which will degrade the quality of communication over the channel,preventing the reception of safety messages,and thereby posing a safety hazard to the vehicle’s passengers.In this paper,VANET jamming detection applying Support Vector Machine(SVM)machine learning technology is used to classify jamming and non-jamming situations.The analysis is based on two cases which include normal traffic and heavy traffic conditions,where the results show that the probability of packet dropping will increase when many vehicles are using the wireless channel simultaneously.When using SVM classification,the most appropriate feature set applied in determining a jamming situation shows an accuracy of 98%or higher.Furthermore,more advanced jamming attacks need to be considered for preparation of more reliable and safer autonomous ITS services.Such research can use vehicular communication transmission and reception data based on selected published datasets.In this paper,an additional adversarial defense algorithm using the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)method is proposed,which assumes that evolutionary attacks of the jammer will attempt to confuse the trained classifier.The simulation results show that applying DBSCAN can improve the accuracy by elimination of outliers before conducting classification testing.

关键词： Vehicle safety VANET jamming SVM adversarial defense

Improved Control in Single Phase Inverter Grid-Tied PV System Using Modified PQ Theory

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Intelligent Automation & Soft Computing 2023年第8期37卷 2441-2457页

作者： Nur Fairuz Mohamed Yusof Dahaman Ishak Muhammad Ammirrul Atiqi Mohd Zainuri Muhammad Najwan Hamidi Zuhair Muhammed Alaas Mohamed Mostafa Ramadan Ahmed Faculty of electrical engineering&Technology Universiti Malaysia Perlis02600ArauMalaysia School of electrical&electronic engineering Universiti Sains Malaysia14300Nibong TebalMalaysia department of electrical Electronic and Systems EngineeringFaculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaSelangor43600Malaysia School of engineering Jazan UniversityJazanSaudi Arabia Faculty of Technology and Education Helwan UniversityCairoEgypt

Grid-connected reactive-load compensation and harmonic control are becoming a central topic as photovoltaic(PV)grid-connected systems diversified.This research aims to produce a high-performance inverter with a fast dynamic response for accurate reference tracking and a low total har-monic distortion(THD)even under nonlinear load applications by improving its control scheme.The proposed system is expected to operate in both stand-alone mode and grid-connected mode.In stand-alone mode,the proposed controller supplies power to critical loads,alternatively during grid-connected mode provide excess energy to the utility.A modified variable step incremental conductance(VS-InCond)algorithm is designed to extract maximum power from PV.Whereas the proposed inverter controller is achieved by using a modified PQ theory with double-band hysteresis current controller(PQ-DBHCC)to produce a reference current based on a decomposition of a single-phase load current.The nonlinear rectifier loads often create significant distortion in the output voltage of single-phase inverters,due to excessive current harmonics in the grid.Therefore,the proposed method generates a close-loop reference current for the switching scheme,hence,minimizing the inverter voltage distortion caused by the excessive grid current harmonics.The simulation findings suggest the proposed control technique can effectively yield more than 97%of power conversion efficiency while suppressing the grid current THD by less than 2%and maintaining the unity power factor at the grid side.The efficacy of the proposed controller is simulated using MATLAB/Simulink.

关键词： Hysteresis current controller incremental conductance nonlinear load PQ theory single-phase inverter

Data-driven Robust State Estimation Through Off-line Learning and On-line Matching

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Journal of Modern Power Systems and Clean Energy 2021年第4期9卷 897-909页

作者： Yanbo Chen Hao Chen Yang Jiao Jin Ma Yuzhang Lin State Key Laboratory of Alternate electrical Power System with Renewable Energy Sources School of Electrical&Electronic EngineeringNorth China Electric Power UniversityBeijing 102206China School of electrical and Information engineering University of SydneySydney 2006Australia department of electrical and Computer engineering University of MassachusettsLowellMA 01852USA

To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust state estimation (DDSE) method through off-line learning and on-line matching. At the off-line learning stage, a linear regression equation is presented by clustering historical data from supervisory control and data acquisition (SCADA), which provides a guarantee for solving the over-learning problem of the existing DDSE methods;then a novel robust state estimation method that can be transformed into quadratic programming (QP) models is proposed to obtain the mapping relationship between the measurements and the state variables (MRBMS). The proposed QP models can well solve the problem of collinearity in historical data. Furthermore, the off-line learning stage is greatly accelerated from three aspects including reducing historical categories, constructing tree retrieval structure for known topologies, and using sensitivity analysis when solving QP models. At the on-line matching stage, by quickly matching the current snapshot with the historical ones, the corresponding MRBMS can be obtained, and then the estimation values of the state variables can be obtained. Simulations demonstrate that the proposed DDSE method has obvious advantages in terms of suppressing over-learning problems, dealing with collinearity problems, robustness, and computation efficiency.

关键词： Robust state estimation historical snapshot off-line learning on-line matching collinearity

Dynamic State Estimation for Integrated Electricity-gas Systems Based on Kalman Filter

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CSEE Journal of Power and Energy Systems 2022年第1期8卷 293-303页

作者： Yanbo Chen Yuan Yao Yuzhang Lin Xiaonan Yang State Key Laboratory of Alternate electrical Power System with Renewable Energy Sources School of Electrical&Electronic EngineeringNorth China Electric Power University102206 BeijingChina Qinghai Key Laboratory of Efficient Utilization of Clean Energy Tus-Institute for Renewable EnergyQinghai UniversityXining 810016China School of engineering Xining UniversityXining 810016China School of electrical&electronic engineering North China Electric Power University102206 BeijingChina department of electrical and Computer engineering University of MassachusettsLowellMA 01852USA State Key Laboratory of Power Grid Safety and Energy Conservation China Electric Power Research Institute100192 BeijingChina

In recent years, integrated electricity-gas systems(IEGSs) have attracted widespread attention. The unifiedscheduling and control of the IEGS depends on high-precisionoperating data. To this end, it is necessary to establish anappropriate state estimation (SE) model for IEGS to filter theraw measured data. Considering that power systems and naturalgas systems have different time scales and sampling periods, thispaper proposes a dynamic state estimation (DSE) method basedon a Kalman filter that can consider the dynamic characteristicsof natural gas pipelines. First, the standardized state transitionequations for the gas system are developed by applying the finitedifference method to the partial differential equations (PDEs) ofthe gas system;then the DSE model for IEGS is formulatedbased on a Kalman filter;also, the measurements from theelectricity system and the gas system with different samplingperiods are fused to ensure the observability of DSE by using theinterpolation method. The IEEE 39-bus electricity system and the18-nodes Belgium gas system are integrated as the test systems.Simulation results verify the proposed method’s accuracy andcalculation efficiency.

关键词： Dynamic state estimation integrated electricitygas system Kalman filter two time-scale measurements transition state equation