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Identification Method for Single-line-to-ground Faults with Line Break Based on Phasor Measurement in Distribution Networks

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Journal of Modern power Systems and Clean Energy 2023年第3期11卷 907-916页

作者： Yadong Liu Zichang Li Yingjie Yan Guanghui He Jian Fang Kejun Li Xiuchen Jiang institute of Intelligent power Transmission and Distribution.Shanghai Jiao Tong University Shanghai 201100China electric power test institute of guangzhou power supply bureau co. Ltd.Guangzhou 510420China IEEE

The single-line-to-ground faults with line breaks(SLGFs-LBs)occur more and more frequently in distribution networks and can cause major safety accidents.It is difficult to distinguish the single-line-to-ground faults(SLGFs)in resonant grounding systems and ungrounding systems due to the same electrical characteristics on the source side and uncertain operation co.ditions of distribution networks.This paper proposes a method for distinguishing SLGFs-LBs and SLGFs.First,the source-side and load-side voltage characteristics of SLGFs and SLGFs-LBs are analyzed,and the phase difference between the voltages of the fault phase and non-fault phase on the load side is selected as the identification criterion.Phasor measurement units(PMUs)are selected as measuring devices.Then,the effects of operation co.ditions and external devices in distribution networks on the proposed method are discussed,and the phase errors caused by them are calculated to co.rect the identification method.Finally,the field testing and simulation experiments are co.ducted to verify the effectiveness and robustness of the proposed method.

关键词： Distribution network phase measurement unit single-line-to-ground fault(SLGF) identification method influencing factor

Risk Management of Weather-related Failures in Distribution Systems Based on Interpretable Extra-trees

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Journal of Modern power Systems and Clean Energy 2023年第6期11卷 1868-1877页

作者： Ying Du Yadong Liu Yingjie Yan Jian Fang Xiuchen Jiang Department of electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China guangzhou power supply bureau co. Ltd.Electric Power Test InstituteGuangzhou 510000China

Weather-related failures significantly challenge the reliability of distribution systems. To enhance the risk management of weather-related failures, an interpretable extra-trees based weather-related risk prediction model is proposed in this study. In the proposed model, the interpretability is successfully introduced to extra-trees by analyzing and processing the paths of decision trees in extra-trees. As a result, the interpretability of the proposed model is reflected in the following three respects: it can output the importance, co.tribution, and threshold of weather variables at high risk. The importance of weather variables can help in developing a long-term risk prevention plan. The co.tribution of weather variables provides targeted operation and maintenance advice for the next prediction period. The threshold of weather variables at high risk is critical in further preventing high risks. co.pared with the black-box machine learning risk prediction models, the proposed model overco.es the application limitations. In addition to generating predicted risk levels, it can also provide more guidance information for the risk management of weather-related failures.

关键词： Extra-tree machine learning interpretability weather-related failure distribution system

Stochastic Accelerated Alternating Direction Method of Multipliers for Hedging co.munication Noise in co.bined Heat and power Dispatch

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CSEE Journal of power and Energy Systems 2023年第2期9卷 696-706页

作者： Zhigang Li Xinyu Liang Fan Hu Wen Xiong Renbo Wu J.H.Zheng Q.H.Wu School of electric power Engineering South China University of TechnologyGuangzhou 510641China guangzhou power supply bureau Guangdong Power Grid Co.LtdGuangzhouChina

co.bined heat and power dispatch(CHPD)opens a new window for increasing operational flexibility and reducing wind power curtailment.electric power and district heating systems are independently co.trolled by different system operators;therefore,a decentralized solution paradigm is necessary for CHPD,in which only minor boundary information is required to be exchanged via a co.munication network.However,a nonideal co.munication environment with noise co.ld lead to divergence or inco.rect solutions of decentralized algorithms.To bridge this gap,this paper proposes a stochastic accelerated alternating direction method of multipliers(SA-ADMM)for hedging co.munication noise in CHPD.This algorithm provides a general framework to address more types of co.straint sets and separable objective functions than the existing stochastic ADMM.Different from the single noise sources co.sidered in the existing stochastic approximation methods,co.munication noise from multiple sources is addressed in both the local calculation and the variable update stages.Case studies of two test systems validate the effectiveness and robustness of the proposed SAADMM.

关键词： Alternating direction method of multipliers co.bined heat and power dispatch co.munication noise decentralized optimization

co.relation knowledge extraction based on data mining for distribution network planning

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Global Energy Interco.nection 2023年第4期6卷 485-492页

作者： Zhifang Zhu Zihan Lin Liping Chen Hong Dong Yanna Gao Xinyi Liang Jiahao Deng guangzhou power supply bureau of Guangdong power Grid co. Ltd.Guangzhou 510000P.R.China South China University of Technology School of Electric PowerGuangzhou 510000P.R.China

Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the co.relations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and co.relation knowledge of existing problems in the network was obtained.A data-mining model based on co.relation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray co.relation method.The Apriori algorithm was used to extract co.relation knowledge from the operational data of the distribution network and obtain strong co.relation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong co.relation rules of the model output.In this study,the co.relation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the co.fidence of the co.relation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.

关键词： Distribution network planning Data mining Apriori algorithm Gray co.relation analysis Chi-square test

The Averaged-value Model of a Flexible power Electronics Based Substation in Hybrid AC/DC Distribution Systems

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CSEE Journal of power and Energy Systems 2022年第2期8卷 452-464页

作者： Hong Liu Zhanfeng Deng Xialin Li Li Guo Di Huang Shouqiang Fu Xiangyu Chen Chengshan Wang the Key Laboratory of Smart Grid of Ministry of Education Tianjin UniversityTianjin 300072China the State Key Laboratory of Advanced power Transmission Technology Global Energy Interconnection Research InstituteBeijing 100220China the State Grid Jibei electric power Eco.omic Research institute Beijing 100038China State Key Laboratory of Reliability and Intelligence of electrical Equipment Hebei University of TechnologyTianjinChina the guangzhou power supply bureau of Guangdong Grid co. Ltd.Guangzhou 510620China

The co.cept of a flexible power electronics substation(FPES)was first applied in the Zhangbei DC distribution network demonstration project.As a multi-port power electronics transformer(PET)with different AC and DC voltage levels,the FPES has adopted a novel topology integrating modular multilevel co.verter(MMC)and four-winding medium frequency transformer(FWMFT)based multiport DC-DC co.verter,which can significantly reduce capacitance in each sub-module(SM)of a MMC and also save space and co.t.In this paper,in order to accelerate speed of electromagnetic transient(EMT)simulations of FPES based hybrid AC/DC distribution systems,an averaged-value model(AVM)is proposed for efficient and accurate representation of FPES.Assume that all SM capacitor voltages are perfectly balanced in the MMC,then the MMC behavior can be modeled using co.trolled voltage sources based on modulation voltages from co.trol systems.In terms of the averaged current transfer characteristics among the windings of the FWMFT,we co.sider that all multiport DC-DC co.verters are co.trolled with the same dynamics,a lumped averaged model using co.trolled current and voltage sources has been developed for these four-port DC-DC co.verters co.nected to the upper or lower arms of the MMC.The presented FPES AVM model has been tested and validated by co.parison with a detailed IGBT-based EMT model.Results show that the AVM is significantly more efficient while maintaining its accuracy in an EMT simulation.

关键词： Averaged-value model(AVM) flexible power electronics substation(FPES) four-winding medium frequency transformer(FWMFT) hybrid AC/DC distribution systems modular multilevel co.verter(MMC) multiport DC-DC co.verter

Investigation of Atmospheric Pressure Dielectric Barrier Glow Discharge in Argon/Ammonia Mixture

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高电压技术 2013年第9期39卷 2254-2259页

作者： ZHANG Zenghui ZHANG Guanjun SHAO Xianjun CHANG Zhengshi GU Chtmhui Shenzhen power supply co. Ltd. Shenzhen 518000 China State Key Laboratory of electrical Insulation and power Equipment Xi'an Jiaotong University Xi'an 710049 China electric power test and Research institute Guangzhou Power Supply Co. Ltd. Guangzhou 510410 China

In this paper,the influence of ammonia admixture on argon discharge properties is investigated.electrical measurements,as well as ten-nanoseco.ds-exposure photographs taken by an intensified charge-co.pled device(ICCD)camera,are employed to co.firm the existence of atmospheric pressure glow discharge(APGD)in Ar/NH3mixture.The breakdown voltage and transition voltage between APGD and filamentary discharge are studied at various ammonia co.centrations.The results show that a small amount of NH3can lead to APGD due to the Penning ionization of NH3molecules by metastable argon,and the breakdown voltage increases with the growth in NH3co.centrations owing to the electronegative feature of NH3.The optical emission spectrum of Ar/NH3APGD is analyzed.Besides,gas temperature is estimated at 327 K by the diagnoses of the OH(A-X)(0,0)band of the spectrum.

关键词：大气压辉光放电混合物氩气介质阻挡 APGD 氨常压电荷耦合器件

Application status and development trends for intelligent perception of distribution network

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High Voltage 2021年第6期6卷 938-954页

作者： Yingjie Yan Yadong Liu Jian Fang Yuefeng Lu Xiuchen Jiang Department of electrical Engineering Shanghai Jiao Tong UniversityShanghaiChina power test Research institute of guangzhou power supply bureau of Guangdong power Grid co. Ltd.GuangzhouChina China Southern power Grid GuangzhouChina

Intelligent perception is the co.nerstone of digitalisation of power grid.Due to the closest co.nection with users,the information perception ability of distribution network directly affects the reliability of power supply.Distribution network has a wide range of geographical distribution and equipment types.The application of intelligent perception is with high co.plexity and dynamics under the limitation of both technology and management.Therefore,the study first sorts out the current application status of intel-ligent perception technology and equipment in distribution network from three appli-cation fields including distribution automation,metering systems,and inspection.Then,the co.straints of existing intelligent perception applications and the key points of further research are pointed out.Finally,the development trends of intelligent perception technology in distribution network are presented from the three aspects of basic tech-nology,perception equipment,and advanced applications.With the improvement of sensing,co.munication,energy acquisition,chips and perception equipments,the depth and breadth of advanced applications in distribution network will be expanded.The research results can provide references for the follow‐up research and practice of intel-ligent perception in distribution networks.

关键词： network distribution perception

A Day-ahead Eco.omic Dispatch Method co.sidering Extreme Scenarios Based on Wind power Uncertainty

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CSEE Journal of power and Energy Systems 2019年第2期5卷 224-233页

作者： Jian Xu Bao Wang Yuanzhang Sun Qi Xu Ji Liu Huiqiu Cao Haiyan Jiang Ruobing Lei Mengjun Shen School of electrical Engineering and Automation Wuhan UniversityWuhan430072China guangzhou power supply bureau co. Ltd.Guangzhou510620China electric power Research institute of Guangdong power Grid co. Ltd.Guangzhou510080China Suzhou power supply bureau co. Ltd.Suzhou215000China

As the intermittency of wind power is a growing co.cern in the day-ahead eco.omic dispatch,this paper proposes a day-ahead eco.omic dispatch method co.sidering extreme scenarios of wind power by using an uncertainty set.The uncertainty set inspired by robust optimization is used to describe wind power intermittency in this paper.Four extreme scenarios based on the uncertainty set are formulated to represent the worst cases of wind power fluctuation.An eco.omic dispatch method co.sidering the co.ts of both load shedding and wind curtailment is proposed.The eco.omic dispatch model can be easily solved by a quadratic programming method owing to the introduction of four extreme scenarios and the uncertainty set of wind power.Simulation is done using the IEEE 30-bus system and the results verify the effectiveness of the proposed method.

关键词： Eco.omic dispatch extreme scenarios uncertainty set wind power

Fault diagnosis of electric transformers based on infrared image processing and semi-supervised learning

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Global Energy Interco.nection 2021年第6期4卷 596-607页

作者： Jian Fang Fan Yang Rui Tong Qin Yu Xiaofeng Dai Key Laboratory of Middle-low Voltage electric Equipment Inspection and testing of China Southern power Grid co. LtdGuangzhou 510620P.R.China guangzhou power supply bureau of Guangdong power Grid co. LtdGuangzhou 510620P.R.China

It is crucial to maintain the safe and stable operation of distribution transformers,which co.stitute a key part of power systems.In the event of transformer failure,the fault type must be diagnosed in a timely and accurate manner.To this end,a transformer fault diagnosis method based on infrared image processing and semi-supervised learning is proposed herein.First,we perform feature extraction on the co.lected infrared-image data to extract temperature,texture,and shape features as the model reference vectors.Then,a generative adversarial network(GAN)is co.structed to generate synthetic samples for the minority subset of labelled samples.The proposed method can learn information from unlabeled sample data,unlike co.ventional supervised learning methods.Subsequently,a semi-supervised graph model is trained on the entire dataset,i.e.,both labeled and unlabeled data.Finally,we test the proposed model on an actual dataset co.lected from a Chinese electricity provider.The experimental results show that the use of feature extraction,sample generation,and semi-supervised learning model can improve the accuracy of transformer fault classification.This verifies the effectiveness of the proposed method.

关键词： Transformer Fault diagnosis Infrared image Generative adversarial network Semi-supervised learning