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Analysis of high impedance faults using fractal techniques

IEEE TRANSACTIONS ON power systemS 1996年第1期11卷 435-440页

作者： Mamishev, AV Russell, BD Benner, CL Power System Automation Laboratory Department of Electrical Engineering Texas A and M University College Station TX USA

Phase currents and voltages in a distribution power system change with a certain degree of chaos when high impedance faults (HIFs) occur. This paper describes application of the concepts of fractal geometry to analyze chaotic properties of high impedance butts. Root-mean-square rather that instantaneous values of currents are used for characterization of temporal system behavior;this results in relatively short time-series available for analysis. An algorithm is presented for pattern recognition and detection of HIFs;it is based on techniques suited for analysis of relatively small data sets. Examples are given to illustrate the ability of this approach to discriminate between faults and other transients in a power system.

关键词： high impedance fault power lines fractals

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Practical High Impedance Fault Detection for Distribution Feeders

Practical High Impedance Fault Detection for Distribution Fe...

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Rural Electric power Conference

作者： C.L. Benner B.D. Russell Power System Automation Laboratory Department of Electrical Engineering Texas A and M University College Station TX USA

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Reporting bulk power system delivery point reliability

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IEEE TRANSACTIONS ON power systemS 1996年第3期11卷 1262-1267页

作者： Weber, E Adler, B Agarwal, S Allan, R Bhavaraju, M Billinton, R Blanchard, M DAquanni, R Ellis, R Endrenyi, J Garrison, D Grigg, C Luehmann, M Odom, J Preston, G Rau, N Reppen, N Salvaderi, L Schilling, M Schneider, AW Vojdani, A White, T Division of System Studies Western Area Power Administration Billings MT Reliability and Performance PECO Energy Company Philadelphia PA Electrical Energy Systems UMIST Manchester UK General Reliability CA Public Service Electric and Gas Company Newark NJ Esearch and Extension University of Saskatchewan Saskatoon SAS Canada IREQ (Hydro-Quebec) Varennes Canada Applied Resources Group Inc. Brookline MA Power System Operations Bonneville Power Administration Vancouver WA Ontario Hydro Technologies Toronto ONT Canada Duke Power Company Charlotte NC Department of Electrical and Computer Engineering Rose-Hulman Institute of Technology Terre Haute IN Consumers Power Company Jackson MI Florida Power Corp. Saint Petersburg FL Utility Dept. City of Austin Elect. Austin TX Utility Planner National Renewable Energy Laboratory Golden CO Power Technologies Inc. Schenectady NY ENEL-Planning Dept. Rome Italy Universidade Federal Fluminense Brazil MAIN Coordination Center Lombard IL Electrical Systems EPRI Palo Alto CA MAPP Coordination Center Minneapolis MN

This paper is part of an ongoing activity of the IEEE Application of Probability Methods Subcommittee to advance the probabilistic methods used to analyze Bulk power system (BPS) reliability. The objective of the Task Force is to develop a set of guidelines for measuring delivery point reliability. This involves reviewing published literature and other documentation of existing procedures, definitions, and indices. This report presents the results of the Task Force efforts to compile a useful set of terms and procedures for consistent reporting of BPS delivery point reliability.

关键词： power system reliability Guidelines power system measurements power measurement power system analysis computing Force measurement power system planning power system security power system transients power system harmonics

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An object-oriented approach to video coding via the CNN Universal Machine

An object-oriented approach to video coding via the CNN Univ...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： A. Toffels T. Roska L.O. Chua Inst. of Power Syst. & Power Econ. Tech. Hochschule Aachen Germany Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Nonlinear Electronics Laboratory at the Department of Electrical Engineering and Computer Science University of California Berkeley USA

The cellular neural network Universal Machine (CNNUM) is applied to object-oriented image compression algorithms and proves its universality as a hardware platform for future applications. The estimated processing times allow a real-time analysis of the video sequence and outdo the performance of other comparable digital devices reported.

关键词： Video coding Cellular neural networks Turing machines Image segmentation Labeling Image coding power system economics power engineering computing Video sequences Video compression

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ARCING FAULT-DETECTION FOR DISTRIBUTION FEEDERS - SECURITY ASSESSMENT IN LONG-TERM FIELD TRIALS

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IEEE TRANSACTIONS ON power DELIVERY 1995年第2期10卷 676-683页

作者： RUSSELL, BD BENNER, CL Power System Automation Laboratory Department of Electrical Engineering Texas A and M University College Station TX USA

A downed conductor, arcing fault detection system has been designed using multiple protection algorithms. An intelligent analysis system processes the outputs from several algorithms to determine the ''confidence'' that a fault exists. The design includes careful attention to discriminating arcing faults from normal system activity to ensure system security. Key to the acceptance of this system is testing under actual field conditions. The results of long term tests on five utilities are presented. The behavior of the prototype systems to staged faults, naturally occurring faults, and normal system disturbances is described. Conclusions are drawn concerning the practical viability of this system.

关键词： field experimentation Long term testing Feeders algorithms Defect detection arcing fault Safety assessment

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Analysis of high impedance faults using fractal techniques

Analysis of high impedance faults using fractal techniques

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power Industry computer Application Conference (PICA)

作者： A.V. Mamishev B.D. Russell C.L. Benner Power System Automation Laboratory Department of Electrical Engineering Texas A and M University College Station TX USA

Phase currents and voltages in a power distribution system change with a certain degree of chaos when high impedance faults (HIFs) occur. This paper describes application of the concepts of fractal geometry to analyze chaotic properties of high impedance faults. Root-mean-square rather that instantaneous values of currents are used for characterization of temporal system behavior; this results in relatively short time-series available for analysis. An algorithm is presented for pattern recognition and detection of HIFs; it is based on techniques suited for analysis of relatively small data sets. Examples are given to illustrate the ability of this approach to discriminate between faults and other transients in a power system.

关键词： Impedance Fractals Chaos power system transients Voltage power distribution Geometry Time series analysis Pattern recognition Pattern analysis

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Steady‐state security evaluation of electrical power systems by means of artificial neural network

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European Transactions on electrical power 1995年第2期5卷 91-97页

作者： Chiodo, E. Menniti, D. Testa, A. Picardi, C. Elio Chiodo (1959) received the degree in Electronics Engineering in 1985 and the Ph.D. degree in Computational Statistics both from the University of Naplefltaly. He is a Researcher at the Department of Electrical Engineering of the University of Naples and a member of the Italian Statistical Society. His areas of interest include probabilistic methods applied to electric power systems analysis. (University of Naples Fedrrico 11. Electrical Engineering Dept.via Claudio 21 1-80125 Naplefltaly T +3981/7683226 Fax+3981/2396897) Daniele Menniti (1958) received the degree in Electrical Engineering from the University of Calabria. Cosenzataly and the Ph.D. degree in Electrical Engineering from the University of NapleslItaly in 1984 and 1989 respectively. He is a researcher at the Electronic. Computer and Systems Science Department of the University of Calabria. Italy. Hiscurrent research interests concern electric power system analysis real-time control and automation. (University of Calabria Electronic Computer and Systems Science Dep. Arcavacataji Rende (CS). 1-87036 CosenzdItaly T +39984/494707. Fax +39984/4947 13) Alfredo Testa (1950) received the degree in Electrical Engineering from the University of Naples/Italy in 1975. He is an Associate Professor in Electrical Power Systems at the Department of Electrical Engineering of the University of Naples. He is engaged in researches on electrical power systems reliability and harmonic analysis. (University of Naples Federico 11. Electrical Engineering Dep. via Claudio '2 1 1-80 I25 NapleslItaly T + 39 8 I/7 68 3'2 11. Fax+3981/2396897) Ciro Picardi (1949) received the degree in Electronics Engineering from the University of Naples/Italy in 1975. He is currently Associate Professor in Process Control at the Department of Electronic Computer and System Science of the University of Calabria. Italy. His current research interests are in the area of electrical drives robotics neural networks and fuzzy control. (University of Calabria Electronic. Compu

An artificial‐neural‐network (ANN) application for steady‐state security evaluation of electrical power systems is presented. Such application is based upon a combined use of a multilayer back‐propagation neural network and of an opportune electrical system model, previously proposed by some of the authors. In the paper, the definition of steady‐state security and the problems arising from its on‐line evaluation are briefly recalled. Then, the ANN utilized is described with particular reference to the solutions adopted by the authors. Afterwards, some remarks on the system model utilized are reported. Finally, numerical applications on the AEP‐14 bus system are presented and the results obtained with different ANN configurations are analyzed. Copyright © 1995 John Wiley & Sons, Ltd.

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Multiagent fault‐diagnosis expert system in power systems

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European Transactions on electrical power 1995年第5期5卷 341-347页

作者： Wang, J.P. Trécat, J. Dr. Jianping Wang is a doctor fellow in the Faculte Polytechnique de Mons in Belgium. His current research field is parallel processing applications in power systems. Dr. Wang obtained his BS degree from Southwest Jiaotong University in P.R. Chinain 1982. From 1982 to 1990 he was appointed as an assistant lecturer. lecturer and associate professor respectively in the electrical engineering department of Southwest Jiaotong University. He obtained his Ph.D in the FacultC Polytechnique de Mons in July of 1993. (BD Dolez 3 1 FPMS B-7000 Mons Belgium T +32-65/37 41 87 Fax +32-65/37 43 00) Professor J. Trécat is a director in the power system laboratory in the Faculty Polytechnique de Mons. He obtained his Ph.D in the University of Manchester Institute of Science and Technology(UM1ST) in U.K. in 1970. He has been working in the fields of power system automation artificial intelligence application and computer vision in the Facult6 Polytechnique de Mons since 1970. He is a senior member of IEEE and he has made much contribution both in electrical engineering education and research. (BD Dolez 3 I FPMS B-7000 Mons T +32-651374185. Fax +32-6513743 00)

In order to solve the speed problem and shallow reasoning problem met in current research in fault diagnosis expert system, this paper presents a model based parallel fault diagnosis expert system for energy management systems (EMS). The Petri net model, which corresponds to the relationship between power system components and their protection systems, has been used for the inference in fault diagnosis. A multiagent parallel processing expert system, which is based on five transputers in Sun workstation, has been built for fault diagnosis purposes. The test results show that this expert system is not only fast but also has better performances. Copyright © 1995 John Wiley & Sons, Ltd.

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PERFORMANCE OF HIGH-IMPEDANCE FAULT-DETECTION ALGORITHMS IN LONG-TERM FIELD TRIALS

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ELECTRIC power systemS RESEARCH 1994年第2期31卷 71-77页

作者： RUSSELL, BD BENNER, CL Power System Automation Laboratory Department of Electrical Engineering Texas A&M University College Station TX 77843-3128 USA

Researchers at Texas A&M University's power system automation laboratory have tested the long-term performance of high-impedance fault detection algorithms at five utilities. During the test period, prototype units were installed on feeders with a wide variety of load types. They were exposed to long-term load variations, switching events, and naturally occurring faults. One unit was also exposed to 62 staged fault tests. None of the prototype units experienced any false indications. Sensitivity to staged faults was very good. Finally, during the test period, one of the prototypes experienced a non-staged high-impedance fault, it successfully detected this fault.

关键词： DIGITAL SIGNAL PROCESSING FAULT DETECTION power system PROTECTION RELAY PROTECTION

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An approach to the direct analysis of transient stability

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European Transactions on electrical power 1993年第3期3卷 241-248页

作者： Djukanovic, M.B. Sobajic, D.J. Pao, Y.‐H. Miodrag B. Djukanovic (1959) received his B.S. M.Sc. and Ph.D. degrees in Electrical Engineering from the University of Belgrade/Yugoslavia in 1982 1985 and 1992 respectively specializing in electric power systems. In 1984 he joined the Electrical Engineering Institute “Nikola Tesla” in Belgrade where he was working on the scientific studies in the field of power systems planning operation and control. In 1985 and 1990 he was appointed as a research scholar at the Royal Institute of Technology Stockholm and Case Western Reserve University Cleveland Ohio. His major in- terests are in the area of power system analysis steady-state and dynamic security and application of neural networks in electric power systems. (Electrical Engineering Institute “Nicola Tesla” ul. Koste Glavinica 8A YU-11000 Belgrad T +3811/2351-619 Fax + 3811/2351-823) Dejan J. Sobajic (1949) received the B.S.E.E. and the M.S.E.E. degrees from the University of Belgrade/Yugoslavia in 1972 and 1976 respectively and the Ph.D. degree from Case Western Reserve University Cleveland Ohio in 1988. At present he is with the Department of Electrical Engineering and Applied Physics Case Western Reserve University Cleveland. He is also the Engineering Manager of A1 WARE Inc. Cleveland. His current research interests include power system operation and control neuralnet systems and adaptive control. He is a member of the IEEE Task Force on Neural-Network Applications in Power Systems and of the IEEE Intelligent Controls Committee. He is the Chairman of the International Neural-Networks Society Special Interest Group on Power Engineering. (Case Western Reserve University Department of Electrial Engineering and Computer Sciences Glennan Building Ohio 44 106 USA T + 1216/421-2380 Fax +1216/368-8776) Yoh-Han Pao (1922) has been a Professor of Electrical Engineering and Computer Science at Case Westem Reserve University (CWRU) Cleveland Ohio since 1967. He has served as chairman of the University's Electrical Engineering Department

The Transient Energy Function (TEF) method has been intensely investigated over the last decade as a reliable and accurate tool for transient stability assessment of multimachine power systems. In this paper we propose the Potential Energy Boundary Surface (PEBS) based method for direct analysis of transient stability. The critical value of transient energy and the Critical Clearing Time (T_CCT) are evaluated without the need for successive calculation and memorization of the system kinetic and potential energy values along the sustained fault trajectory. The method is used for determination of output features in the training phase of the neural‐net based transient security assessment. The proposed approach is tested on the well‐known ten‐generator New England test system demonstrating the validity and accuracy of obtained results. Copyright © 1993 John Wiley & Sons, Ltd.

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