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IEEE Region 10 International Conference TENCON

作者： Norasage Pattanadech Phethai Nimsanong Electrical Engineering Dept King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Power System Operation and Control Section Power System Control Dept Metropolitan Electricity Authority Bangkok Thailand

This paper represents a partial discharge (PD) classification technique by using learning vector quantization (LVQ) network model. LVQ model was not only implemented with the PD test data but also combined with the principal component analysis (PCA), so called, PCA-LVQ for a data reduction. In this research work, both LVQ model and PCA-LVQ model were investigated. PD phenomena, corona at high voltage side in air (CHV), corona at low voltage side in air (CLV), surface discharge (SF), and internal discharge (IN) were simulated in the shielding room. Electromagnetic wave due to PD phenomena was detected using a log-periodic antenna and recorded employing a spectrum analyzer. 80 experiments in total were performed for CHV, CLV, SF and IN. The original independent variables for each classification model, skewness and kurtosis of each period of the captured signals, were calculated. Then, 60% of the experimented data was used as a training data for the PD classification models. Another 40% experimented data was used to evaluate the performance of the designed PD classification models both LVQ and PCA-LVQ models. Besides, noise signals were generated with computer program for testing the efficiency of these models. The peak of noise signal was set up at 10%, 20% and 30% of the peak value of the PD signal. These noise signals were added with the PD signals to generated a mixed noise - PD signal. Then, the mixed noise - PD signals were used to evaluate the performance of the PD classification models. It was found that the designed LVQ model can predict PD patterns without noise signal with the accuracy 100% whereas the PCA-LVQ model provided more than 87.5% accuracy of PD classification. The prediction ability of LVQ PD classification models decreased sharply especially for CHV when this model was tested by the mixed noise-PD signals. Whereas the prediction accuracy of PCA-LVQ model was more robust to the noise signals than LVQ model.

关键词： Partial discharges Mathematical model Noise Discharges (electric) Predictive models Data models Corona

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Effect of training methods on the accuracy of PCA-KNN partial discharge classification model

Effect of training methods on the accuracy of PCA-KNN partia...

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IEEE Region 10 International Conference TENCON

作者： Norasage Pattanadech Phethai Nimsanong Electrical Engineering Dept King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Power System Operation and Control Section 2 Metropolitan Electricity Authority Bangkok Thailand

The aim of this paper is to describe the effect of training methods on the accuracy of PCA-KNN partial discharge (PD) classification model. This model used principal component analysis (PCA) combined with k-nearest neighbor (KNN) model, so called, PCA-KNN PD classification model for PD pattern classification. PD phenomena, corona at high voltage side in air (CHV), corona at low voltage side in air (CLV), surface discharge (SF), and internal discharge (IN) were experimented in the shielding room. Electromagnetic wave due to PD phenomena was detected using a log-periodic antenna and recorded employing a spectrum analyzer. 80 PD experiments in total were performed. The original independent variables for the classification model, skewness and kurtosis of each period of the captured signals, were calculated. To study the effect of training methods: two patterns for data training, odd/even and block training methods were investigated. In case of the block training method, the effect of training data number can be examined as well. Besides, noise signals were generated with the computer program and trained into the PD classification models. The peak of noise signal was set up at 30% of the peak value of the PD signal. These noise signals were added with the PD signals to generated a mixed noise - PD signal. Then, the mixed noise - PD signals were used to evaluate the performance of the PCA-KNN PD classification model. It was found that the block data training method provided the higher accuracy PD classification compared with the odd/event data training method. The block training method with 80% training data/20% testing data gave the highest accuracy (95% correction) for PD classification without noise signal. However, this training technique provided the lowest accuracy (56.25% correction) for PD classification with the mixed noise-PD signals.

关键词： Partial discharges Training Noise Accuracy Discharges (electric) Training data Testing

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Effect of noise signals on partial discharge classification models

Effect of noise signals on partial discharge classification ...

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IEEE Region 10 International Conference TENCON

作者： Norasage Pattanadech Phethai Nimsanong Electrical Engineering Dept King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Power System Operation and Control Section 2 Metropolitan Electricity Authority Bangkok Thailand

This document proposes the comparison of four statistical classification models for partial discharge (PD) classification as follows: k-nearest neighbors (KNN) model, probabilistic neural network (PNN) model, and other two statistical models using principal component analysis (PCA) for a data reduction approach combined with KNN and PNN models, so called, PCA-KNN model and PCA-PNN model. PD phenomena, corona at high voltage side in air (CHV), corona at low voltage side in air (CLV), surface discharge (SF), and internal discharge (IN) were simulated and measured in the shielding room. Electromagnetic wave due to PD phenomena was detected using a log-periodic antenna and recorded employing a spectrum analyzer. 80 experiments in total were performed for CHV, CLV, SF, and IN. The original independent variables for each classification model, skewness and kurtosis of each period of the captured signals, were calculated. Then, 60% of experimented data was used as a training data for the PD classification model. Another 40% experimented data was used to evaluate the performance of the designed PD classification models. Besides, noise signals were generated with computer program and trained into the PD classification model as well. The peak of noise signal was set up at 10%, 20% and 30% of the peak value of the PD signal. These noise signals were added with the PD signals to generate a mixed noise - PD signal. Then, the mixed noise - PD signals were used to evaluate the performance of the PD classification models. It was found that the designed KNN, PNN, PCA-KNN and PCA - PNN model can predict PD patterns without noise signal with the accuracy 100%. Noise signals with amplitude of 20% or more of peak value of PD signal have obviously influence the accuracy of PD pattern classification. The combination of PCA with KNN model can improve the ability of PD classification compared with KNN PD classification model. However, it seems that PCA provided negative effect when PCA was c

关键词： Partial discharges Noise Principal component analysis Discharges (electric) Atmospheric modeling Data models Training

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Differential energy based microgrid protection against fault conditions

Differential energy based microgrid protection against fault...

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2012 IEEE PES Innovative Smart Grid Technologies, ISGT 2012

作者： Samantaray, S.R. Joos, Geza Kamwa, I. School of Electrical Sciences Indian Institute of Technology Bhubaneswar-751013 India Department of Electrical and Computer Engineering McGill University McConnell 633 3480 University Street Montreal QC H3A 2A7 Canada Hydro-Quebec/IREQ Power System Analysis Operation and Control Varennes QC J3X 1S1 Canada

ISBN: (纸本)9781457721588

A differential energy based fault protection in microgrid is presented in this paper. Initially the currents at the respective buses are retrieved and processed through a novel time-frequency transform known as S-transform to generate time-frequency contours. Spectral energy content of the time-frequency contours of fault current signals are calculated and differential energy is computed to register the fault patterns in the microgrid at grid-connected and islanded mode. The proposed scheme is tested for different shunt faults (symmetrical and unsymmetrical) and High Impedance Faults (HIF) in the microgrid with radial and loop structure. The results based on extensive study indicate that the differential energy based protection scheme can reliably protect the microgrid against different fault situations. © 2012 IEEE.

关键词： Mathematical transformations

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Optimized quality factor of fractional order analog filters with band-pass and band-stop characteristics

Optimized quality factor of fractional order analog filters ...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Anindya Pakhira Saptarshi Das Anish Acharya Indranil Pan Suman Saha Department of Instrumentation and Electronics Engineering Jadavpur University Kolkata India Department of Power Engineering Jadavpur University Kolkata India MERG Energy Environment Modelling and Minerals E2M2) Research Section Department of Earth Science and Engineering Imperial College London London UK Drives and Control System Technology Group CSIR-Central Mechanical Engineering Research Institute Durgapur India

ISBN: (纸本)9781467356930

Fractional order (FO) filters have been investigated in this paper, with band-pass (BP) and band-stop (BS) characteristics, which can not be achieved with conventional integer order filters with orders lesser then two. The quality factors for symmetric and asymmetric magnitude response have been optimized using real coded Genetic Algorithm (GA) for a user specified center frequency. Parametric influence of the FO filters on the magnitude response is also illustrated with credible numerical simulations.

关键词： Numerical simulation Filtering Ear

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Decision tree based fault detection and classification in distance relaying

Engineering Intelligent Systems

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Engineering Intelligent systems 2011年第3期19卷 139-147页

作者： Samantaray, S.R. Kamwa, I. Joos, Geza School of Electrical Sciences Indian Institute of Technology Bhubaneswar Odisha India Hydro-Quebec/IREQ Power System Analysis Operation and Control Varennes QC J3X 1S1 Canada Department of Electrical and Computer Engineering McGiII University McConnell 6333480 University Street Montreal QC H3A 2A7 Canada

This paper presents a new approach for fault detection and classification in transmission line using Decision Tree (DT). The DT based fault detection algorithm uses 1/4th cycle data of fault currents from fault inception, to generate the optimal decision tree for fault detection. Similarly, the DT based classification algorithm takes half cycle data from fault inception of three phase currents along with zero sequence current, and constructs the optimal decision tree for classifying all 10 types of shunt faults in the transmission line fault process. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network. The results indicate that the proposed method can reliably detect and classify faults in transmission line within the sub-cycle time-frame while keeping the computational burden sufficiently low to make a real-time implementation feasible. © 2011 CRL Publishing Ltd.

关键词： Decision trees

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Voltage control in power system using expert system based on SCADA system

Voltage control in power system using expert system based on...

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IEEE Winter Meeting power Engineering Society

作者： C. Pimpa S. Premrudeepreechacharn System Dispatch Section 2 Regional System Control and Operation Division Northern Regional Operation Department EGAT Phitsanulok Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand

ISBN: (纸本)0780373227

This paper presents the type of expert system for controlling the 22 kV voltage levels of a power system in the northern region of Thailand based on the SCADA system. At present, for the operation, the operators have to make decisions by their knowledge and experience to control the voltage. This expert system is obtained for alleviation of voltage violation in the day-to-day operation of a distribution substation in the system, and for processing the data from the SCADA for helping the operator detect buses experiencing abnormal conditions. This expert system focused on shunt reactive compensating devices and transformer tap change to select the most effective control for keeping the bus voltage in the entire system within limits. This study selected 6 distribution substations to be tested with this expert system. The performance of the expert system is compared with the operator control in the terms of voltage deviation indices, numbers of tap changing and minimizing losses.

关键词： Voltage control power system control power systems Expert systems SCADA systems control systems Shunt (electrical) Capacitors Substations system testing

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Open-distributed SCADA system for the okutataragi power station and substation

Open-distributed SCADA system for the okutataragi power stat...

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Waterpower Conference 1999 - Hydro's Future: Technology, Markets, and Policy, Waterpower 1999

作者： Nishi, Minori Yamamoto, Jun Kokado, Toshitsugu Ohga, Yukiharu Uchida, Tomonobu Tokai District Office Kansai Electric Powei Co.Inc. 27-14 2-chome Izumi Higashi-ku Nagoya 46l-8540 Japan New Business Development Dept Kansai Tclecornmurucalion Technology Co. Ltd. Office of Human Resource Development l-9-3-chonie. Awajimachi yuou-ku Osaka 541-0047 Japan Hydro Section Office of Power System Engineering and Operation Kansai Electric Power Co. Inc. 3-22 3-chome Nakanoshima Kita-ku Osaka 530-8270 Japan Power and Industrial Systems R and D Division Hitachi Ltd. 7-2-1 Omika-cho Hitachi-shi Ibaraki-ken 319-1221 Japan Power Systems Information and Control Division Hiiachi Ltd. 6 Kanda-Surugadai 4-chome Chiyoda-ku Tokyo 101-8010 Japan

ISBN: (纸本)0784404402

The total supervisory control and data acquisition (SCADA) system has been developed for the Okutataragi Pumped Storage power Station and its substation. The system applies an open distributed client-server computer architecture and the state-of-the-art man-machine devices, such as a large mimic displays and CRTs with mouse operation. It also includes the following operator support functions: a fault tree based operator guidance function, a bearing temperature prediction function, and a vibration monitoring function. The SCADA system has been put into commercial operation where its superior capabilities have allowed the entire power station and its substation to be run by only two operators. Copyright © 2014 ASCE.

关键词： SCADA systems

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Boiler-Dynamics-Model-Based Economic Load Dispatch

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IFAC Proceedings Volumes 1996年第1期29卷 6951-6956页

作者： M. Yoshikawa N. Toshida H. Kawamura Y. Harada M. Tsurugai Y. Nakata Control System Section Kansai Electric Power Co. Inc. 3-22 Nakanoshima 3-chome Kita-ku Osaka-shi Osaka-fu 530-70 Japan Hitachi Ltd. Hitachi Research Laboratory 1-1 Omika-cho 7-chome Hitachi-shi Ibaraki-ken 319-12 Japan Hitachi Ltd. Omika Works 2-1 Omika-cho 5-chome Hitachi-shi Ibaraki-ken 319-12 Japan

This paper presents an economic dispatching method, BEST method , where BEST is short for Boiler-dynamics-based Economic load diSpaTch. Because this method is based on dynamics models more accurate than the conventional quadratic ones, it can reduce boiler fuel cost. First, to reduce the model deviations from the actual data, the autoregressive moving average (ARMA) model is employed. Second, an economic dispatching problem based on this model is formulated as a quadratic programming (QP) problem. Finally, the cost reduction is evaluated by computer simulations.

关键词： ARMA model Energy management systems Dynamics Quadratic programming Boilers

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FUTURE PROPULSION MACHINERY TECHNOLOGY FOR GAS-TURBINE powerED FRIGATES, DESTROYERS, AND CRUISERS

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NAVAL ENGINEERS JOURNAL 1984年第2期96卷 34-46页

作者： BASKERVILLE, JE QUANDT, ER DONOVAN, MR USN The Authors Commander James E. Baskerville USNis presently assigned to Naval Sea Systems Command (NA VSEA) as the Ship Design Manager for the DDG 51 the Navy's next generation surface combatant. A graduate of the U.S. Naval Academy Class of 1969 he is a qualified Surface Warfare Officer and designated Engineering Duty Officer (ED). He received his M.S. degree in Mechanical Engineering and his professional degree of Ocean Engineer from the Massachusetts Institute of Technology (MIT) and holds a patent right on an Electronic Control and Response System. His naval assignments include tours in USSRamsey (FFG-2) Aide and Flag Lieutenant to the Commander Naval Electronic Systems Command and Ship Superintendent Surface Type Desk Officer and Assistant Design Superintendent at NA VSHIPYD Pearl Harbor. He was awarded the Meritorious Service Medal for distinguished performance at Pearl Harbor Naval Shipyard. As an author he has contributed articles to the ASNEJournaland given presentations at local sections on ship design the use of innovative technology in ship repair and maintenance and the costs and risks associated with engineering progress. Commander Baskerville is a registered Professional Engineer in the State of Virginia an adjunct professor teaching marine engineering at Virginia Tech. and in addition to ASNE which he joined in 1975 is a member of SNAME Tau Beta Pi Sigma Xi ASME and the American Society of Heating Refrigeration and Air Conditioning Engineers (ASHRAE). Dr. Earl R. Quandt:received his degree of Chemical Engineer from the University of Cincinnati in 1956 and his Ph.D. degree in Chemical Engineering from the University of Pittsburgh in 1961. He worked in the naval reactors program at the Bettis Atomic Power Laboratory from 1956 to 1963. Since that time he has been with David Taylor Naval Ship Research and Development Center Annapolis Maryland where he is Head of the Power Systems Division. He contributed to this paper while on a one year assignment to the U.S. Naval Academy as V

A turning point occurred in naval engineering in 1972 when the U.S. N avy chose to use marine gas turbines for the propulsion of its new SPRUANCE and PERRY Class ships. This paper reviews the more than twenty years of experience with turbine technology and its design integration into combat ships needed to make that decision. It is concluded that the availability of a good second generation aircraft derivative engine with proven reliability and a strong commercial base, i.e., the LM-2500, was as important to the decision as was the predicted improved ship effectiveness and cost benefits. This paper discusses improvements that can be made to the twin engine, single gear, single propeller shaft system. Focusing only on this mechanical transmission concept, it addresses the impact of possible improvements to the engine, gear, and shafting. In particular, the paper discusses current LM-2500 related R&D efforts to: (a) obtain improved part-power fuel rates, (b) integrate with a reversing reduction gear, and (c) add on a waste heat recovery steam cycle. Looking ahead to the year 2000, this paper suggests that a successor to the ubiquitous LM-2500 will appear in the 15 MW power range to provide the next step in the evolution of the twin engine package. This new naval engine will most likely be based on an aircraft core that exists at present, such that it will have demonstrated its reliability and commercial potential through many hours of testing prior to its mid-1990 marine conversion. This new engine is expected to offer improved air flow, an excellent fuel rate (approaching a flat 0.30 LB/HP-HR), and effective maintenance monitoring, all at some expense in size, weight, and cost. The year 2000 engine will burn a liquid hydrocarbon fuel similar to JP-5 because of its aircraft origins. Combined with advances in gear and shafting technology, the full twin engine propulsion system of the year 2000 should be markedly lighter, smaller, and more efficient than today's units.

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