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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/664

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contributor.authorSamantaray, S R-
contributor.authorPanda, G (Guide)-
contributor.authorDash, P K (Guide)-
date.accessioned2008-04-24T05:41:23Z-
date.available2008-04-24T05:41:23Z-
date.issued2007-
identifier.citationA new approach to Power System Protection using Time-frequency analysis and Pattern Recognition, Thesis submitted in partial fulfillment of the requirements for the award of the Doctor of Philosophy in Electronics, Submitted to National Institute of Technology, Rourkelaen
identifier.urihttp://hdl.handle.net/2080/664-
descriptionCopyright for the thesis belongs to National Institute of Technology Rourkelaen
description.abstractThe fault diagnosis of Electric Power System is a process of discriminating the faulted system elements by protective relays and subsequent tripping by circuit breakers. Specially, as soon as some serious faults occur on a power system, a lot of alarm information is transmitted to the control center. Under such situation, the operators are required to judge the cause, location, and the system elements with faults rapidly and accurately. Thus, good fault diagnosis methods can provide accurate and effective diagnostic information to dispatch operators and help them take necessary measures in fault situation so as to guarantee the secure and stable operation of the Electric power system. This thesis reports various techniques used for detection, classification and localization of faults on the high voltage transmission line. The distance protection scheme for transmission line is employed for various power networks such as single-circuit line, double-circuit line, and lines having FACTS devices. The faulted voltage and current signal samples are retrieved at the relaying point for all 11 types of shunt faults at various operating conditions like variation in source impedance, fault resistance, inception angle, and fault locations. These sampled voltage and current signals are used for detection, classification, and location of different types of faults. Unlike the conventional relaying schemes, using fuzzy systems and neural networks, the proposed research work presents a novel technique for distance and differential protection, using time-frequency analysis and pattern recognition approach. The time-frequency transform such as S-Transform and its variations are used for fault detection, classification and location determination for transmission lines. The S-Transform is an extension of Wavelet Transform which possesses superior property over the latter as the moving functions are fixed with respect to time axis while the localizing scalable Gaussian window dilates and translates. The S-Transform uses an analysis window whose width is decreasing with frequency providing a frequency dependent resolution. Phase spectrum obtained in this transform is always with respect to fixed reference point and the real and imaginary spectrum can be localized independently. Such a transform with moving and scalable localizing Gaussian window, therefore, provides excellent time localization property for different signals. The proposed research work includes pre-processing the fault current and voltage signal samples through S-Transform and finding out the phasor information such as amplitude and phase, which are used for impedance calculation to the fault point. Also energy and standard deviation of the S-matrix are computed to detect and classify the fault patterns. Another variation of the S-Transform such as Hyperbolic S-Transform is also used to detect and localize the fault with various operating conditions of the power network. Wavelet Transform is also applied to the faulted voltage and current signals and multi-resolution analysis is done to detect and classify the faulty section and section identification of the transmission line including FACTS. Intelligent techniques such as Radial Basis Function Neural network (RBFNN) and Support Vector Machine (SVM) are embedded to the proposed protection schemes for automatic recognition of the fault patterns for transmission line including FACTS. The RBFNN and SVMs are trained and tested to design a robust fault classifier which provides accurate results for different types of faults with wide variations in operating conditions. In another approach, a differential equation based fault locator is designed for transmission line including Unified Power Flow Controller (UPFC). The faulted power network is drawn and differential equations are developed for voltage and current at the fault point. Using the faulted voltage and current information at both sending and receiving end, the line inductance to the fault point is calculated which directly reflects the location of the fault point from the relaying location. Another variation of S-Transform known as complex windowed S-Transform is used to extract the time-frequency contours of the inrush current and fault current signals, to distinguish the inrush current and fault current, used for power transformer protection. The time-frequency contours at different frequencies are extracted and an energy index is devised to distinguish both signals. The proposed method provides better results compared to existing 2nd harmonic restraint protection for power transformer.en
format.extent1966785 bytes-
format.mimetypeapplication/pdf-
language.isoen-
publisherNIT Rourkelaen
titleA new approach to Power System Protection using Time-frequency analysis and Pattern Recognitionen
typeThesisen
Appears in Collections:Thesis (Doctor of Philosophy)

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