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Author: search.filters.author.Ngaopitakkul, AtthapolSubject: search.filters.subject.Transmission Line

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    Fault classification in transformer using low frequency component
    (2017-12-13)
    Jettanasen, Chaiyan
    ;
    Ngaopitakkul, Atthapol
    ;
    Asfani, Dimas Anton
    ;
    Negara, I. Made Yulistya
    Transform is a vital equipment in power system that need protection system in order to provide fast and correct response when disturbance occur in system. So, this paper proposed internal and external fault classification in Transformer using algorithm based on discrete wavelet transform (DWT). Low frequency component from DWT has been used to create condition for algorithm. The proposed algorithm has been test using transmission line connected to transformer experimental setup on laboratory level. The result from proposed algorithm shown satisfactory result with 100% accuracy in both internal and external fault in transmission line connected transformer system.
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    Comparison of mother wavelet for classification fault on hybrid transmission line systems
    (2017-07-01)
    Klomjit, Jittiphong
    ;
    Ngaopitakkul, Atthapol
    ;
    Sreewirote, Bancha
    This paper proposes comparison mother wavelets for fault classification on hybrid transmission line systems. Hybrid system consists of overhead line and underground cable of 115 kV. ATP/EMTP software has been used for generating fault signals. Then it varies location of fault, fault type and angle. Current signals and zero sequence are analyzed by Discrete Wavelet Transform (DWT) in MATLAB software. DWT decomposes high frequency components from fault signals. Coefficient in scale 1 has been decomposed from Mother Wavelets such as Daubechies (db), Symlets (sym), Biorthogonal (bior) and Coiflets (coif). The coefficient for any mother wavelet has same behavior but different value. Design algorithm for fault classification and compare the result. Therefore, comparison of mother wavelet for fault classification is important to provide the high accuracy. Daubechies (db) can give accuracy more than any mother wavelet.