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Fault classification in transformer using low frequency component
(2017-12-13)
Jettanasen, Chaiyan
;
Ngaopitakkul, Atthapol
;
Asfani, Dimas Anton
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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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Internal Fault Classification Algorithm in Power Transformer Based on Discrete Wavelet Transform and Fuzzy Logic
(2017-11-15)
Ananwattanaporn, Santipont
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Leelajindakrairerk, Monthon
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Jettanasen, Chaiyan
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Pothisarn, Chaichan
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Ngaopitakkul, Atthapol
This paper proposed classification algorithm that combination of wavelet transform and fuzzy logic to classifying the internal fault type in power transform. The decision algorithm process, a structure of the fuzzy logic consists of 4 inputs and 1 output. The maximum ratio of DWT at & #xbc; cycle of phase A, B, C is performed as input variables while the output variables are designated corresponding to various types of internal faults. The 50 MVA, 115/23 kV three-phase power transformer has been modelled and simulate to evaluate the performance of proposed algorithm. The results show that the proposed algorithm gives satisfactory results, however, the overall accuracy indicates that this algorithm requires the further improvement.
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Behavior analysis of winding to ground fault in transformer using high and low frequency components from discrete wavelet transform
(2017-07-21)
Rummdkarn, Jintasit
;
Ngaopitakkul, Atthapol
This paper analyzes the behavior of winding to ground fault in the single-phase transformer using experimental setup in laboratory level. The winding to ground fault in each voltage winding of the single-phase transformer is first obtained in order to analyze the behavior of the differential current of the transformer. For different winding voltages of the transformer, the calculated differential current of the transformer will be employed to analyze the behavior of winding fault to ground in the single-phase transformer using discrete wavelet transform (DWT) method. The coefficient comparison between high frequency component and low frequency component will be done in order to confirm the effectiveness of the applied technique in this study.
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Comparison of mother wavelet for classification fault on hybrid transmission line systems
(2017-07-01)
Klomjit, Jittiphong
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Ngaopitakkul, Atthapol
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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.
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Behaviour of interturn fault in power transformer winding using high frequency components of discrete wavelet transform
(2012-12-01)
Klomjit, Jittiphong
;
Ngaopitakkul, Atthapol
Behaviour of interturn winding fault signals in a three-phase two-winding transformer with delta connected primary and wye connected secondary, using high frequency components of DWT is proposed in this paper. The mother wavelet daubechies4 (db4) is employed to decompose high frequency components from signals. Various case studies have been done including the variation of fault inception angles, fault types, and fault locations. The result will be useful in the development of a fault detecting scheme for power transformer in the future. © 2012 IEEJ Industry Appl Soc.
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Discriminating among inrush current, external fault and internal fault in power transformer using low frequency components comparison of DWT
(2012-12-01)
Jettanasen, Chaiyan
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Pothisarn, Chaichan
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Klomjit, Jittiphong
;
Ngaopitakkul, Atthapol
A technique using discrete wavelet transform (DWT) in order to discriminate among inrush current, internal fault, and external fault has been proposed. Daubechies4 (db4) is employed as mother wavelet in order to decompose low frequency components from fault signals. A ratio between per unit differential current and per unit time is calculated and performed as comparison indicator. The results obtained from the proposed technique have good accuracy to discriminating fault in the considered system. © 2012 IEEJ Industry Appl Soc.

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