KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Settings

Author: search.filters.author.Pothisarn, ChaichanSubject: search.filters.subject.Power transformer

Search Results

Now showing 1 - 4 of 4
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    Application of probabilistic neural networks using high-frequency components’ differential current for transformer protection schemes to discriminate between external faults and internal winding faults in power transformers
    (2021-11-01)
    Chiradeja, Pathomthat
    ;
    Pothisarn, Chaichan
    ;
    Phannil, Nattanon
    ;
    Ananwattananporn, Santipont
    ;
    Leelajindakrairerk, Monthon
    Internal and external faults in a power transformer are discriminated in this paper using an algorithm based on a combination of a discrete wavelet transform (DWT) and a probabilistic neural network (PNN). DWT decomposes high-frequency fault components using the maximum coefficients of a 1/4 cycle DWT as input patterns for the training process in a decision algorithm. A division algorithm between a zero sequence of post-fault differential current waveforms and the differential current coefficient in the 1/4 cycle DWT is used to detect the maximum ratio and faults. The simulation system uses various study cases based on Thailand’s electricity transmission and distribution systems. The simulation results demonstrated that the PNN and BPNN are effectively implemented and perform fault detection with satisfactory accuracy. However, the PNN method is most suitable for detecting internal and external faults, and the maximum coefficient algorithm is the most effective in detecting the fault. This study will be useful in differential protection for power transformers.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    Application of support vector machines algorithm for discriminating between external fault and internal winding fault in power transformer
    (2014-02-04)
    Ngaopitakkul, Atthapol
    ;
    Jettanasen, Chaiyan
    ;
    Leelajindakrairerk, Monthon
    ;
    Pothisarn, Chaichan
    ;
    Suechoey, Boonlert
    The differential relaying principle is used for protection of medium and large power transformers. In the past decade, several decision algorithms have different solutions and techniques. This paper proposes a new technique using discrete wavelet transform (DWT) and support vector machines (SVM) to classify and discriminate between external fault and internal fault in power transformer. The DWT is used to detect the high frequency components from fault signals. The variations of first scale high frequency component that detects fault are used as input for the SVM. The proposed method gives satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission systems. © 2014 ICIC International.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    Behaviour of internal fault and external fault in power transformer using discrete wavelet transform
    (2012-06-12)
    Ngaopitakkul, Atthapol
    ;
    Pothisarn, Chaichan
    The differential protection is aimed at detecting internal faults in transformer windings. Therefore, it is necessary to understand fault behaviour before doing performing decision algorithm. This paper presents behaviour of internal winding fault and external short circuit in a three-phase two-winding transformer. The advantage of the discrete wavelet transform (DWT) is considered herein. The fault is simulated using ATP/EMTP and the behaviour analysis of signals is performed using DWT. The variation of high frequency components of differential current signals is presented in this paper. The results obtained from the analysis will be useful in the development of a fault detecting scheme for power transformer in the future.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    Behavior of winding to ground fault in transformer windings using discrete wavelet transform
    (2010-12-01)
    Pothisarn, Chaichan
    ;
    Ngaopitakkul, Atthapol
    ;
    Pongchaisrikul, Worravut
    ;
    Apisit, Chaowat
    ;
    Jonpermpoonpol, Saridroje
    In the literature for fault detection, most of research works have never been mentioned about the high frequency transformer including capacitances. This paper presents behaviour of winding to ground fault signals in a three-phase two-winding transformer. The advantage of the discrete wavelet transform (DWT) is that the band of analysis can be fine adjusted so that high frequency components and low frequency components are detected precisely, consequently DWT is considered herein. The fault is simulated using ATP/EMTP and the behaviour analysis of signals is performed using DWT. The variation of high frequency components of differential current signals is proposed in this paper. The results obtained from the analysis will be useful in the development of a detect fault scheme for power transformer in the future.