Research Papers - Department of Electrical and Electronic Engineering

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Author: search.filters.author.Hettiwatte, S. NSubject: search.filters.subject.power transformers

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    PublicationOpen Access
    Application of Parzen Window estimation for incipient fault diagnosis in power transformers
    (The Institution of Engineering and Technology, 2018-12) Islam, M. D. M; Hettiwatte, S. N; Lee, G
    Accurate faults diagnosis in power transformers is important for utilities to schedule maintenance and minimises the operation cost. Dissolved gas analysis (DGA) is one of the proven and widely accepted tools for incipient fault diagnosis in power transformers. To improve the accuracy and solve the cases that cannot be classified using Rogers’ Ratios, IEC ratios and Duval triangles methods, a novel DGA technique based on Parzen window estimation have been presented in this study. The model uses the concentrations of five combustible hydrocarbon gases: methane, ethane, ethylene, acetylene and hydrogen to compute the probability of transformers fault categories. Performance of the proposed method has been evaluated against different conventional techniques and artificial intelligence-based approaches such as support vector machines, artificial neural networks, rough sets analysis and extreme learning machines for the same set of transformers. A comparison with other soft computing approaches shows that the proposed method is reliable and effective for incipient fault diagnosis in power transformers.
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    PublicationEmbargo
    A measurements-based discharge location algorithm for plain disc winding power transformers
    (IEEE, 2005-06-20) Wang, Z. D; Hettiwatte, S. N; Crossley, P. A
    A measurements-based electrical method for locating partial discharges (PD) in transformers is described in the paper. This location method relies on the series resonance frequencies of the signals produced at the transformer terminals by a discharge on the winding. Based on the equivalent circuit of plain disc type winding which consists of series inductance (L), series capacitance (K) and shunt capacitance to earth (C) of the winding, an analytical location algorithm is derived which gives the relationship between the location of a discharge and its terminal response's series resonance frequencies. LKC parameters of the equivalent circuit can be estimated using the series resonance frequencies of a calibration signal measured at the bushing tap during PD calibration. The PD location algorithm was tested on 11 kV transformer winding using signals produced by a discharge simulator and real discharges, and the results confirm its validity with a location accuracy of better than 10% of the winding length. However, blind area where this location algorithm is not applicable does exist near the neutral of the winding and far away from the measuring terminal. Since this location algorithm uses the series resonance frequencies below 500 kHz, it can be implemented with conventional PD measuring circuitry and instruments to detect and locate discharges in power transformers.