Time–time‐transform application to fault diagnosis of power transformers. Issue 6 (1st June 2014)

• Record Type: Journal Article
• Authors: Ashrafian, A.; Vahidi, Behrooz; Mirsalim, Mojtaba
• Is Part Of: IET generation, transmission & distribution. Volume 8:Issue 6(2014)
• Page Start: 1156
• Page End: 1167
• Publication Date: 2014-06-01
• Subjects: fault diagnosis -- power transformer protection -- transforms; time‐time‐transform application -- power transformer fault diagnosis -- TT‐transform method -- power transformer differential protection -- relay scheme -- differential current signal -- TT‐matrix -- inrush current -- internal fault -- typical power system -- EMTP software -- Matlab environment -- differential current extraction -- wavelet transform method -- S‐transform method; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2013.0622
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Application of time–time (TT)‐transform for differential protection of power transformers has been suggested. At first, external and internal disturbances are discriminated. If the disturbance is external, relay scheme restrains more analysis and tripping. Otherwise, the differential current signal is analysed by TT‐transform and TT‐matrix is computed. Next, a suggested index is computed, accordingly. Discrimination between inrush current and internal fault is performed by the proposed index. To investigate the effectiveness of the method, a typical power system has been modelled in EMTP software. Also, the relay scheme has been developed in MATLAB environment. Then, differential currents extracted from the system modelled in EMTP have been fed to MATLAB for analysis. Also, the performance of the method in noisy environments has been assessed. To make an analogy between the TT‐transform‐based method and wavelet transform‐based methods, a wavelet transform‐based scheme has been developed in MATLAB environment and results have been compared to the results of the TT‐transform‐based method. In addition, an S ‐transform‐based method has been implemented in MATLAB and has been compared with the suggested method. The results show that the method is superior to both wavelet transform and S ‐transform‐based methods.