A New Algorithm for the Classification of Faults in Multi-Terminal Transmission Network using Wavelet Morphology
Y. Srinivasa Rao1, G. Ravikumar2, P. Srinivasa Varma3

1Y. Srinivasa Rao, Assistant Proffesor in the department of EEE at K L University , B.Tech Electrical and Electronics Engineering in Avanthi Institute of Engineering and Technology. M.Tech CEN.Assistant Proffesor department of EEE  K L University (Andhra Pradesh), India.
2G. Ravikumar, Proffesor department of EEE Bapatla Engineering College, B.E Electrical Engineering Andhra University college of Engineering and Technology Visakhapatnam, (Andhra Pradesh), India.
3P. Srinivasa Varma, Associate professor in the Department of Electrical and Electronics Engineering at Koneru lakshmaiah Education Foundation, Vaddeswaram, AP, India.

Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 1102-1109 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2524037619/19©BEIESP
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Abstract: Unevenly abnormalities may appear on High Voltage transmission line, consequently power interruptions are taken place in distributed loads. Classification of faults is highly essential to design appropriate protective scheme at terminals of the transmission line. Faulty signals can be process through 2D or 3D Analysis .But in present paper has been analysed 2 dimensional analysis. Faulty conditions of an interconnected power system network (IEEE-9 Bus) are captured and sampled for a specific interval of time, and which are analysed by wavelet morphology to discriminate the faults at each terminal of the transmission line. This paper presents an innovative approach for the detection of fault, based on Morphological wavelet transform and Daubechies – Eight (Db-8) wavelet has been selected as structuring element for transformation of three phase currents on transmission lines, A standard IEEE 9-bus system has been simulated for different types of faults and which are process through Morphological transformation for identification of fault in a very short time period.
Keywords: Morphological Transform (MT), Dabachies wavelet (db8), Interconnected power system, Feature Extraction, Ground Fault Index, Fault resistance, Matlab / Simulink.

Scope of the Article: Classification