Vol(1), Issue(10)

IJSRE - Vol(1), Issue(10)

A FUZZY LOGIC BASED FAULT CLASSIFICATION SCHEME WITH HIGH ROBUSTNESS FOR TRANSMISSION LINE PROTECTION
Monesh Kumar Chandrakar*, Mr. Ashish Dewangan
ABSTRACT :

In this paper, a new and accurate fuzzy logic based scheme for fault classification of EHV transmission lines has been presented. The fault classification scheme is carried out by using only the post-fault magnitude of three phase’s current phasor and its sequence components. The proposed fault classification technique is able to classify all possible faults type which can affect a transmission line such as the single-phase to ground faults, two-phase faults, two-phase to ground faults and three-phase faults with high accuracy under wide variety of fault conditions. Large numbers of simulation test cases are generated to verify the performance of proposed scheme. The simulation studies have been carried out by using MATLAB software and MATLAB Fuzzy Logic Toolbox.

AUTHOR :

Monesh Kumar Chandrakar
M.Tech Student, Department of E.E.E., SSITM, Bhilai, Chhattisgarh, INDIA

Mr. Ashish Dewangan
Sr. Assistant Professor, Department of E.E.E., SSITM, Bhilai, Chhattisgarh, INDIA

KEYWORDS :

Fuzzy logic system (FLS), Discrete Fourier transform (DFT), Fault classification (FC), Fault inception angle (FIA), Extra high voltage, Transmission line

CONCLUSION :

A fast, reliable and accurate fault classification based on fuzzy-logic is presented in this paper to identify all ten types of faults that may occur in power transmission lines. Only three line currents measurement are sufficient to implement this technique. The Discrete Fourier Transform (DFT) is used to compute the positive, negative and zero sequence components of fundamental frequency of currents. The proposed protection technique requires the consideration of the three phase post fault current samples at one end of line only. The fault classification algorithm is based on the angular differences among the sequence components of the fundamental fault current as well as on the relative magnitudes of fundamental phase current.
The proposed fuzzy logic-based fault classification scheme identified all of the test cases correctly. The performance of the proposed method is not affected by a wide variation of fault resistance, fault inception angle and fault location for different types of fault.

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