DETERMINANT-BASED FEATURE EXTRACTION FOR FAULT DETECTION AND CLASSIFICATION FOR POWER TRANSMISSION LINES

Abstract : Three phase transmission line are soul of power system. In this paper different types of fault are classified in the three phase transmission line. In the present scenario the both end ratios are considered for the data acquisition of voltage and currents. This states are measured and fed to the control panel for the fault analysis and detection. These techniques are very much accurate for the short and medium transmission line. But for long transmission line classification needs the accuracy and actual detection of the fault and direction of the fault. For a 400kV, 100MVA, and 112km transmission is simulated and worked in MATLAB/SIMULINK environment.

 EXISTING SYSTEM :

 In transmission line four types of fault namely single line-ground, line-line, double line-ground and three phase faults have been taken into consideration into this work and only single line ground fault will be the proposed neural network structures. Neural network are indeed a reliable and attractive method for transmission line faults scheme especially in view of increase complexity of the modern power systems.

 DISADVANTAGE :

 INTRODUCTION Protection of power system transmission line have great impact on the economic consideration of any state or country. It also directly affects the people life and indirectly to the growth of any nation. There are various duties of protection system including to isolate the healthy system from the faulty system. Along with, the isolation from the healthy system it is very necessary to classify the nature of fault for the further studies and the report generation. The classification of fault provides the information regarding the faulty phase, severity level of fault etc.

 PROPOSED SYSTEM :

  METHODOLOGY Idea and purpose is to classify and detect fault based on the symmetrical components with their phase angle and magnitude of current. The phasor values of three phase system can be converted into the equivalent symmetrical components. Only, positive and negative components have been used in this paper to perform the classification of faults. In the present scenario, zero sequence components give the definite ground fault but during unbalanced system zero sequence component may present. Although in the un-faulted condition zero sequence may occur in the system.

 

 

voltage-dip-and-engorge POWER-QUALITY-IMPROVEMENT PV-system high-output-power- super-capacitors

FAULT DETECTION- POWER TRANSMISSION LINES MATLAB/SIMULINK Three-phase-transmission-line- power-system