A Probabilistic Generative Model for Fault Analysis of a Transmission line with SFCL

Author(s):  
Shahriar Rahman Fahim ◽  
Subrata K. Sarker ◽  
Sajal Kumar Das ◽  
Md. Rabiul Islam ◽  
Abbas Z. Kouzani ◽  
...  
2014 ◽  
Vol 29 (2) ◽  
pp. 942-950 ◽  
Author(s):  
Papiya Dutta ◽  
Ahad Esmaeilian ◽  
Mladen Kezunovic

2014 ◽  
Vol 984-985 ◽  
pp. 996-1004
Author(s):  
D. Miruthula ◽  
Ramachandran Rajeswari

This paper presents a new method to classify transmission line shunt faults and determine the fault location using phasor data of the transmission system. Most algorithms employed for analyzing fault data require that the fault type to be classified. The older fault-type classification algorithms are inefficient because they are not effective under certain operating conditions of the power system and may not be able to accurately select the faulted transmission line if the same fault recorder monitors multiple lines. An intelligent techniques described in this paper is used to precisely detect all ten types of shunt faults that may occur in an electric power transmission system (double-circuit transmission lines) with the help of data obtained from phasor measurement unit. This method is virtually independent of the mutual coupling effect caused by the adjacent parallel circuit and insensitive to the variation of source impedance. Thousands of fault simulations by MATLAB have proved the accuracy and effectiveness of the proposed algorithm. This paper includes the analysis of fault identification techniques using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System based protection schemes. The performances of the techniques are examined for different faults on the parallel transmission line and compared with the conventional relay scheme. The results obtained shows that ANFIS based fault identification gives better performance than other techniques.


Recognition and arrangement of current-voltage, power fluctuations are critical functions for the safety of the power system (PS). Many perturbations of power quality (PQ) are unpredictable and ephemeral, and the demand for voltage and current recognition and arrangement is confirmed. By using Fast Fourier transform, expert systems, and neural networks, certain intelligent system technologies dominate fault analysis. As expected, there are five types of issues that include sag and swell, ripple, transient fluctuation, interruption and natural waveform. In this paper, we study the transmission line faults for voltage drop, voltage swell, and transient voltage. Power supply and traffic transmission leakage have been major problems for electricity providers and consumers. Much of the disturbance is non-stationary and intermittent, needing specialized methods and techniques for PQ disturbance research. This article provides a full collection of MATLAB / Simulink models to simulate different energy efficiency disturbances. This paper implements power quality disturbance in the model Matlab/ Simulink. The model provided can be used to simulate various disturbances of energy quality and waveforms for analysis and research into power quality, and to help to develop educational programs and understand the energy quality. This would concentrate on what are PQ problems and current approaches to evaluate and classify such problems.


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