Fault analysis (detection, classification and location) of transmission network is of great importance in power system. A Wavelet-Alienation-Neural (WAN) technique has been developed for the fault analysis of Unified Power Flow Controller (UPFC) compensated transmission network. The detection and classification of various outages are accomplished by alienation of wavelet based approximate coefficients computed from current signals. The precise location of faults is carried out by an Artificial Neural Network fed from estimated approximate coefficients computed from voltage and current signals of the same quarter cycle. The robustness of the algorithm is proved with the case studies of varying fault locations, sampling frequency, system parameters, effects of noise, fault incipient angle, different control strategies and fault path impedances.


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    Title :

    Protection scheme using wavelet-alienation-neural technique for UPFC compensated transmission line



    Publication date :

    2021-01-01


    Remarks:

    Rathore , B , Mahela , O P , Khan , B & Padmanaban , S 2021 , ' Protection scheme using wavelet-alienation-neural technique for UPFC compensated transmission line ' , IEEE Access , vol. 9 , 9328115 , pp. 13737-13753 . https://doi.org/10.1109/ACCESS.2021.3052315



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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