Background:
In this paper, two methods and their comparison used to determine the fault locaton in VSC-HVDC transmission lines. Fast and reliable control are features of these systems.
Methods:
Additionally, wavelet transform from advanced techniques of signal processing is employed for the purpose of extracting important characteristics of fault signal from both sides of the line by PMU. To do so, Deep learning is used to identify the relation between the extracted features from wavelet analysis of the fault current and variations under fault conditions. As such, wavelet transform and advanced signal processing techniques are used to extract important features of fault signal from both sides of the line by the PMU.
Results:
The results show the high accuracy of finding fault location by the deep learning algorithm method compared to the k-means
algorithm with an error rate of <1%.
Conclusion:
Studies on the 50 kV VSC-HVDC transmission line with a length of 25 km in MATLAB have been simulated.