This paper proposes a novel algorithm for EHV transmission line faulted phase selection based on current transients by employing the wavelet transform (WT) and the artificial neural network (ANN) techniques. The WT technique and spectral energy calculation offer an efficient method for feature extraction and the ANN plays an important role for decision making. The system is simulated using EMTP and the proposed faulted phase selection scheme is developed based on MATLAB. All the test results show that the designed algorithm is very suitable for identifying the faulted phase(s) under a wide variety of different system and fault conditions in EHV-transmission lines.
|Title of host publication||2011 International Conference on Advanced Power System Automation and Protection (APAP), 16-20 October 2011|
|Number of pages||6|
|Publication status||Published - Oct 2011|
- wavelet transform
- neural networks
- phase selection
Chen, J., Aggarwal, R., & Lu, Y. (2011). New algorithm for EHV transmission line faulted-phase selection based on wavelet transforms and artificial intelligence. In 2011 International Conference on Advanced Power System Automation and Protection (APAP), 16-20 October 2011 (Vol. 3, pp. 2374-2379). IEEE. https://doi.org/10.1109/APAP.2011.6180825