| Title |
Multi-channel CNN-LSTM based Power System Event Classification via Wavelet Image Features |
| DOI |
https://doi.org/10.5370/KIEE.2023.72.9.982 |
| Keywords |
PMU; Synchrophasor; Event Classification; CNN-LSTM; Wavelet Analysis |
| Abstract |
This paper proposes the event-based power system situational awareness method by utilizing PMU infrastructure. The proposed algorithm is specifically configured as algorithm that can be utilized in a wide area power system using an optimized set of PMUs and a window frame configuration. The key to utilizing an optimized set of PMUs is imaging each measured time series data with a wavelet transform to efficiently enable the CNN-based classification. The proposed CNN-LSTM based event classification technique is able to classify event categories implemented in the power system. Finally, the proposed algorithm is verified through simulation, and represents the performance evaluation according to the number of PMU measurements |