Multi-channel CNN-LSTM based Power System Event Classification via Wavelet Image Features; 다중채널 CNN-LSTM 및 웨이브렛 이미지 기반 전력계통 이벤트 분류

Citations

SCOPUS

0

초록

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 © © The Korean Institute of Electrical Engineers.

키워드

CNN-LSTMEvent ClassificationPMUSynchrophasorWavelet Analysis
제목
Multi-channel CNN-LSTM based Power System Event Classification via Wavelet Image Features; 다중채널 CNN-LSTM 및 웨이브렛 이미지 기반 전력계통 이벤트 분류
저자
Kim, Do-in
DOI
10.5370/KIEE.2023.72.9.982
발행일
2023
유형
Article
저널명
전기학회논문지
72
9
페이지
982 ~ 986