Author:
Ao Yuqi,Chen Jinfu,Cai Defu,Liu Haiguang,Chen Rusi
Publisher
Springer Nature Singapore
Reference14 articles.
1. Zhu, L., Hill, D., Lu, C.: Hierarchical deep learning machine for power system online transient stability prediction. IEEE Trans. Power Syst. 35(3), 2399–2411 (2020)
2. Suresh, V., Sutradhar, R., Mandal, S., et al.: Near miss of blackout in southern part of north eastern grid of India. In: 2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies, pp. 1–5. IEEE Press, New York (2021)
3. Lin, W., Yi, J., Guo, Q., et al.: Analysis on blackout in Argentine power grid on June 16, 2019 and Its enlightenment to power grid in China. Proc. CSEE 40(09), 2835–2842 (2020). (in Chinese)
4. Mosavi, S.: Extracting most discriminative features on transient multivariate time series by bi-mode hybrid feature selection scheme for transient stability prediction. IEEE Access 9, 121087–121110 (2021)
5. Kosen, I., Huang, C., Chen, Z., et al.: UPS: unified PMU-data storage system to enhance T+D PMU data usability. IEEE Trans. Smart Grid 11(1), 739–748 (2020)