Natural Disaster Management Using Machine Learning for Resilient Electrical Grids
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-52330-4_8
Reference13 articles.
1. Das, L.: Measuring smart grid resilience: methods, challenges and opportunities. Renew. Sustain. Energy Rev. 130, 109918 (2020)
2. Laya, M., Mera, K.: Classification of natural disaster on online news data using machine learning. In: 5th International Conference on Electrical, Telecommunication and Computer Engineering (ELTICOM), vol. 5, pp. 42–46. IEEE (2021)
3. Daeli, A., Salman, M.: Power grid infrastructural resilience against extreme events. Energies 16(1), 64 (2023)
4. Bragg‐Sitton, S.M.: Reimagining future energy systems: overview of the US program to maximize energy utilization via integrated nuclear‐renewable energy systems. Int. J. Energy Res. 44(10), 8156–8169 (2020)
5. Ren, H., Hou, Z.J.: Analysis of weather and climate extremes impact on power system outage. In: IEEE Power Energy Society General Meeting (PESGM), IEEE (2021)
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