Artificial Intelligence Forecasting for Transmission Line Ampacity
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-79606-8_16
Reference25 articles.
1. Zainuddin, N.M., Rahman, M.A., Kadir, M.A., Ali, N.N., Ali, Z., Osman, M.: Review of thermal stress and condition monitoring technologies for overhead transmission lines: issues and challenges. IEEE Access 8, 120053–120081 (2020)
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3. Pepiciello, A., Coletta, G., Vaccaro, A., Villacci, D.: The role of learning techniques in synchrophasor-based dynamic thermal rating. Int. J. Electr. Power Energy Syst. 115, 105435 (2020)
4. Hou, Y., Wang, W., Wei, Z., Deng, X., Ji, Q., Wang, T.: Research and application of dynamic line rating technology. Energy Rep. 6, 716–730 (2020)
5. Karimi, S., Musilek, P., Knight, A.M.: Dynamic thermal rating of transmission lines: a review. Renew. Sustain. Energy Rev. 91, 600–612 (2018)
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