An Online Security Prediction and Control Framework for Modern Power Grids
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- Sharifzadeh, Mahdi & Sikinioti-Lock, Alexandra & Shah, Nilay, 2019. "Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian Process Regression," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 513-538.
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- Yunus Yalman & Tayfun Uyanık & İbrahim Atlı & Adnan Tan & Kamil Çağatay Bayındır & Ömer Karal & Saeed Golestan & Josep M. Guerrero, 2022. "Prediction of Voltage Sag Relative Location with Data-Driven Algorithms in Distribution Grid," Energies, MDPI, vol. 15(18), pages 1-16, September.
- Petar Sarajcev & Antonijo Kunac & Goran Petrovic & Marin Despalatovic, 2022. "Artificial Intelligence Techniques for Power System Transient Stability Assessment," Energies, MDPI, vol. 15(2), pages 1-21, January.
- Dahu Li & Xiaoda Cheng & Leijiao Ge & Wentao Huang & Jun He & Zhongwei He, 2022. "Multiple Power Supply Capacity Planning Research for New Power System Based on Situation Awareness," Energies, MDPI, vol. 15(9), pages 1-24, April.
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Keywords
security; incremental machine learning; renewable energy sources; distributed generation;All these keywords.
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