Risk Assessment of Power Supply Security Considering Optimal Load Shedding in Extreme Precipitation Scenarios
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- Maosong Fan & Mengmeng Geng & Kai Yang & Mingjie Zhang & Hao Liu, 2023. "State of Health Estimation of Lithium-Ion Battery Based on Electrochemical Impedance Spectroscopy," Energies, MDPI, vol. 16(8), pages 1-14, April.
- Riley Weinmann & Eduardo Cotilla-Sanchez & Ted K. A. Brekken, 2022. "Toward Models of Impact and Recovery of the US Western Grid from Earthquake Events," Energies, MDPI, vol. 15(24), pages 1-17, December.
- Xiaoyang Deng & Jinghan He & Pei Zhang, 2017. "A Novel Probabilistic Optimal Power Flow Method to Handle Large Fluctuations of Stochastic Variables," Energies, MDPI, vol. 10(10), pages 1-21, October.
- Ning Ma & Huaixian Yin & Kai Wang, 2023. "Prediction of the Remaining Useful Life of Supercapacitors at Different Temperatures Based on Improved Long Short-Term Memory," Energies, MDPI, vol. 16(14), pages 1-14, July.
- Zhang, Hao & Gao, Jingyi & Kang, Le & Zhang, Yi & Wang, Licheng & Wang, Kai, 2023. "State of health estimation of lithium-ion batteries based on modified flower pollination algorithm-temporal convolutional network," Energy, Elsevier, vol. 283(C).
- R. A. Swief & T. S. Abdel-Salam & Noha H. El-Amary, 2018. "Photovoltaic and Wind Turbine Integration Applying Cuckoo Search for Probabilistic Reliable Optimal Placement," Energies, MDPI, vol. 11(1), pages 1-17, January.
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