Continuous estimation of power system inertia using convolutional neural networks
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DOI: 10.1038/s41467-023-40192-2
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- Davide del Giudice & Samuele Grillo, 2019. "Analysis of the Sensitivity of Extended Kalman Filter-Based Inertia Estimation Method to the Assumed Time of Disturbance," Energies, MDPI, vol. 12(3), pages 1-19, February.
- Tielens, Pieter & Van Hertem, Dirk, 2016. "The relevance of inertia in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 999-1009.
- Heylen, Evelyn & Teng, Fei & Strbac, Goran, 2021. "Challenges and opportunities of inertia estimation and forecasting in low-inertia power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
- Wenju Sang & Wenyong Guo & Shaotao Dai & Chenyu Tian & Suhang Yu & Yuping Teng, 2022. "Virtual Synchronous Generator, a Comprehensive Overview," Energies, MDPI, vol. 15(17), pages 1-29, August.
- Amirhossein Sajadi & Rick Wallace Kenyon & Bri-Mathias Hodge, 2022. "Synchronization in electric power networks with inherent heterogeneity up to 100% inverter-based renewable generation," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
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