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Resilient frequency stabilization of renewable-penetrated microgrids via deep learning and machine learning
The intrinsic variability of wind generation necessitates accurate wind speed forecasting to minimize active power imbalance between supply and demand and thereby enhance frequency stability in microgrids (MGs). In this context, this paper investigates wind speed prediction at four geographically di
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