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A. Satpathy

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Open access Oct 2026

Physics-informed sparse deep neural networks for ultra-fast solar power forecasting and frequency response support in ancillary service markets

The results show the potential of physics-informed sparse learning as a disruptive tool for reliable, scalable and commercially viable participation of solar in fast frequency response services, thus increasing the resilience and sustainability of future low-carbon power systems.

Asit Mohanty, A. Ramasamy, S. Mohanty et al. · 0 citations

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