Zhaocai Wang

Physics-constrained and peak-aware hybrid deep learning for ultra-short-term photovoltaic power forecasting

Accurate prediction of ultra-short-term photovoltaic (PV) power is crucial for ensuring the safe and stable operation of the power grid and promoting the efficient integration and utilization of renewable energy. Existing data-driven models have significant limitations in handlin...

Lightweight multiscale time-series mixing with periodic encoding and physical constraints for ultra-short-term photovoltaic power forecasting

Photovoltaic (PV) power generation is crucial to modern power systems, yet its output exhibits significant randomness, volatility, and periodicity due to factors like solar irradiance and cloud cover, posing severe challenges to grid dispatch. Existing ultra-short-term forecastin...