Reinforcement Learning Lab

Train the reward policy on real historical irradiance (Open-Meteo archive → pvlib digital twin)

Site

Episodes

Years (ERA5)

Days (if 0 yrs)

Real data

Real-data training fetches genuine past weather (set Years ≥ 1 for multi-year ERA5 history), runs pvlib physics to build production/target curves, then optimizes penalty/bonus/discount rates with a REINFORCE policy gradient.

Training Run History

When	Algorithm	Episodes	Data Source	Best Reward	Rates (P/B/D)
No training runs yet — train a policy above.