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cs.LG2026
UniWind: Day-Ahead Wind Power Forecasting via Physics-Informed State Routing
Ronghui Xu, Tongxin Wu, Guozhen Zhang +4
Accurate day-ahead wind power forecasting is essential for cost-effective power-system operation. Wind power generation is primarily driven by future meteorological conditions whil…
cs.LG2026
REnergy: A Large-Scale Benchmark for Robust Renewable Energy Forecasting under Diverse and Extreme Conditions
Zhi Sheng, Yuan Yuan, Guozhen Zhang +1
The rapid expansion of renewable energy, particularly wind and solar power, has made reliable forecasting critical for power system operations. While recent deep learning models ha…