New AI Model Improves Power Grid Carbon Footprint Forecasting

Researchers introduced FTimeXer, a frequency-aware transformer that accurately predicts grid carbon intensity by combining Fast Fourier Transform analysis with exogenous variables to handle missing or misaligned data. The model's improved forecasting capabilities enable more reliable product carbon accounting and better decarbonization planning decisions.