Abstract
We propose a novel concept in energy forecasting and show that averaging day-ahead electricity price forecasts of a predictive model across 28–728 day calibration windows yields better results than selecting only one “optimal” window length. Even more significant accuracy gains can be achieved by averaging over a few, carefully selected windows.
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