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nMAE (normalised Mean Absolute Error) is the average gap between forecast and actual production, expressed as a percentage of the plant's installed capacity: the lower, the better. In our real day-ahead cases, nMAE is 5.98% for wind and 1.67% for solar.
A model can win every benchmark and still cost you money. We work on what actually drives your financial result: local calibration, correction based on each site's historical patterns, and forecasting down to the individual turbine.
For wind, an AI-native digital twin of each plant, calibrated for high winds and rapid ramps. For solar, a physical model of the plant corrected by a machine learning layer.
A smaller gap between forecast and actual production means lower imbalance costs. On a 120 MW wind farm this can cut imbalance costs by 25-38%, worth around €1 million per year. We'll estimate the saving on your own portfolio together with you.
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