In this on-demand webinar, Amperon’s VP of Customer, Elliott Chorn, and meteorologist Arianna Goldstein unveil the Grid Demand Mid-Term Forecast (MTF) the first AI and ECMWF-powered weather-driven demand forecast that extends up to seven months ahead.
They explain how Amperon bridges the gap between short-term and seasonal planning with:
Machine-learning-based interpolation that converts ECMWF’s 6-hour data into hourly precision, improving accuracy by up to 300% over linear models.
51 ensemble forecasts that produce a full range of load outcomes, empowering users to identify risk, opportunity, and convergence signals weeks before they appear on the grid.
Actionable insight into extreme weather and peak demand events proven to capture record PJM and ERCOT load peaks 30+ days in advance.
The result: an unprecedented view of seasonal grid risk and opportunity, enabling energy professionals to hedge smarter, plan generation more effectively, and build confidence in long-range operational decisions.
Key Takeaways
Learn how Amperon’s ECMWF-based MTF redefines mid-term forecasting accuracy.
Understand how probabilistic ensembles improve long-term hedging and scenario analysis.
See validation case studies from PJM and ERCOT showing 30-day early signals of major peaks.
Hear what’s next in load-growth modeling and data-center forecasting in future releases.
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