Tighten the gap between assumed yield and actual.
Combine on-site met-mast and lidar data with mesoscale reanalysis to verify yield assumptions, validate developer forecasts, and tighten dispatch.
The challenge
Most wind farms start operating on a P50 yield assumption that hasn’t been re-verified since financial close. The on-site met masts and lidars that could improve the picture publish to a separate system. The trading desk submits day-ahead nominations off a third-party forecast that nobody benchmarks. Imbalance penalties are the result.
What success looks like
Hub-height
Forecasts and resource estimates at the height turbines actually operate at, not 10 m
Bias-corrected
Mesoscale forecast continuously corrected against on-site measurement history
Audited
Daily forecast-vs-actual scorecard so the value is provable to the trading desk
How WindTwin delivers it
- Mesoscale forecast ingest — ECMWF (HRES & ENS), GFS, ICON, with hub-height interpolation per turbine.
- Met-mast & lidar fusion — on-site measurements weighted into the short-term horizon where they outperform the mesoscale.
- Long-term resource statistics — rolling 12-month rose, Weibull fit, capacity-factor by hour and month, against the P50 you bought the farm on.
- Power-output forecasts derived from your warranted curves plus live availability.
- Daily forecast-vs-actual scorecard — MAE, RMSE, and bias by horizon and turbine, so the trading desk can audit the platform.
Where this lands first
- Imbalance-exposed portfolios — even small forecast accuracy gains pay back quickly.
- Refinancing decisions — a credible long-term resource view changes lending terms.
- Curtailment-heavy regions — knowing when curtailment is likely lets you schedule maintenance into it.
What you need to start
- At least one met mast or on-site lidar stream we can ingest.
- A history of past nominations vs. actual production for the bias backtest.
- Warranted power curves for the turbines on site.
See it backtested on your own data
Send us a month of measured wind and a month of past forecasts. We'll show you what WindTwin would have done with them.
Book a walkthrough