Research
1 / 5
Multi-model ensemble forecasts combine outputs from several independent atmospheric models, reduce bias, and quantify uncertainty. Lower uncertainty directly cuts imbalance costs in power markets.
2 / 5
EPT-2e outperforms the 50-member ECMWF ENS on both RMSE and CRPS across almost the entire 0–240 hour range while using only 30 members.
3 / 5
Jua’s rapid-refresh models update up to 24 times per day at a tiny share of traditional NWP cost (~0.25 kWh vs. 8,400 kWh), which enables higher-frequency ensemble updates for traders.
4 / 5
Improved forecast accuracy on hub-height wind and surface solar radiation can save €1.5 M–€3 M per year for a 1 GW renewables portfolio under standard hedging structures.
5 / 5
Run EPT-2e head-to-head against your current ensemble provider on your own region and variables.
Jua's EPT-2e outperforms ECMWF ENS on RMSE & CRPS, cutting imbalance costs. See how multi-model ensemble forecasts boost renewables trading accuracy.