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Two-Product System

EPF produces two distinct forecast products, each aligned to the OMIE market publication schedule and optimized for its decision window.

Why Two Products?

The Spanish day-ahead electricity market (OMIE) follows a strict timeline:

  • ~12:00 UTC — Bidding gate closes
  • ~12:30–13:00 UTC — D+1 prices published

This creates a natural split in forecast usefulness:

  • Before publication — Traders need D+1 forecasts to inform bidding strategy
  • After publication — D+1 prices are known facts; the value shifts to D+2 through D+7 strategic planning

A single forecast product cannot serve both needs well. Predicting already-known prices wastes model capacity, and the information available at 10:00 UTC is fundamentally different from what’s available at 15:00 UTC.

Product Definitions

ProductRun TimeHorizonGroupsKey Feature
D+1 Day-Ahead~10:00 UTC24 hours (D+1 full day)DA1, DA2Predicts before OMIE gate closes
D+2–D+7 Strategic~15:00 UTC144 hours (days 2–7)S1–S5Uses published D+1 prices as features

D+1 Day-Ahead

Generated at approximately 10:00 UTC — before the OMIE bidding gate closes. This gives traders time to incorporate forecasts into their bidding strategies.

The model has access to:

  • All historical prices up to the forecast origin
  • Current weather observations and 7-day weather forecasts
  • Latest commodity prices (TTF gas, ETS carbon)
  • Real-time generation mix and demand data

D+2–D+7 Strategic

Generated at approximately 15:00 UTC — after OMIE publishes D+1 prices. The strategic product covers the next 6 days (D+2 through D+7) and is designed for medium-term planning: maintenance scheduling, portfolio optimization, and risk assessment.

The strategic model has an important additional input: published D+1 prices. These 24 data points are the strongest predictive signal for the days that follow, providing features such as:

  • D+1 daily average, min, max, and standard deviation
  • D+1 peak vs. off-peak spread
  • D+1 price at the same hour-of-day as each target (the single most important feature, accounting for ~26.5% of model importance)

Training Separation

Each product is trained independently using origin-filtered data:

  • Day-ahead models train only on samples from 08:00–12:00 UTC origins — mimicking the morning forecast scenario
  • Strategic models train only on samples from 13:00–18:00 UTC origins — mimicking the afternoon scenario where D+1 is known

This ensures the models learn from realistic information conditions rather than averaging across incompatible scenarios.

Production Schedule

Two automated runs execute daily:

  • ~10:00 UTC — Day-ahead prediction (D+1)
  • ~15:00 UTC — Strategic prediction (D+2 to D+7)

Performance

Based on a 149-day walk-forward backtest (October 2025 — February 2026):

ProductBest ModelMAE (EUR/MWh)Bias (EUR/MWh)
D+1 Day-AheadXGBoost14.85-12.49
D+2–D+7 StrategicEnsemble23.24-0.30

The strategic product benefits from near-zero bias thanks to the MAE loss function and the strong signal from D+1 published prices. The day-ahead product shows higher bias because it lacks this anchor — an area of ongoing improvement through post-prediction bias correction.