Electricity price forecasting across Norway's five bidding zones in the post-crisis era
Predicting electricity prices when market conditions have dramatically shifted
When Norway's electricity market was hit by the 2021–2022 energy crisis and closer ties to Continental Europe, old forecasting models stopped working reliably. Researchers tested eight different forecasting approaches across Norway's five bidding zones and found that a machine learning method called LightGBM performed best, achieving error margins of 1.64 to 5.74 EUR per megawatt-hour—but surprisingly, simpler models using just past prices and calendar dates came close. The key insight: external factors like reservoir levels and gas prices matter less for accuracy in normal times, but become essential for predicting how far off forecasts will be when markets get stressed.
Norway's electricity traders, grid operators, and energy companies rely on accurate price forecasts to make buying and selling decisions worth millions of euros daily. The old models trained on pre-crisis data were giving them false confidence in their predictions. This research provides updated benchmarks that work across all five zones, and shows traders which models and feature combinations to trust—and critically, when those models are likely to fail. The finding that simpler models work just as well in routine conditions could save companies from overcomplicating their systems, while the warning about stressed regimes gives decision makers a concrete signal for when to add extra caution to their bets.