Probabilistic load forecasting in Europe: Capturing meteorological, socio-economic and political risks

Electricity in Europe is delivered through an interconnected grid that requires continuous balancing of supply and demand while large-scale storage remains limited. Trading, contracting and generation decisions therefore rely on high-resolution mid-term load forecasts capturing cross-country dependencies and uncertainty in meteorological, socio-economic and political conditions. Yet fine-resolution models at this horizon remain scarce—and probabilistic multivariate frameworks across countries rarer still. We propose a novel probabilistic mid-term forecasting model for hourly electricity demand that is multivariate across 24 European countries. Demand is decomposed within an interpretable Generalized Additive Model (GAM) into calendar and temperature effects, including a climate trend, an endogenously retrieved unit-root socio-economic and political component, and short-term autoregressive deviations. Uncertainty in these components is modeled jointly across countries and propagated through forecasted trajectories. In a forecasting study based on more than nine years of hourly data (2015–2024), the model outperforms standard benchmarks in terms of Continuous Ranked Probability Scores. The latent socio-economic component is shown to align with external macroeconomic, energy-market and uncertainty indicators. Beyond probabilistic forecasting, the trajectory-based design enables gigawatt-level attribution of individual drivers under risk scenarios. We demonstrate this by showing how extreme weather events translate into country-specific demand deviations, revealing elevated cold-weather vulnerability in countries with high shares of electric heating. • Interpretable GAM decomposes mid-term load into calendar, weather, state, AR. • Multivariate errors capture cross-country dependence in all stochastic drivers. • Endogenous socio-economic state shows unit-root trends and aligns with indicators. • One-year study for 24 countries improves CRPS and spans COVID and energy crisis.