Synthetic Multi-Day Electricity Price Forecasting Dataset: Actual Exogenous Forecasts

Synthetic hourly dataset mirroring the structure and statistical behaviour of the household electricity demand, dynamic price signal, and battery state-of-charge profiles from the original dataset. Generated via STL decomposition and block bootstrap resampling, preserving the daily seasonality and long-run trends of each variable while resampling residual noise in 24-hour blocks to maintain short-term autocorrelation and the coupling between demand profiles, price signals, and storage dynamics. The synthetic data retains the statistical properties required to support risk-based scheduling model development as reported in the HELORS 2025 proceedings, without reproducing any original observations directly.