Forecasting the Intra-Day Spread Densities of Electricity Prices
This work addresses the need for accurate price spread predictions for electricity traders and operators, but it is incremental as it builds on existing density modeling approaches.
The paper tackled the problem of forecasting intra-day electricity price spreads by developing dynamic density functions based on skewed-t distributions, which allowed parameters to respond hourly to factors like weather and demand, and selected the best models using the Pinball Loss function.
Intra-day price spreads are of interest to electricity traders, storage and electric vehicle operators. This paper formulates dynamic density functions, based upon skewed-t and similar representations, to model and forecast the German electricity price spreads between different hours of the day, as revealed in the day-ahead auctions. The four specifications of the density functions are dynamic and conditional upon exogenous drivers, thereby permitting the location, scale and shape parameters of the densities to respond hourly to such factors as weather and demand forecasts. The best fitting and forecasting specifications for each spread are selected based on the Pinball Loss function, following the closed-form analytical solutions of the cumulative distribution functions.