Abstract
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.
Highlights
Whilst day ahead electricity price forecasting has been a topic of substantial and wide-ranging research in terms of methods, the focus has mostly been upon price levels for the delivery periods the following day
We provide a new formulation with a focus upon price spreads, and we forecast the density functions for the intraday spreads in the day-ahead prices
The p-values are displayed in Figure 25 and the results show that out of 276 spreads: (a) the skew type distribution is significantly better at forecasting the spreads 161 times at 5% and 15 times at 10%
Summary
Whilst day ahead electricity price forecasting has been a topic of substantial and wide-ranging research in terms of methods, the focus has mostly been upon price levels for the delivery periods (usually hourly) the following day. We provide a new formulation with a focus upon price spreads, and we forecast the density functions for the intraday spreads in the day-ahead prices. If the risk is a consideration, analysis of the mean differences in price levels would be inadequate, and we directly estimate the density functions of all hourly spreads in prices at the day-ahead stage. These forecasts ahead of the day-ahead auctions would be needed to help traders decide whether they want to be buyers or sellers at each hour and thereby optimise their bids and offers. Estimation and forecasting of these arbitrage spreads are new and computationally-intensive
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