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Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices

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  • Maciejowska, Katarzyna
  • Nitka, Weronika
  • Weron, Tomasz

Abstract

In recent years, a rapid development of renewable energy sources (RES) has been observed across the world. Intermittent energy sources, which depend strongly on weather conditions, induce additional uncertainty to the system and impact the level and variability of electricity prices. Predictions of RES, together with the level of demand, have been recognized as one of the most important determinants of future electricity prices. In this research, it is shown that forecasts of these fundamental variables, which are published by Transmission System Operators (TSO), are biased and could be improved with simple regression models. Enhanced predictions are next used for forecasting of spot and intraday prices in Germany. The results indicate that improving the forecasts of fundamentals leads to more accurate predictions of both, the spot and the intraday prices. Finally, it is demonstrated that utilization of enhanced forecasts is helpful in a day-ahead choice of a market (spot or intraday), and results in a substantial increase of revenues.

Suggested Citation

  • Maciejowska, Katarzyna & Nitka, Weronika & Weron, Tomasz, 2021. "Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices," Energy Economics, Elsevier, vol. 99(C).
    • Handle: RePEc:eee:eneeco:v:99:y:2021:i:c:s014098832100178x
    DOI: 10.1016/j.eneco.2021.105273
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    References listed on IDEAS

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