4.8 Article

How good are TSO load and renewable generation forecasts: Learning curves, challenges, and the road ahead

Journal

APPLIED ENERGY
Volume 323, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2022.119565

Keywords

Forecasting; Electricity demand; Renewable energy generation; Accuracy; Learning curves

Funding

  1. Research Foundation - Flanders (FWO) , Belgium [1262921N]

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This paper analyzes five years of TSO forecasts for load, wind and solar generation in 16 European countries, and finds that there is still room for improvement in the accuracy of TSO forecasts.
Transmission system operators (TSOs) forecast load and renewable energy generation to maintain smooth functioning of the grid by contracting sufficient generation and reserve capacity. These forecasts are also utilized by third parties, such as energy generators and demand aggregators, in their own forecasting and decision-making pipelines e.g. to determine suitable trading strategies. Inaccurate forecasts by the TSOs can therefore lead to increased balancing needs as well as elevated societal and market costs. The situation is further exacerbated by the challenges arising due to rapidly increasing renewable generation and the effects of the post-Covid era. In this paper, we analyse five years of TSO forecasts for load, wind and solar generation for 16 European countries. More concretely, using a comprehensive set of metrics, we explore relevant questions such as whether there are TSO specific differences in forecast accuracy, and how forecast errors have changed over time and if they can be reduced further. Our results show that while errors tend to increase linearly with demand or renewable generation, most TSOs still have considerable room for improvement in terms of accuracy. The paper concludes with a set of recommendations for TSOs to improve their forecasts, as well as the ENTSO-E transparency platform where we obtained the data used in this study.

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