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

Hussain Kazmi and Zhenmin Tao

Applied Energy, 2022, vol. 323, issue C, No S0306261922008753

Abstract: 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.

Keywords: Forecasting; Electricity demand; Renewable energy generation; Accuracy; Learning curves (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (8)

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DOI: 10.1016/j.apenergy.2022.119565

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