Evaluation of Cost-at-Risk related to the procurement of resources in the ancillary services market. The case of the Italian electricity market

Francesco Lisi, Luigi Grossi and Federico Quaglia

Energy Economics, 2023, vol. 121, issue C

Abstract: Measuring the risk exposure of TSOs on the dispatching market is a crucial task for the correct management of liberalized electricity markets. To fill a gap in the literature, the notion of Cost-at-Risk (CaR) is defined in the context of the dispatching market. Moreover, we propose a set of semi-parametric and non-parametric models for the estimation of the Cost at Risk (CaR) for the Italian TSO (Terna) and evaluate the corresponding out-of-sample forecasting performance. The empirical analysis relies on a rich hourly dataset provided by Terna, including several costs’ drivers. The results, in terms of 1-day and 30-day ahead predictions, suggest that the model with the globally best performance is the semi-parametric GAM-GARCH model.

Keywords: Cost-at-risk (caR); Electricity market; Ancillary services; GAM models; Q-GAM models; GARCH models; Quantile regression (search for similar items in EconPapers)
JEL-codes: C01 C14 C22 D81 G32 Q4 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:121:y:2023:i:c:s0140988323001238

DOI: 10.1016/j.eneco.2023.106625

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