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Pan-European CVAR-constrained stochastic unit commitment in day-ahead and intraday electricity markets

  • The fundamental modeling of energy systems through individual unit commitment decisions is crucial for energy system planning. However, current large-scale models are not capable of including uncertainties or even risk-averse behavior arising from forecasting errors of variable renewable energies. However, risks associated with uncertain forecasting errors have become increasingly relevant within the process of decarbonization. The intraday market serves to compensate for these forecasting errors. Thus, the uncertainty of forecasting errors results in uncertain intraday prices and quantities. Therefore, this paper proposes a two-stage risk-constrained stochastic optimization approach to fundamentally model unit commitment decisions facing an uncertain intraday market. By the nesting of Lagrangian relaxation and an extended Benders decomposition, this model can be applied to large-scale, e.g., pan-European, power systems. The approach is applied to scenarios for 2023—considering a full nuclear phase-out in Germany—and 2035—considering a full coal phase-out in Germany. First, the influence of the risk factors is evaluated. Furthermore, an evaluation of the market prices shows an increase in price levels as well as an increasing day-ahead-intraday spread in 2023 and in 2035. Finally, it is shown that intraday cross-border trading has a significant influence on trading volumes and prices and ensures a more efficient allocation of resources.

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Author:Moritz Nobis, Carlo Schmitt, Ralf Schemm, Armin Schnettler
Parent Title (English):Energies
Place of publication:Basel
Document Type:Article
Year of Completion:2020
Date of the Publication (Server):2020/08/07
Issue:Art. 2339
First Page:1
Last Page:35
Special Issue Uncertainties and Risk Management in Competitive Energy Markets
Institutes:FH Aachen / Fachbereich Energietechnik
FH Aachen / Nowum-Energy
collections:Verlag / MDPI
Open Access / Gold
Licence (German):License LogoCreative Commons - Namensnennung