An Efficient Framework to Estimate the State of Charge Profiles of Hydro Units for Large-Scale Zonal and Nodal Pricing Models

Luca Lena Jansen, Georg Thomaßen, Georgios Antonopoulos and Ľuboš Buzna
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Luca Lena Jansen: Faculty of Management Science and Informatics, University of Žilina (UNIZA), 010 26 Žilina, Slovakia
Georg Thomaßen: Joint Research Centre (JRC), European Commission, 1755 LE Petten, The Netherlands
Georgios Antonopoulos: Joint Research Centre (JRC), European Commission, 1755 LE Petten, The Netherlands
Ľuboš Buzna: Faculty of Management Science and Informatics, University of Žilina (UNIZA), 010 26 Žilina, Slovakia

Energies, 2022, vol. 15, issue 12, 1-23

Abstract: The power system is undergoing significant changes so as to accommodate an increasing amount of renewably generated electricity. In order to facilitate these changes, a shift from the currently employed zonal pricing to nodal pricing is a topic that is receiving increasing interest. To explore alternative pricing mechanisms for the European electricity market, one needs to solve large-scale nodal optimization problems. These are computationally intensive to solve, and a parallelization or sequencing of the models can become necessary. The seasonality of hydro inflows and the issue of myopic foresight that does not display the value in storing water today and utilizing it in the future is a known problem in power system modeling. This work proposes a heuristic step-wise methodology to obtain state of charge profiles for hydro storage units for large-scale nodal and zonal models. Profiles obtained from solving an aggregated model serve as guidance for a nodal model with high spatial and temporal resolution that is solved in sequences. The sequenced problem is guided through soft constraints that are enforced with different sets of penalty factors. The proposed methodology allows for adjustments to congestions on short timescales and proves to perform well in comparison to other approaches to this issue suggested in the literature. Following the input profile closely on a long timescale renders good results for the nodal model.

Keywords: energy system modeling; hydro modeling; heuristic; nodal pricing (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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