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

Author

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  • Luca Lena Jansen

    (Faculty of Management Science and Informatics, University of Žilina (UNIZA), 010 26 Žilina, Slovakia
    Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy)

  • 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)

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.

Suggested Citation

  • Luca Lena Jansen & Georg Thomaßen & Georgios Antonopoulos & Ľuboš Buzna, 2022. "An Efficient Framework to Estimate the State of Charge Profiles of Hydro Units for Large-Scale Zonal and Nodal Pricing Models," Energies, MDPI, vol. 15(12), pages 1-23, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4233-:d:834443
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