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Hourly CO 2 Emission Factors and Marginal Costs of Energy Carriers in Future Multi-Energy Systems

Author

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  • Felix Böing

    (Forschungsstelle für Energiewirtschaft (FfE) e.V., 80995 München, Germany
    Department of Electrical and Computer Engineering, Technical University of Munich (TUM), 80333 München, Germany)

  • Anika Regett

    (Forschungsstelle für Energiewirtschaft (FfE) e.V., 80995 München, Germany
    Department of Electrical and Computer Engineering, Technical University of Munich (TUM), 80333 München, Germany)

Abstract

Hourly emission factors and marginal costs of energy carriers are determined to enable a simplified assessment of decarbonization measures in energy systems. Since the sectors and energy carriers are increasingly coupled in the context of the energy transition, the complexity of balancing emissions increases. Methods of calculating emission factors and marginal energy carrier costs in a multi-energy carrier model were presented and applied. The model used and the input data from a trend scenario for Germany up to the year 2050 were described for this purpose. A linear optimization model representing electricity, district heating, hydrogen, and methane was used. All relevant constraints and modeling assumptions were documented. In this context, an emissions accounting method has been proposed, which allows for determining time-resolved emission factors for different energy carriers in multi-energy systems (MES) while considering the linkages between energy carriers. The results showed that the emissions accounting method had a strong influence on the level and the hourly profile of the emission factors. The comparison of marginal costs and emission factors provided insights into decarbonization potentials. This holds true in particular for the electrification of district heating since a strong correlation between low marginal costs and times with renewable excess was observed. The market values of renewables were determined as an illustrative application of the resulting time series of costs. The time series of marginal costs as well as the time series of emission factors are made freely available for further use.

Suggested Citation

  • Felix Böing & Anika Regett, 2019. "Hourly CO 2 Emission Factors and Marginal Costs of Energy Carriers in Future Multi-Energy Systems," Energies, MDPI, vol. 12(12), pages 1-32, June.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2260-:d:239448
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    References listed on IDEAS

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    5. Tobias Hübner, 2020. "Small-Scale Modelling of Individual Greenhouse Gas Abatement Measures in Industry," Energies, MDPI, vol. 13(7), pages 1-43, April.
    6. Mustafa Jaradat & Omar Alsotary & Adel Juaidi & Aiman Albatayneh & Asem Alzoubi & Shiva Gorjian, 2022. "Potential of Producing Green Hydrogen in Jordan," Energies, MDPI, vol. 15(23), pages 1-21, November.
    7. Nils Seckinger & Peter Radgen, 2021. "Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050," Energies, MDPI, vol. 14(9), pages 1-22, April.
    8. Müller, Mathias & Blume, Yannic & Reinhard, Janis, 2022. "Impact of behind-the-meter optimised bidirectional electric vehicles on the distribution grid load," Energy, Elsevier, vol. 255(C).
    9. Johannes Röder & David Beier & Benedikt Meyer & Joris Nettelstroth & Torben Stührmann & Edwin Zondervan, 2020. "Design of Renewable and System-Beneficial District Heating Systems Using a Dynamic Emission Factor for Grid-Sourced Electricity," Energies, MDPI, vol. 13(3), pages 1-22, February.
    10. Fleschutz, Markus & Bohlayer, Markus & Braun, Marco & Henze, Gregor & Murphy, Michael D., 2021. "The effect of price-based demand response on carbon emissions in European electricity markets: The importance of adequate carbon prices," Applied Energy, Elsevier, vol. 295(C).
    11. Capone, Martina & Guelpa, Elisa & Verda, Vittorio, 2021. "Multi-objective optimization of district energy systems with demand response," Energy, Elsevier, vol. 227(C).

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