Comparing empirical and model-based approaches for calculating dynamic grid emission factors: An application to CO2-minimizing storage dispatch in Germany

Fritz Braeuer*, Rafael Finck, Russell McKenna

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

As one possibility to increase flexibility, battery storage systems (BSS) will play a key role in the decarbonization of the energy system. The emissions-intensity of grid electricity becomes more important as these BSSs are more widely employed. In this paper, we introduce a novel data basis for the determination of the energy system's CO2 emissions, which is a match between the ENTSO-E database and the EUTL databases. We further postulate four different dynamic emission factors (EF) to determine the hourly CO2 emissions caused through a change in electricity demand: the average emission factor (AEF), the marginal power mix (MPM), the marginal system response (MSR) and an energy-model-derived marginal power plant (MPP). For generic and battery storage systems, a linear optimization on two levels optimizes the economic and environmental storage dispatch for a set of 50 small and medium enterprises in Germany. The four different emission factors have different signaling effects. The AEF leads to the lowest CO2 reduction and allows for roughly two daily cycles. The other EFs show a higher volatility, which leads to a higher utilization of the storage system from 3.4 to 5.4 daily cycles. The minimum mean value for CO2 abatement costs over all 50 companies is 14.13 €/tCO2 .

Original languageEnglish
Article number121588
Number of pages12
JournalJournal of Cleaner Production
Volume266
Early online date26 Apr 2020
DOIs
Publication statusE-pub ahead of print - 26 Apr 2020

Keywords

  • CO emissions
  • CO-minimizing dispatch
  • Dynamic emission factors
  • Empirical emission factors
  • Energy storage system
  • German industry

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Environmental Science(all)
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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