Comparing empirical and model-based approaches for calculating dynamic grid emission factors: An application to CO_2-minimizing storage dispatch in Germany

摘要

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 BSS5 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-modelderived 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(sic)/t(CO2). (C) 2020 Elsevier Ltd. All rights reserved.