TY - JOUR
T1 - Comparing empirical and model-based approaches for calculating dynamic grid emission factors
T2 - An application to CO2-minimizing storage dispatch in Germany
AU - Braeuer, Fritz
AU - Finck, Rafael
AU - McKenna, Russell
N1 - The authors thank the Energie Consulting GmbH in Kehl- Goldscheuer, Germany, and its managing director Dr. Jürgen Joseph for the provision of the anonymized data of the 50 SMEs. The third author (RM) acknowledges the financial support of the FlexSUS Project (Project nbr. 91352), which has received funding in the framework of the joint programming initiative ERA-Net Smart Energy Systems’ focus initiative Integrated, Regional Energy Systems, with support from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 775970, as well as the Smart City Accelerator project. The usual disclaimer applies.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - 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 .
AB - 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 .
KW - CO emissions
KW - CO-minimizing dispatch
KW - Dynamic emission factors
KW - Empirical emission factors
KW - Energy storage system
KW - German industry
KW - ENERGY
KW - FLEXIBILITY
KW - CO2 EMISSIONS
KW - CO2 emissions
KW - CO2-minimizing dispatch
KW - ELECTRICITY-GENERATION
KW - IMPACTS
UR - http://www.scopus.com/inward/record.url?scp=85084637913&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2020.121588
DO - 10.1016/j.jclepro.2020.121588
M3 - Article
AN - SCOPUS:85084637913
VL - 266
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
SN - 0959-6526
M1 - 121588
ER -