TY - JOUR
T1 - Comparing open source power system models - A case study focusing on fundamental modeling parameters for the German energy transition
AU - van Ouwerkerk, J.
AU - Hainsch, K.
AU - Candas, S.
AU - Muschner, C.
AU - Buchholz, S.
AU - Günther, S.
AU - Huyskens, H.
AU - Berendes, S.
AU - Löffler, K.
AU - Bußar, C.
AU - Tardasti, F.
AU - von Köckritz, L.
AU - Bramstoft, R.
PY - 2022/6
Y1 - 2022/6
N2 - Recent European and German climate targets call for a faster power system transition towards variable renewable energy sources. With the increasing importance of Open Science, several Open Source models have been developed in recent years. However, only a few studies exist that compare their performance against each other. Therefore, this study performs a comprehensive model comparison of five mature Open Source power sector models. For this purpose, we apply eight fully harmonized and simplified one-year scenarios for the German power sector, to analyze deviations in model results. First, an in-depth analysis of two base scenarios for 2016 and 2030 reveals that linear programming-based models differ substantially from models with pre-implemented dispatch orders. Other deviations occur across all models and are mainly caused by the indifferent use of flexibility options such as storage and transmission. Second, variations of parameters and characteristics with a political significance are individually applied to the 2030 base scenario to identify their impact on model results. This includes CO2 emission budgets, increased demands by sector coupling, coal exit strategies, and renewable generation shares. The results prove that some models are far more sensitive to these parameters than others, and renewable generation shares alone are not sufficient to reach desired effects in emission reductions. Finally, a comprehensive scenario for 2030 combines all measures to evaluate general trends that result from the most recent updates in German energy policy. Model results indicate that the new targets require substantially increased investments into renewable generation capacities, storage, and transmission.
AB - Recent European and German climate targets call for a faster power system transition towards variable renewable energy sources. With the increasing importance of Open Science, several Open Source models have been developed in recent years. However, only a few studies exist that compare their performance against each other. Therefore, this study performs a comprehensive model comparison of five mature Open Source power sector models. For this purpose, we apply eight fully harmonized and simplified one-year scenarios for the German power sector, to analyze deviations in model results. First, an in-depth analysis of two base scenarios for 2016 and 2030 reveals that linear programming-based models differ substantially from models with pre-implemented dispatch orders. Other deviations occur across all models and are mainly caused by the indifferent use of flexibility options such as storage and transmission. Second, variations of parameters and characteristics with a political significance are individually applied to the 2030 base scenario to identify their impact on model results. This includes CO2 emission budgets, increased demands by sector coupling, coal exit strategies, and renewable generation shares. The results prove that some models are far more sensitive to these parameters than others, and renewable generation shares alone are not sufficient to reach desired effects in emission reductions. Finally, a comprehensive scenario for 2030 combines all measures to evaluate general trends that result from the most recent updates in German energy policy. Model results indicate that the new targets require substantially increased investments into renewable generation capacities, storage, and transmission.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85126842546&partnerID=MN8TOARS
U2 - 10.1016/j.rser.2022.112331
DO - 10.1016/j.rser.2022.112331
M3 - Article
SN - 1364-0321
VL - 161
JO - Renewable and Sustainable Energy Reviews
JF - Renewable and Sustainable Energy Reviews
M1 - 112331
ER -