Publication Details

Category Text Publication
Reference Category Book chapters
DOI 10.1109/EEM68581.2026.11589624
Title (Primary) Exploring Germany’s national energy and climate plan using stochastic optimization
Title (Secondary) 2026 22nd International Conference on the European Energy Market (EEM), Trondheim, Norway, 22-24 June 2026
Author Gutjahr, S.; Esmaeili Aliabadi, D. ORCID logo ; Moskalenko, N.; Löffler, K.; Thrän, D. ORCID logo
Source Titel EEM
Year 2026
Department SANA
Volume 2026
Language englisch
Topic T5 Future Landscapes
Keywords Modeling; Energy; Renewable energy sources; Meteorology; Wind; Optimization models; Availability; Printing; Climate; Costing
Abstract The energy sector is the biggest contributor to greenhouse gas emissions. The need to decarbonize the energy sector leads to increasing investment in renewable energy sources. While variable renewable energy (VRE) such as wind and solar photovoltaics introduces fluctuations, depending on weather variability, bioenergy - with its inherent flexibility can mitigate the negative impacts of the intermittency on a netzero emissions energy system. Furthermore, biomass removes atmospheric carbon dioxide, assisting us to reach climate goals. This work presents the integration of stochasticity into the extended bioenergy optimization model (BENOPTex) to analyze the interplay between VRE and dispatchable bioenergy. The findings demonstrate that for large amounts of solar and wind energy, the overall system cost is at the minimum, whereas during shortages, flexible bioenergy can support meeting electricity demand but at a higher system cost.
Gutjahr, S., Esmaeili Aliabadi, D., Moskalenko, N., Löffler, K., Thrän, D. (2026):
Exploring Germany’s national energy and climate plan using stochastic optimization
2026 22nd International Conference on the European Energy Market (EEM), Trondheim, Norway, 22-24 June 2026
EEM 2026
Institute of Electrical and Electronics Engineers (IEEE), New York, NY,
10.1109/EEM68581.2026.11589624