Coupled vs. separate optimization in industry and energy system defossilization analysis: A German case study.

Area of Science:

• Energy Systems Analysis
• Industrial Ecology
• Techno-economic Modeling

Background:

• Achieving carbon neutrality necessitates decarbonizing energy and industrial sectors.
• These sectors are interconnected through shared resources and energy carriers.
• Existing studies often model these sectors in isolation, neglecting crucial feedback loops.

Purpose of the Study:

• To compare coupled versus sequential optimization of German industry and the energy system.
• To analyze the impact of cross-sectoral feedbacks on resource allocation, emissions, and costs.
• To evaluate the effectiveness of different modeling approaches for achieving carbon neutrality.

Main Methods:

• Utilized a techno-economic model for German industry.
• Employed the energy system model PyPSA-Eur.
• Compared coupled optimization with sequential (soft-linked) optimization.

Main Results:

• Coupled optimization showed similar costs (0.3% lower) but altered resource use compared to sequential modeling.
• Industry favored direct electrification, reduced biomass and hydrogen use, and achieved negative emissions (-24 Mt CO2) under coupled optimization.
• Sequential approaches required more expensive direct air capture to achieve sectoral neutrality.

Conclusions:

• Cross-sectoral feedbacks are critical for accurate resource and emission allocation, particularly for hydrogen use.
• Sequential modeling approaches have limitations in capturing these vital interdependencies.
• Integrated modeling is essential for efficient and effective pathways to carbon neutrality.