Computing transformation pathways towards a climate neutral energy system

Abstract

The transition of energy infrastructure towards climate neutrality poses significant challenges for infrastructure planners and policymakers. Large-scale energy system models play a fundamental role in evaluating alternative scenarios for future development and enabling informed decision making. However, modeling renewable energy sources and flexibility options requires high spatial and temporal resolution, resulting in some of the largest linear optimization problems tackled. Various approaches have been developed to deal with this complexity, including heuristics, mathematical decomposition, and complexity reduction. This study combines the REMix framework with the parallel solver PIPS-IPM++ to compute transformation paths for the European energy system. This combination can provide insights into the ideal timing for converting natural gas infrastructure to hydrogen and explore the trade-off between investment rates and the remaining carbon budget. First, this talk addresses the computational challenges of solving large linear optimization problems with parallel solvers and discusses the tuning of the decomposition approach to exploit the block structure. Second, it presents insights and key findings on the cost-optimal transformation path of the European energy infrastructure towards climate neutrality. These findings include spatial allocation of capacity and storage, as well as robust network topologies for both power grids and gas pipelines.