Robust transmission grid planning under a changing climate: high-resolution models and efficient optimization methods

• Applicant: Professor Dr.-Ing. Christian Rehtanz
• Subject Area: Electrical Energy Systems, Power Management, Power Electronics, Electrical Machines and Drives
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 527339595

To reach climate neutrality a large-scale integration of renewable energy sources and the electrification of other energy sectors such as the climatization and transport sectors is key. For the large-scale integration of renewable energy sources, a robust transmission grid is required. However, the planning process of transmission grids underlies multi-scale uncertainties. Thus, forecasting impacts of possible climate trends or the occurrence of extreme weather events is crucial for planning transmission grids. In addition to multi-scale uncertainty, accurately valuing the potential impacts of electrification of end-use sectors is key to achieve a cost-efficient power system transformation. Therefore, the objective of this project is to develop novel methodologies for robust transmission grid planning in the context of multi-scale uncertainties considering flexible consumers from sector coupling. Firstly, a methodology for modelling uncertainty in multiple time scales within long-term power system planning, with special focus on weather-induced uncertainty will be developed. Secondly, an integrated transmission grid planning model based on a Unit Commitment model will be proposed. Within the stochastic dispatch model not only the operation of conventional power plants and storages is determined, but also the behaviour of sector-coupling technologies in the transport and climatization sectors is optimized. Due to the high problem complexity resulting from the consideration of multi-scale uncertainties, a well-suited solution method is required. Therefore, in a third step, a hybrid decomposition method will be developed. The method will be based on distributed computing and the combination of the Column Generation & Sharing algorithm with state-of-the-art decomposition methods. It will exploit the strengths of the different decomposition methods for achieving enhanced computational performance and enable planning realistic-size power systems. As such, the proposed set of methodologies will provide a framework for robust planning of large-scale power systems. The proposed planning framework will be used to generate optimal development pathways for the European and Chilean transmission grid, and to generate evidence on the impact of weather-induced uncertainties and the transport and climatization sectors on investment decisions.

• DFG Programme: Research Grants
• International Connection: Chile
• Partner Organisation: Agencia Nacional de Investigación y Desarrollo (ANID)
• Cooperation Partner: Dr.-Ing. Ángela Matilda Flores Quiroz