In the research project iKlimEt, we develop cutting-edge open-source simulation tools for integrated energy system planning that consider climate change impacts and extreme events.

The innovative approach, based on optimization, machine learning, and energy analytics methods, focuses on the critical interfaces between: climate models and energy system models on the generation side (in particular climate scenarios and their impact on the generation of renewable energy sources); and, the impact of climate change and climate policy on the demand side (on the evolution of energy demands of different sectors). To this end, a Climate-and-Energy-System Translator and an Energy-Demand Tool will be designed. Together, they enable the automated translation of climate scenarios into time series with high spatial and temporal resolution: of the generation side (capacity factors, temperature, inflows); as well as the demand side (disaggregated by final energy use). These time series serve as inputs for a flexible and modular sector-coupled energy system optimization model (electricity, gas/hydrogen, heating/cooling, transport, demand-side management), which determines optimal expansion and operating decisions. The validation of the simulation tools is carried out in a case study of the energy system of Energienetze Steiermark (embedded in the Austrian and European context) aligned with Austria’s climate neutrality goals of 2040. Through this integral approach, iKlimEt closes the prevailing gap between climate and energy system models, thereby making it possible to highly automate comprehensive analyses of climate change adaptations of the energy infrastructure.