Explaining Complex Energy Systems: A Challenge (Proposals Track)
Jonas Hülsmann (TU Darmstadt); Florian Steinke (TU Darmstadt)
Abstract
Designing future low-carbon, sector-coupled energy systems is a complex task. The work is therefore often supported by software tools that model and optimize possible energy systems. These tools typically have high dimensional inputs and outputs and are tailored towards domain experts. The final investment decisions to implement a certain system, however, are mostly made by people with little time and prior knowledge, thus unable to understand models and their input data used in these tools. Since such decisions are often connected to significant personal consequences for the decision makers, it is not enough for them to rely on experts only. They need an own, at least rough understanding. Explaining the key rationales behind complex energy system designs to non-expert decision makers in a short amount of time is thus a critical task for realizing projects of the energy transition in practice. It is also an interesting, novel challenge for the explainable AI community.