Capturing uncertainties of household decision making with machine learning in an agent-based model

Kurzfassung

Precise modelling of uncertainties in energy system analysis is central for future energy systems. However, it is difficult to bring individual decisions to the system level. We combine the agent-based model AMIRIS (Schimeczek et al. 2023) with a stochastic optimisation and a diffusion model for three flexibility providing technologies, namely PV and storage, heat pumps (Sperber et al. 2020) and electromobility (Wulff et al. 2021). These three micro-models are aggregated with machine learning (ML) to fit the system level.