Behavior-Aware Digital Twins for Residential Energy Systems with FMI-Based Cross-Platform Deployment

The electrification of residential buildings,
together with dynamic pricing and distributed renewables,
demands models that capture both physical dynamics and
human behavior. Existing residential Digital Twins (DTs) often
rely on simplified loads or proprietary tools, limiting realism
and deployment. This paper proposes a behavior-aware,
physics-based DT framework for residential energy systems
with cross-platform execution via the Functional Mock-up
Interface (FMI). Selected appliances and thermal systems are
modelled using first-principles formulations, while human
behavior is represented through set points, overrides, and tariff
driven interactions. FMI-compliant models are executed using
open-source tools, demonstrating the approach's feasibility and
suggesting its potential to capture realistic dynamics, preserve
cross-platform fidelity, and support applications in demand
response and user-centric energy management.