A review of challenges and opportunities in occupant modeling for future residential energy demand

Electrified heating and electric mobility are increasing residential electricity demand and, together with distributed energy resources, reshaping load profiles, necessitating substantial investment in distribution grids and flexibility measures. Yet key behavioral factors that drive present and future residential demand remain poorly captured in many demand models. Activity-based, bottom-up models make dependencies explicit, better informing flexible operation and investment in low-carbon technologies.
We review 45 activity-based, bottom-up models and assess coverage of appliances, domestic hot water, space heating and cooling, and electric vehicle charging, which are rarely considered jointly in one integrated model. To our knowledge, this is the first review to include activity-based mobility modeling, thereby identifying methodological gaps in consistent behavior modeling across residential energy services: First, most studies simulate single occupants and overlook interdependencies among household members. Second, predominant approaches are structurally limited in producing temporally consistent activity schedules. Together, these shortcomings hinder a consistent, cross-service representation of household demand and can bias estimates of coincident peaks and residential flexibility. ... mehrWe provide guidelines to overcome these shortcomings and to support high-quality behavioral foundations for future bottom-up demand modeling. Future studies should combine complementary behavioral datasets with sophisticated models (e.g., deep neural networks). Such models can capture complex dependencies to generate high-quality synthetic behavioral data as a basis for future bottom-up residential energy demand modeling. In order to ensure consistent progress in this field, reproducible validation frameworks based on open datasets are needed to enable the benchmarking and comparison of activity-based models.