Time-use data (TUD) have a large potential for improving occupancy and load modelling and for introducingrealistic behavioural patterns into various simulations. In this article, previously developed models of occupancy,activities and energy use based on TUD are extended and described in a general framework. Two extensions arestudied: deterministic conversion of empirical TUD is extended into a complete thermal load model encompassingboth occupancy and various end-uses and a Markov-chain approach for generating synthetic TUD sequences isextended to include a model for load management. Three examples of building-related applications are presented:simulation of indoor climate in a low-energy building, household electricity load management in response to timedifferentiatedelectricity tariffs and simulations of load matching in a net zero energy building. The main conclusionis that the extended model framework can generate detailed and realistic behavioural patterns that allow diversityand correlations between end-uses to be taken into account.