Total utility demand prediction system for dwellings based on stochastic processes of actual inhabitants

This article describes a new methodology to calculate the likely utility load profiles (energy such as power, natural gas, space heating and cooling, and other thermal requirements, as well as city water) in a dwelling. This calculation takes into account the behavioural variations of the dwelling inhabitants. The proposed method contains a procedure for cooling load calculations based on a series of Monte Carlo simulations where the heating, ventilating and air conditioning (HVAC) on/off state and the indoor heat generation schedules are varied, time-step by timestep. A data set of time-varying inhabitant behaviour schedules, with a 15-min resolution, generated by the authors in previous studies and validated by a comparison analysis to several field measurement data sets, was integrated into the model. The established model, which is called the total utility demand prediction system, can be applied to, for example, likely estimation of an integrated space maximum requirement, such as the total load of a building or an urban area. In a series of numerical experiments, huge discrepancies were found between the conventional results and those considering the time-varying inhabitant behaviour schedules. In particular, deriving the dynamic state change, of having the HVAC on/off from the inhabitants' schedules, was found to be a significant factor in the maximum cooling and heating loads.