Author(s)

TIM TRÖNDLE, RUCHI CHOUDHARY

Abstract

Energy use in the urban residential sector corresponds directly to operation of energy consuming devices. For instance, space-heating is a substantial element of residential energy consumption in the UK, but it is as much tied to occupant preferences and timing of their presence in a home, as it is to the physical characteristics of the dwelling. Timing, duration, and in-use efficiency of residential energy consumption are essential for increasing the utilization of district energy systems and demand-side management. The ongoing IEA-EBC Annex 66 and our own recent work attests that there is a need to develop new methods to represent occupant presence and energy consuming activities in energy demand modelling. This is as much a multi-scale simulation issue, as it is a computational challenge. This paper presents a proof-of-concept methodology of estimating thermal energy demand on the urban scale by introducing occupancy models to high resolution bottom-up energy models. A synthetic population is created from census data and the occupancy of every citizen is modelled using a time heterogeneous Markov chain which is calibrated using time use survey data. The methodology is applied to a case study where the thermal energy demand is found to be varying up to 50% in different locations at certain times of the week. Regions with less diverse energy demand and thermal power patterns can be identified and discriminated against those with more diversity in the demand.

Keywords

residential building occupancy, building energy model, agent-based model, population synthesis, micro-simulation