Coupling a stochastic occupancy model to EnergyPlus to predict hourly thermal demand of a neighbourhood
conference contributionposted on 2016-05-11, 13:01 authored by Candy He, Timothy Lee, Simon Taylor, Steven FirthSteven Firth, Kevin LomasKevin Lomas
When designing and managing integrated renewable energy technologies at a community level, prediction of hourly thermal demand is essential. Dynamic thermal modelling, using deterministic occupancy profiles, has been widely used to predict the highresolution temporal thermal demand of individual buildings. Only in recent years has this approach started to be applied to simulate all buildings in a neighbourhood or an entire housing stock of a region. This study explores the potential of predicting hourly thermal demand for a group of dwellings by applying a stochastic occupancy model to dynamic thermal modelling. A case study with 125 new houses demonstrates the approach. The result was a more realistic and representative hourly thermal demand profile, compared to using standard deterministic occupancy profiles.
This work was funded under UK EPSRC grant EP/I002124/1 (Self Conserving Urban Environments – SECURE). SECURE is a consortium of four UK universities: Newcastle, Sheffield, Exeter and Loughborough. Website: https://www.secureproject. org/
- Architecture, Building and Civil Engineering