This research investigates modelling detailed energy behaviours to deal with overheating during summer times in UK domestic buildings using agent-based modelling and dynamic simulation models.
Agent-Based Modelling (ABM) is a new approach for exploring complex systems with interacting autonomous agents. It offers the advantage of modelling the complexity arising from the interactions of individuals’ behaviours. Because of these advantages, ABM is often used to model social systems that consist of interacting, influential and adaptive agents.
To cope with a changing climate, numerous changes to occupant behaviour will be required. These changes should be considered by simulation models, thus, current models have to be further developed so that they can incorporate a range of current and future occupant behaviour, so the accuracy of the information on building performance can be improved.
This research therefore attempts to simulate occupant behaviour in residential buildings in response to overheating in summer. The range of interactions will include agents interacting with the building’s cooling systems, windows, curtains, lighting, etc, and agents would interact with other agents while making decisions. It is proposed to link the model to a dynamic building simulation tool through to allow dynamic representation of occupants’ behaviour, and examine the extent of the effect that occupants have on building thermal performance.
This may help assessing the effectiveness of current measures and policies to reduce energy consumption in residential stock during summer periods.
Also, this model could help traditional energy modelling software to better predict energy use by serving as a supplemental tool. This will benefit in starting to bridge the gap between predicted and actual building performance, and in making better informed decisions during the design phase, resulting in a reduced energy consumption and CO2 emissions from residential buildings.