Abstract:
With the continuous increase in demand and cost of electricity, and decrease in production and supply, awareness of energy use is on the rise. This has led to a global demand for construction of energy efficient buildings due to their potential of energy saving and other economic benefits to clients and building operators. The construction industry is facing challenges to ensure that the performance of energy efficient buildings is at par with their design expectations. However enough evidence is available which reveals that these buildings are not performing as per the expectations, resulting into energy performance gap. There could be many reasons for this gap: occupant behavior is one such factor. The divergence between the predicted and actual energy consumption can be linked with the negligence of behavioral influences of occupants during design phase. Occupant behavior is dynamic; it modifies with time under formal and informal influences but energy simulation software assume it as a static entity during energy estimation. It has a lot of potential to save energy; if the behavior is positively reinforced, it can bring very good results in the reduction of the energy usage. In this research the existing behavior classification from literature is used to categorize users as per Low Energy Consumers (LEC), Medium Energy Consumers (MEC) and High Energy Consumers (HEC). Building and occupant data is collected from three office buildings in the major cities of Pakistan. Further, an agent based model is developed based on the behavior modification techniques using the AnyLogic 7® software. The model simulates the number of occupants in different categories and time required by them to change their consumption behavior. Finally, to put the findings into perspective, the effect caused by behavior modification is quantified. Conclusions are drawn and modifications for further work are proposed.
