Intelligent Energy Costs and Comfort Management in Office Buildings

There is a strong relationship between occupants’ comfort conditions and their level ofproductivity. Indoor environment has an impact on the mental and physical performance ofoccupants that influence their level of productivity. Generally, occupants in a shared space, havevaried preferences over the indoor environment conditions. Moreover, their perception of theindoor environment, such as their thermal and visual sensations depend on their positions insideenclosed spaces. For energy management system, inability to acknowledge occupants’ preferencesand personalized parameters would cause occupants’ productivity losses. Salaries of officeworkers in commercial buildings are many times higher than costs of energy consumption, hence,improving office workers’ productivity offers significant economic benefits. The main interest ofthis research is to propose a Multi-Objective Optimization (MOOP) method for intelligent energyand comfort management in office buildings. Occupants’ different thermal and visual preferenceand behavior models, as well as their positions inside the rooms and tasks they performed, are theparameters considered during decision-making. Personalized parameters, alongside energy pricesand indoor and outdoor weather conditions, are included in the MOOP method problemformulation for hourly automated control of the indoor environment. Intelligent energy andmanagement system, enhanced with the MOOP method simultaneously optimize energy costs,thermal comfort, visual comfort, and IAQ of the occupants. The operation of the proposed methodis studied by energy performance simulation of an office building, located in Montreal, Canada.Based on provided results, the importance of personalization of energy and comfort for occupants’productivity improvement is observed. Moreover, different capabilities of the method in takingsituation-specific decisions, suitable for intelligent energy management system are confirmed.

Keywords:

Intelligent Buildings , Energy Efficiency , Building Simulation , Comfort Conditions , Occupant Behavior Model , Productivity