Intelligent Energy Costs and Comfort Management in Office Buildings

There is a strong relationship between occupants’ comfort conditions and their level of productivity. Indoorenvironment has an impact on the mental and physical performance of occupants that influence their level ofproductivity. Generally, occupants in a shared space, have varied preferences over the indoor environment conditions.Moreover, their perception of the indoor environment, such as their thermal and visual sensations depend on theirpositions inside enclosed spaces. For energy management system, inability to acknowledge occupants’ preferences andpersonalized parameters would cause occupants’ productivity losses. Salaries of office workers in commercial buildingsare many times higher than costs of energy consumption, hence, improving office workers’ productivity offerssignificant economic benefits. The main interest of this research is to propose a Multi-Objective Optimization (MOOP)method for intelligent energy and comfort management in office buildings. Occupants’ different thermal and visualpreference and behavior models, as well as their positions inside the rooms and tasks they performed, are the parametersconsidered during decision-making. Personalized parameters, alongside energy prices and indoor and outdoor weatherconditions, are included in the MOOP method problem formulation for hourly automated control of the indoorenvironment. Intelligent energy and management system, enhanced with the MOOP method simultaneously optimizeenergy costs, thermal comfort, visual comfort, and IAQ of the occupants. The operation of the proposed method isstudied by energy performance simulation of an office building, located in Montreal, Canada. Based on providedresults, the importance of personalization of energy and comfort for occupants’ productivity improvement is observed.Moreover, different capabilities of the method in taking situation-specific decisions, suitable for intelligent energymanagement system are confirmed.

Keywords:

Intelligent Buildings , Energy Efficiency , Building Simulation , Comfort Conditions , Productivity