Optimizing energy consumption and occupants comfort in open-plan offices using local control based on occupancy dynamic data

Abstract

Optimal management of buildings' energy-consuming systems is of great importance for minimizing building energy consumption while satisfying the occupants. Since the operation of building systems are highly dependent on the presence of occupants, considering the dynamic occupancy information has become crucial to reflect the occupancy dynamism within offices and the random patterns in occupant behavior. Thus, occupancy-centered control strategies are required in order to enhance the energy management of buildings. On the other hand, the need for localized and customizable comfort controls is increasing in office buildings to improve the occupants’ satisfaction, and consequently their productivity. To this end, a framework aiming at developing optimal occupancy-centered local control strategies is proposed in this paper. A new simulation-based multi-objective optimization model of the energy consumption in offices is developed to exploit occupancy-related data and evaluate possible local control strategies to select the best ones. A set of real occupancy data collected over a period of one year is fed to the integrated simulation-based optimization model for investigating the energy-saving potentials. Comparing the results shows that a considerable improvement in the indoor comfort condition can be achieved through the application of the proposed framework. We conclude that optimal control strategies not only provide demand-driven control solutions but also optimize building energy performance. The integrated model enables dynamic building energy management according to dynamic occupancy patterns. It avoids over-conditioning that is the result of the application of common practices, which control building systems based on the peak occupancy.