Dynamic optimization technique for control of HVAC system utilizing building thermal storage

This paper proposes a dynamic optimization technique for building heating and cooling systems. The proposed algorithm returns trajectories for space temperature setpoints throughout a specified period that will minimize objective functions such as running cost or peak energy consumption. It can be applied to buildings for which the thermal mass allows various choices of temperature setpoints. The algorithm also specifies an optimal on-off schedule for HVAC equipment. The discussion includes modeling of the building's thermal characteristics, optimization techniques, and example studies.