Abstract

Energy Management Control Systems (EMCS) in buildings can help reduce the energy consumption while maintaining satisfactory occupant environment. The energy management control strategies have to be developed taking into consideration the thermal behavior of buildings and the thermal, operational characteristics of mechanical systems in buildings. In this thesis, improved EMC algorithms are developed and implemented in a variable air volume HVAC (VAV-HVAC) system. Firstly, HVAC system component dynamic models are developed. Then, several individual improved EMC functions (outdoor air economical cycle, programmed start time, programmed stop time, reset supply air temperature setpoint, occupied time control strategies) are developed and evaluated. Finally, real-time simulations are carried out, in which the results of implementing above improved EMC functions are compared with those of conventional EMC functions. This comparison reveals that the HVAC system with each independent improved function can save 7% to 12% energy. Simulation results also show that a VAV-HVAC system employing all EMC algorithms can save between 14% to 15% energy during summer and winter operation. An optimization methodology to compute optimal setpoints is proposed. These optimal setpoints were used as tracking signals to PI and adaptive control strategies developed in this thesis. The use of optimal setpoints resulted in 17% energy savings. A real-time supervisory EMC platform is developed in which the developed EMC algorithms are embedded. Simulation results showing the typical operation of a VAV-HVAC system under supervisory EMC system are presented.