Two-objective online optimization of supervisory control strategy

The  set  points  of  supervisory  control  strategy  are optimized with respect to energy use and thermal comfort for existing HVAC systems. The set point values  of  zone  temperatures,  supply  duct  static pressure, and supply air temperature are the problem variables, while energy use and thermal comfort are the objective functions. The HVAC system model includes   all   the   individual   component   models developed and validated against the monitored data of  an  existing  VAV  system.  It  serves  to  calculate energy use during the optimization process, whereas the   actual   energy   use   is   determined   by   using monitoring   data   and   the   appropriate   validated component  models.  A  comparison,  done  for  one summer  week,  of  actual  and  optimal  energy  use shows that the on-line implementation of a genetic algorithm  optimization  program  to  determine  the optimal  set  points  of  supervisory  control  strategy could  save  energy  by  19.5%,  while  satisfying  the minimum zone airflow rates and the thermal comfort. The results also indicate that the application of the two-objective optimization problem can help control daily energy use or daily building thermal comfort, thus saving more energy  than the application of  the one-objective optimization problem.