Component-wise optimization for a commercial central cooling plant

Thermal comfort and energy savings are two main goals of heating, ventilation and air conditioning (HVAC) systems. In this paper, the optimization-simulation approach is proposed for effective energy saving potential in a commercial central cooling plant by refining the model of optimal operation for system components and deriving optimal conditions for their operation subject to technical and human comfort constraints. To investigate the potential of energy savings and air quality, a real-world commercial building, located in a hot and dry climate region, together with its central cooling plant is used for experimentation and data collection. Both inputs and outputs of the existing central cooling plant are measured from the field monitoring in one typical week in the summer. Optimization is performed by using empirically-based models of the central cooling plant components. Optimization algorithms implemented on a transient simulation software package, are used to solve the minimization problem of energy consumption for each considered control strategies and predict the HVAC system optimized set-points under transient load. The integrated simulation tool was validated by comparing predicted and measured power consumption of the chiller during the first day of July. Results show that between 3.2% and 11.8% power savings can be obtained by this approach while maintaining the predicted mean vote (PMV) from −0.5 to +1 for most of the summer time.