Development of an optimal control method of chilled water temperature for constant-speed air-cooled water chiller air conditioning systems

Constant-speed air-cooled water chillers (CAWCs) are typically on–off controlled in accordance with a fixed set point of chilled water return temperature (T_wr), which seriously restricts their efficiency during part load conditions. To improve the performance of CAWC air conditioning (A/C) systems, this paper developed an optimal control method to reset the T_wr of CAWCs real time. Firstly, a simulation platform was established based on an actual office building with a CAWC A/C system using fan coil units (FCUs) as terminal devices in Beijing. Secondly, a dataset of optimal values of T_wr at different part load conditions was calculated by simulation. Thirdly, to enable the practical use of the dataset, a general regression neural network (GRNN) model was built to predict the optimal T_wr value according to three ambient parameters and one operation parameter. Finally, a GRNN based optimal control method was developed for the CAWC/FCU A/C system. The numerical results demonstrated that the proposed method can achieve a good control over indoor thermal environment, and lead to a reduced energy use for the A/C system by 11.0% over the cooling season. This study provided a promising control method of chilled water temperature for CAWC/FCU A/C systems in dry climates.