Energy-saving potential analysis for a 24-hour operating chiller plant using the model-based global optimization method

Abstract

Various studies have been conducted to develop energy efficient measures for chiller plants. In these studies, much attention has been paid to equipment retrofits and various optimal operation strategies, while some measures may interfere with building normal use, like conflicting with the factory's 24-hour production schedule. How much energy saving potential could be obtained from non-interfere measures remains unknown. Therefore, a full-performance simulation chiller plant model was first built based on the Modelica language and then hierarchically calibrated using measured data. Subsequently, the optimization variables were selected based on three principles proposed in this study. An optimization framework based on GenOpt-Dymola was established for the holistic optimization problem, and a chiller plant located in Shanghai, China was used to investigate the energy-saving potential. The results showed that the average global energy-saving rate of the chiller plant reached 8.5% just by optimizing the setpoints in the original control strategy. The largest contribution to energy savings came from the water pumps, which benefited from lowering the chilled water supply temperature, although this reduced the chiller efficiency. Overall, this work can help engineers select appropriate optimization variables that can be easily deployed and can achieve significant energy savings.