To Enhance the Energy Efficiency of Chiller Plants with System Optimization Theory

Abstract

Conventional chiller plants rely on human judgment or control, based on pressure and temperature variables for setting and adjusting component-operating status. However, these methods lack scientific, systematic, and optimal logic and results in imprecise operation and excessive energy consumption. This study proposes a new control model for chiller plant operation. The new model is built upon System Optimization Theory and based on actual cooling capacity for operating adjustment, and with performance, condition, and relevance of each component during actual operation. It also uses an actual case study to test model rationality and efficiency. Test results show that the new control model achieves better energy efficiency operations in the original chiller plant.