Energy analysis of chilled water system configurations using simulation-based optimization

► We developed chilled water system model in Dymola/Modelica. ► We optimized chilled water system at system design and configuration level. ► Estimated initial costs of considered configurations are provided for economic considerations. ► Simulation-based optimization approach proves efficient to find optimal configuration. ► Optimization results in significant energy savings up to 43% for considered cases. The paper presents an incremental development of the methodology for chilled water system design optimization. Initially, the system configuration parameters are varied with fixed design conditions to confirm the established best practice design criteria, followed by a comprehensive system design optimization. The implemented simulation-based optimization approach couples the Dymola/Modelica dynamic modeling and simulation program with GenOpt generic optimization program to find optimal system configuration. A dynamic system model is developed to vary and simulate different chilled water system configurations. Optimization of the chilled water system is achieved at both design and configuration level using five design variables. Two discrete variables are related to system configuration: number of chillers and number of cooling towers and three continuous variables are related to system design: building load demand, temperature difference across condenser, and cooling tower fan speed. The strategy of varying system design and configuration variables together for overall system optimization proved to be the most energy efficient. For a fixed building load demand, power consumption of the considered system can be reduced 17–43% by selecting an optimal system configuration.