Development of an Integrated Operating Model for a Cooling System Based on Optimization

This study aimed to enhance the accuracy of chiller system performance predictions by comparing a model based on fixed performance curves with an optimized model tailored to actual operating conditions. Key performance indicators, including Capacity, Coefficient of Performance (COP), and Fraction of Full Load (FFLP), were adjusted to align with operational data. Results indicated that the existing model, reliant on fixed experimental conditions, failed to adequately reflect dynamic operational changes, leading to discrepancies between predicted and actual power consumption. In contrast, the optimized model effectively incorporated real-time conditions, resulting in improved prediction accuracy and significantly reduced prediction errors. This underscores the necessity of refining performance curves for accurate chiller system predictions to enhance energy efficiency and cost savings. Future research should validate the effectiveness of this optimization method across diverse environments and develop real-time performance monitoring and optimization technologies using digital twin technology.