This study proposes a real-time chiller capacity control strategy based on marginal Coefficient of Performance (COP) analysis to improve the energy efficiency of air-conditioning systems. The research focuses on the air-conditioning system (ACS) of an office building. Operational data, including chiller capacity and the corresponding COP, were collected to derive the chiller’s operating characteristic curve. The Optimal Capacity Control (OCC) strategy aims to maximize the total COP of all chillers, and the initial capacity allocation is determined using the Lagrange multiplier method. To further refine performance, a fine-tuning mechanism is introduced, calculating the ratio of COP variation to capacity variation (RC ratio) for each chiller to identify which unit should be loaded or unloaded. Based on the fine-tuning mechanism, a comprehensive OCC model is established to ensure that the chiller’s cooling output precisely matches the load demand, thereby maximizing system efficiency and reducing energy consumption. To validate the effectiveness of the proposed OCC strategy, a numerical analysis was implemented using real operational data from the existing ACS. Comparative simulations between the OCC and a Traditional Capacity Control (TCC) strategy were conducted. On a representative summer day, total power consumption decreased from 1534.0 kWh (TCC) to 1527.2 kWh (OCC), while total system COP increased from 113.9 to 114.8. Seasonal analysis further confirms consistent energy savings under varying load conditions. The results indicate that the OCC strategy significantly enhances system performance and reduces energy consumption under varying load conditions. Overall, the proposed method achieves a higher system COP, leading to notable electricity savings and improved operational efficiency of the air-conditioning system.
Hou et al. (Tue,) studied this question.