冷却装置通常用于向数据中心提供冷却水。虽然冷水机组是为最大预计热负荷设计的，但大多数数据中心产生的热负荷只是设计负荷的一小部分。部分负荷运行的制冷设备可能无法有效运行。由于现场可用数据有限，评估工作中的冷水机组的性能具有挑战性。此外，在进行调整以提高效率后，不可能知道系统将如何运行。在本文中，我们说明了如何使用基于流量网络建模（FNM）技术的科学方法来提高罗切斯特一个实际数据中心的运行效率，并使用FNM技术创建了冷冻水系统（CWS）的计算机模型。 CWS部件的流动和热特性取自液压手册和制造商数据。计算机模型报告了整个CWS的水流量、压力和温度。通过将这些值与有限位置的现场测量值进行比较，验证了这些值。计算机模型显示，由于多个原因，CWS无法有效工作，包括制冷装置内大量冷冻水的再循环、系统部分的流量不平衡以及冷冻水温度低。使用计算机模型对CWS的各种变化进行了测试。提出了降低泵的速度和提高制冷机供应温度等改进措施。实施了这些修改，并在几个月内监测了水煤浆的能耗。 拟议的修改导致能源减少33%至50%，从而使每年的冷却成本减少约60000美元。引用:2017年年度会议，加利福尼亚州长滩，会议论文

Chiller plants are commonly used to provide cooling water to data centers. While chiller plants are designed for the maximum projected heat load, majority of data centers produce a fraction of the design load. Chiller plants that operate at partial load may not perform efficiently. Evaluating the performance of a working chiller plant is challenging because of the limited data available at the site. Moreover, it is not possible to know how the system will perform after making an adjustment to improve the efficiency. In this paper, we illustrate the use of a scientific approach based on the Flow Network Modeling (FNM) technique for improving the operating efficiency of a real-life data center in Rochester, NYA computer model of the Chilled Water System (CWS) was created using the FNM technique. The flow and thermal characteristics of the components of the CWS were taken from hydraulic handbooks and manufacturer data. The computer model reported the water flow rate, pressure, and temperature throughout the entire CWS. These values were validated by comparing them with field measurements at limited locations.The computer model showed that the CWS was not working efficiently for several reasons including recirculation of a large portion of chilled water inside the chiller plant, flow imbalance in parts of the system, and low chilled water temperature. Various alterations to the CWS were tested using the computer model. Modifications such as reducing the speed of the pumps and increasing the chiller supply temperature were proposed. These modifications were implemented and the energy consumption of the CWS was monitored over a few months. The proposed modifications resulted in energy reduction of 33% to 50%, which reduced the annual cooling cost by approximately $60,000.