某医药检测中心冰蓄冷空调系统智慧运维云平台技术应用
Technology application of intelligent operation and maintenance cloudplatform in ice storage air conditioning system of a medical testing center
摘要：
针对公共建筑集中空调系统运行能耗高、智慧运维水平低的问题,以某医药检测中心冰蓄冷空调系统为例,介绍了基于大数据分析的智慧运维云平台在冰蓄冷空调系统中的应用。部署于云平台的智慧运维技术包括故障诊断规则库、故障图谱诊断及时间表优化控制算法,并通过项目实际运行数据对故障诊断效果和节能控制效果进行了分析。结果表明,故障诊断规则库可以有效检测到冰蓄冷空调系统中暖通设备的运行故障和参数异常,故障图谱诊断可实现对具体故障的定位与溯源,帮助运维人员及时采取设备维修措施。冰蓄冷空调系统应用时间表优化算法后,典型月节能率为7.46%,节费率为11.08%。
Abstract：
In order to solve the problems of high energy consumption and low level of intelligent operation and maintenance of centralized air conditioning system in public buildings, this paper takes the ice storage air conditioning system of a medical testing center as an example to introduce the application of the intelligent operation and maintenance cloud platform based on big data analysis. The intelligent operation and maintenance technology deployed on the cloud platform includes fault diagnosis rule base, fault graph diagnosis and schedule optimal control algorithm, and the effects of the fault diagnosis and energy saving control are analysed through the actual project operation data. The results show that the fault diagnosis rule can effectively detect the operation faults and parameter anomalies of HVAC equipment in the ice storage air conditioning system. The fault graph diagnosis can locate and trace the specific faults in order to help the maintenance staff to take timely equipment maintenance measures. With the application of schedule optimal algorithm in the ice storage air conditioning system, the typical monthly energy saving rate is 7.46% and the cost saving rate is 11.08%.
Keywords:ice storage air conditioning system; intelligent operation and maintenance; fault diagnosis rule; fault graph; optimal control; energy saving; cost saving