巴黎人票APP

          <dfn id='Txdpii'><optgroup id='Txdpii'></optgroup></dfn><tfoot id='Txdpii'><bdo id='Txdpii'><div id='Txdpii'></div><i id='Txdpii'><dt id='Txdpii'></dt></i></bdo></tfoot>

          <ul id='Txdpii'></ul>

          • 暖通空调杂志社>期刊目次>2017年>第2期

            利用大数据技术探究蓄冷系统制冷机制冷能力最佳范围

            Exploring optimum cooling capacity range of refrigerator in cool storage system using big data technology

            郭华龙[1],潘雷彬[2],应康玺[2],钟珂[1]
            [1]东华大学,[2]上海虹桥国际机场公司

            摘要:

            以上海虹桥国际机场空调系统为例,探究蓄冷系统制冷机制冷能力最佳配比。通过分析空调系统历年运行数据,对蓄冷罐闲置比率进行了评估,利用大数据技术分析了蓄冷罐的闲置状况与近10 a气象参数的相关性。研究结果表明:蓄冷罐闲置比率与日空气平均温度的相关性最高;蓄冷充足保证天数比率高到一定程度时,蓄冷罐闲置比率和冷量成本不再明显下降;新增制冷机的制冷能力最佳范围为10 780~11 400 kW。

            关键词:大数据蓄冷系统制冷机制冷能力气象参数蓄冷罐闲置比率

            Abstract:

            Taking an air conditioning system in Shanghai Hongqiao International Airport as an example, explores the optimum range of cooling capacity of the refrigerator in the cool storage system. Based on the operating data of the air conditioning system, evaluates the idle rate of the storage tank and analyses the correlation between the idle rate of the storage tank and the meteorological parameters in the last ten years using the big data technology. The results show that the idle rate of the storage tank has the highest correlation with mean daily air temperature, and when the guarantee rate of cooling storage capacity to a certain enough high extent, the idle rate of storage tank and the cooling cost no longer significantly decrease, and the optimum range of cooling capacity of new refrigerator is 10 780 to 11 400 kW.

            Keywords:bigdata,coolstoragesystem,coolingcapacityofrefrigerator,meteorologicalparameter,idlerateofstoragetank

                你还没注册?或者没有登录?这篇期刊要求至少是本站的注册会员才能阅读!

                如果你还没注册,请赶紧点此注册吧!

                如果你已经注册但还没登录,请赶紧点此登录吧!