摘要
目前,我国标准中提出评价冷水机组节能性能的指标主要有性能系数(Coefficient of Performance, COP)、综合部分负荷性能系数(Integrated Part Load Value, IPLV)和非标准部分负荷性能系数(Non-Standard Part Load Value, NPLV)。IPLV/NPLV作为冷水机组部分负荷性能系数性能评价指标有着重要意义,但是在实际使用中也存在着局限。本文借鉴IPLV/NPLV提出了RPLV(Real Part Load Value, RPLV)计算公式确定方法,可以解决IPLV/NPLV使用过程中的局限,包括(1)可以反映特定项目的实际工况;(2)可以反映多台机组在特定运行策略下的运行情况;(3)可以用该指标简单估算冷水机组实际能耗。同时,本文通过实际工程案例对RPLV计算方法进行了实践应用,证明该方法是切实可行的。此外,本文还对RPLV和IPLV/NPLV从负荷区间划分、权重系数、测试工况、能耗估算适用性等方面进行了关键要素对比分析,总结了RPLV的对比IPLV/NPLV的相同与不同之处,为RPLV的实际应用提供参考借鉴。
At present, Coefficient of Performance(COP), Integrated Part Load Value(IPLV) and Non-Standard Part Load Value(NPLV) are the major indicators proposed in the Chinese standards to evaluate the energy-saving performance of chillers. IPLV/NPLV are significant as the performance evaluation indexes of the chiller part load performance while there are limitations during practical uses. This article proposed a method for determining the RPLV(Real Part Load Value)calculation formula based on IPLV/NPLV, which can solve the limitations in the use of IPLV/NPLV, including(1)reflecting the actual working conditions of a specific project;(2)reflecting the operation of multiple chillers under a specific operating strategy situation;(3)simply estimating the actual energy consumption of the chiller with this indicator. Furthermore, a case study was carried out to prove the RPLV calculation method is feasible. In addition, the key elements of RPLV and IPLV/NPLV in terms of load interval division, weight coefficient, test conditions, applicability of energy consumption estimation, etc. were also compared and summarized in this paper, which can provide references for the practical application of RPLV.
作者
王颖
徐晓燕
王健
吴晓非
陈文震
WANG Ying;XU Xiaoyan;WANG Jian;WU Xiaofei;CHEN Wenzhen(Tongji University,Shanghai 200092;Tongji Architectural Design(Group)Co.,Ltd,Shanghai 200092;Trane Air Conditioning System(China)Co.,Ltd,Shanghai 200051;SensecoTech Energy Technology(Shanghai)Co.,LTD.,Shanghai 200083,China)
出处
《建筑科学》
CSCD
北大核心
2022年第4期205-212,共8页
Building Science