芯片厂房洁净空调系统节能运行影响因素研究
摘要：从芯片厂房洁净空调系统的运行特点出发，通过理论分析得到了芯片厂房洁净空调系统的能耗影响因素，通过实测梳理了芯片厂房洁净空调系统的能耗现状及节能潜力。DesignBuilder软件模拟结果表明，冷水机组COP、换气次数、风机效率、新风量、水泵效率、室内设计温度的空调电耗最大节能率分别为39.7%、23.0%、15.4%、11.2%、10.8%、6.0%。SPSS偏相关分析表明，显著性影响因素为冷水机组COP、换气次数和新风量。研究成果可为预期节能量的预测提供依据。
关键词：芯片厂房洁净空调节能运行影响因素能耗模拟偏相关分析
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[3] 袁伟.苏州地区电子类工业建筑能耗评价分析[D].苏州：苏州科技学院，2015:30- 33.
[4] 石静宜.半导体厂房空调系统节能研究[D].西安：西安科技大学，2014:51- 58.
[5] 李欣.制药厂房净化空调系统能耗影响多因素分析与研究[D].天津：天津大学，2014:78- 84.
[6] 孙铭志，姚晶珊.医院住院部空调能耗影响因素分析[J].暖通空调，2019,49(1):101- 105.
[7] 由玉文，曹宝山，李颖，等.洁净空调系统变新风量的节能控制研究[J].洁净与空调技术，2010(2):15- 18.
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[9] HU S C,TSAO J M.A comparative study on energy consumption for HVAC systems of high-tech FABs[J].Applied thermal engineering,2007,27(17/18):2758- 2766.
[10] TSAO J M,HU S C,CHAN D Y L,et al.Saving energy in the make-up air unit (MAU) for semiconductor clean rooms in subtropical areas[J].Energy and buildings,2008,40(8):1387- 1393.
[11] 刘倩，杨昌智，胡攀.长沙市商场建筑能耗影响因素与预测模型构建研究[J].建筑科学，2017,33(12):96- 102.
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Influencing factors of energy efficient operation of clean air conditioning systems in chip workshops
Abstract: Based on the operating characteristics of the clean air conditioning systems in the chip workshops, the energy consumption influencing factors of the clean air conditioning systems in the chip workshops are obtained through theoretical analysis, and the energy consumption status and energy saving potential of the clean air conditioning systems in the chip workshops are combed through actual measurement. The simulation results of DesignBuilder software show that the maximum energy saving rates of air conditioning power consumption of chiller COP, air change rate, fan efficiency, outdoor air rate, pump efficiency and indoor design temperature are 39.7%, 23.0%, 15.4%, 11.2%, 10.8% and 6.0% respectively. SPSS partial correlation analysis shows that the significant influencing factors are chiller COP, air change rate and outdoor air rate. The research results can provide a basis for the prediction of expected energy saving.
Keywords: chip workshop; clean air conditioning; energy efficient operation; influencing factor; energy consumption simulation; partial correlation analysis;
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