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Evaluation of the energy performance of variable refrigerant flow systems using dynamic energy benchmarks based on data mining techniques
Applied Energy ( IF 11.2 ) Pub Date : 2017-10-16 , DOI: 10.1016/j.apenergy.2017.09.116
Jiangyan Liu , Jiangyu Wang , Guannan Li , Huanxin Chen , Limei Shen , Lu Xing

The variable refrigerant flow (VRF) system has extremely different energy performance at various operation conditions. Its power consumption is inconsistent even under the steady operation condition. In order to accurately evaluate the VRF system’s dynamic energy performance, this study proposed a data-mining-based method to benchmark and assess its energy uses. The correlation analysis is used for key factors selection and the interquartile range rule is employed to remove outliers of the database. In addition, the power consumption patterns are classified using decision tree (DT) method. The classification results are validated by the ANOVA analysis and post hoc test. Nine energy benchmarks are established based on the classified power consumption patterns. Moreover, an energy consumption rating system is established to provide quantitative assessment on the power consumption of the VRF system. A case study is conducted by comparatively analyzing the energy performance of the VRF system at multiple refrigerant charge fault cases. Results show that both the PLR and OT significantly affected the power consumption of the VRF system. However, the degree to which the refrigerant charge fault affects system power consumption varies with the power consumption patterns. For different patterns, the power consumptions of the VRF system were either lower, higher or similar to each other at various RCLs. Results also suggest that the energy benchmarking process provide reasonable classification criteria, and the grading process provide quantitative assessment on the energy consumption. Therefore, the proposed dynamic energy benchmarks are reliable and reasonable to evaluate the dynamic energy performance of VRF systems.



中文翻译:

基于数据挖掘技术的基于动态能量基准的可变制冷剂流量系统的能量性能评估

可变制冷剂流量(VRF)系统在各种运行条件下的能源性能都极为不同。即使在稳定的工作条件下,其功耗也不一致。为了准确评估VRF系统的动态能源性能,本研究提出了一种基于数据挖掘的方法来基准化和评估其能源使用。相关分析用于选择关键因素,四分位间距规则用于去除数据库的异常值。此外,使用决策树(DT)方法对功耗模式进行分类。分类结果通过ANOVA分析和事后检验进行验证。根据分类的功耗模式,建立了九个能源基准。而且,建立了能耗评估系统,以对VRF系统的能耗进行定量评估。通过比较分析在多个制冷剂充注故障情况下的VRF系统的能量性能,进行了案例研究。结果表明,PLR和OT均显着影响VRF系统的功耗。但是,制冷剂充填故障对系统功耗的影响程度随功耗模式而变化。对于不同的模式,在各种RCL上,VRF系统的功耗彼此较低,较高或相似。结果还表明,能源基准测试过程提供了合理的分类标准,而分级过程则对能耗进行了定量评估。所以,

更新日期:2017-10-16
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