Systematic Method for the Energy-Saving Potential Calculation of Air-Conditioning Systems via Data Mining. Part I: Methodology

被引：3

作者：

Ma, Rongjiang ^{[1
,2
]}

Yang, Shen ^{[1
,3
]}

Wang, Xianlin ^{[1
,4
,5
]}

Wang, Xi-Cheng ^{[4
,5
]}

Shan, Ming ^{[1
]}

Yu, Nanyang ^{[2
]}

Yang, Xudong ^{[1
]}

机构：

[1] Tsinghua Univ, Dept Bldg Sci, Beijing 100084, Peoples R China

[2] Southwest Jiaotong Univ, Sch Mech Engn, Chengdu 610031, Peoples R China

[3] Ecole Polytech Fed Lausanne, Sch Architecture Civil & Environm Engn, Human Oriented Built Environm Lab, CH-1015 Lausanne, Switzerland

[4] State Key Lab Air Conditioning Equipment & Syst E, Zhuhai 519070, Peoples R China

[5] Gree Elect Appliances Inc, Zhuhai 519070, Peoples R China

来源：

ENERGIES | 2021年 / 14卷 / 01期

关键词：

energy saving potential; data mining; recognition; optimization; operational data; FAULT-DIAGNOSIS; CONSUMPTION; BUILDINGS;

D O I：

10.3390/en14010081

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Air-conditioning systems contribute the most to energy consumption among building equipment. Hence, energy saving for air-conditioning systems would be the essence of reducing building energy consumption. The conventional energy-saving diagnosis method through observation, test, and identification (OTI) has several drawbacks such as time consumption and narrow focus. To overcome these problems, this study proposed a systematic method for energy-saving diagnosis in air-conditioning systems based on data mining. The method mainly includes seven steps: (1) data collection, (2) data preprocessing, (3) recognition of variable-speed equipment, (4) recognition of system operation mode, (5) regression analysis of energy consumption data, (6) constraints analysis of system running, and (7) energy-saving potential analysis. A case study with a complicated air-conditioning system coupled with an ice storage system demonstrated the effectiveness of the proposed method. Compared with the traditional OTI method, the data-mining-based method can provide a more comprehensive analysis of energy-saving potential with less time cost, although it strongly relies on data quality in all steps and lacks flexibility for diagnosing specific equipment for energy-saving potential analysis. The results can deepen the understanding of the operating data characteristics of air-conditioning systems.

引用

页数：15

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