Investigating the influence of maintenance strategies on building energy performance: A systematic literature review

被引:19
作者
Alghanmi, Ashraf [1 ]
Yunusa-Kaltungo, Akilu [1 ]
Edwards, Rodger E. [1 ]
机构
[1] Univ Manchester, Dept Mech Aerosp & Civil Engn MACE, Manchester, Lancs, England
关键词
Building energy; Energy consumption; Building maintenance; Fault detection and diagnosis (FDD); Systematic review and meta-analysis; DELTA-T SYNDROME; FAULT-DIAGNOSIS STRATEGY; COOLING WATER-SYSTEMS; HVAC-SYSTEMS; ANOMALY DETECTION; HEATING VENTILATION; SUPERVISORY CONTROL; BAYESIAN NETWORK; SENSOR SELECTION; MODEL;
D O I
10.1016/j.egyr.2022.10.441
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
Worldwide, buildings consume a large amount of energy, and a significant share of this energy is wasted due to system degradation, inappropriate control systems and improper maintenance activities. Fortunately, buildings have become data-intensive, which has led to utilising operation data with the help of data mining technologies to improve building energy performance and cut down on energy waste in the operational stage. A systematic review was undertaken as per the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) procedure to identify studies reporting the relationship between building energy performance and maintenance strategies. The search was applied to five search engines: Compendex, Inspec, Geobase, GeoRef and Web of Science. A total of 192 relevant articles were selected, namely 134 journal articles, 44 conference papers, and 14 review papers. This work highlighted the building energy performance deficiencies, the different condition monitoring techniques (top-down and bottom-up), and the types of faults. Also, the types of input data, algorithms, and the evaluation methods of the proposed strategies were investigated. The operation data is the most popular data form used in the case studies, especially with model-based and data-based techniques, and chiller plants were the most studied systems. Finally, the bibliometric method was used to identify the most influential articles within the field, which could significantly aid the planning of future research activities and networking. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:14673 / 14698
页数:26
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