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

Ashraf Alghanmi, Akilu Yunusa-Kaltungo, Rodger Edwards

Research output: Contribution to journalReview articlepeer-review


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.

Original languageEnglish
Pages (from-to)14673-14698
Number of pages25
JournalEnergy Reports
Publication statusPublished - 10 Nov 2022


  • Building energy
  • Energy consumption
  • Building maintenance
  • Fault detection and diagnosis (FDD)
  • Systematic review and meta-analysis


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