Model selection for continuous commissioning of HVAC-systems in office buildings: A review

Abstract

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Mapping failures in energy and environmental performance of buildings

“…The discipline of building energy commissioning has expanded rapidly in recent years, and now includes retro-commissioning, recommissioning and continuous commissioning, with a series of technical procedures and publications defining processes for identifying and correcting building performance issues [13]- [16]. Automated building commissioning tools are being developed [17], [18], and a range of analysis methods for automated fault detection focus principally on air-handling units (AHUs) and chillers [19]- [26]. A study on improving operational energy performance of buildings identified 21% energy savings through "realistic changes in current building operation patterns" [27], while a broader framework for building performance optimisation highlights the need for links between modelling approaches and implementing appropriate control and automation strategies [28].…”

Analysis of active system operation optimization in office buildings

“…It generates a significant part of the operation and maintenance cost of the university. The reference building represents one of the most common office building type, regarding net floor space, number of levels, used structures, materials and renewables using HVAC systems [5], therefore the conclusions are well applicable in a more generic and broad office building design optimization.…”

Development of building thermal environment emulator to evaluate the performance of the HVAC system operation

“…Several simulation software packages have been developed to improve the energy performance of buildings through improved design and operation (Trčka and Hensen 2010). Verhelst et al (2017) argue that such software should be applied throughout a building's life cycle, particularly to address the "performance gap" that arises when the actual consumption during operation deviates from the energy consumption simulated during the design phase (Wilde 2014). Khoury, Alameddine, and Hollmuller (2017) cited two causes for such divergence: suboptimal operational stage control and suboptimal usage conditions.…”