Abstract
Buildings consumed about 40% of primary energy and 70% of the electricity in the U.S. It is well known that most buildings lose a portion of their desired and designed energy efficiency in the years after they are commissioned or recommissioned. Majority of the Heating, Ventilation, and Air-Conditioning (HVAC) systems have multiple faults residing in the systems causing either energy, thermal comfort, or indoor air quality penalties. There are hundreds of fault detection and diagnostics (FDD) algorithms available, but there is lacking a common framework to assess and validate those FDD algorithms. Fault modeling is one of the key components of such a framework. In general, fault modeling has two purposes: testing and assessment of FDD algorithms, and fault impacts analysis in terms of building energy consumption and occupants’ thermal comfort. It is expected that fault ranking from the fault impact analysis can facilitate building facility managers to make decisions. This paper provides a detailed review of current state-of-the-art for the fault modeling of HVAC systems in buildings, including fault model, fault occurrence probability, and fault simulation platform. Fault simulations considering fault occurrence probability can generate realistic faulty data across a variety of faulty operating conditions, and facilitate testing and assessment of different FDD algorithms. They can also help the fault impact study. Three research gaps are identified through this critical literature review: (1) The number of available fault models of HVAC systems is still limited. A fault model library could be developed to cover all common HVAC faults for both traditional and non-traditional HVAC systems. (2) It is imperative to include the fault occurrence probability in fault simulations for a realistic fault impacts analysis such as fault ranking. (3) Fault simulation platforms need further improvements to better facilitate the fault impact analysis.
