In order to reduce building energy effectively and substantially, it is necessary to manage operation information and energy use record systematically after the completion of the building and maintain efficiency of systems as an optimal condition through commissioning. Ongoing commissioning is important for improving the energy efficiency of air conditioning systems and should be an essential part of building operation and maintenance. In this study, to perform history data based on-going commissioning using BAS data which occurs actually in the building, performance index and algorithm are suggested and its performance is verified using real building. Because it is difficult to identify soft fault, target of FDD in this study is applying to soft fault and faults occurring in building can be categorized into sensor faults and system/components failures. It is found that performance indices like LMTDev, LMTDcd, Mref, Effpoly, Effmotor, COP have been selected for being physically meaningful and capable of indicating health condition of chiller system through BAS in real building. And, the type of fault occurring in the chiller is varied and its specific logic of fault detection & diagnosis is present and cause of fault deviated from performance index is suggested and fault classifier consisting of rules correlating faults and their impacts on performance index is constructed.
KSP Keywords
Air conditioning systems, Chiller system, Energy Efficiency, Energy use, Fault classifier, Health condition, History data, Ongoing commissioning, Operation information, Optimal conditions, Soft fault
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