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Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart Buildings

Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230 Odese, Denmark
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Appl. Syst. Innov. 2019, 2(3), 28; https://doi.org/10.3390/asi2030028
Received: 25 July 2019 / Revised: 21 August 2019 / Accepted: 22 August 2019 / Published: 27 August 2019
Performance testing of components and subsystems of buildings is a promising practice for increasing energy efficiency and closing gaps between intended and actual performance of buildings. A typical shortcoming of performance testing is the difficulty of linking a failing test to a faulty or underperforming component. Furthermore, a failing test can also be linked to a wrongly configured performance test. In this paper, we present Building Metadata Performance Testing (BuMPeT), a method that addresses this shortcoming by using building metadata models to extend performance testing with fault detection and diagnostics (FDD) capabilities. We present four different procedures that apply BuMPeT to different data sources and components. We have applied the proposed method to a case study building, located in Denmark, to test its capacity and benefits. Additionally, we use two real case scenarios to showcase examples of failing performance tests in the building, as well as discovery of causes of underperformance. Finally, to examine the limits to the benefits of the applied procedure, a detailed elaboration of a hypothetical scenario is presented. Our findings demonstrate that the method has potential and it can serve to increase the energy efficiency of a wide range of buildings. View Full-Text
Keywords: performance testing; metadata; smart buildings; schemas; fault detection and diagnostics performance testing; metadata; smart buildings; schemas; fault detection and diagnostics
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Markoska, E.; Johansen, A.; Kjærgaard, M.B.; Lazarova-Molnar, S.; Jradi, M.; Jørgensen, B.N. Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart Buildings. Appl. Syst. Innov. 2019, 2, 28.

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