Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart Buildings
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 underp...
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doaj-24cec3bc0c234581bcde1d494bb171c32020-11-25T02:32:27ZengMDPI AGApplied System Innovation2571-55772019-08-01232810.3390/asi2030028asi2030028Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart BuildingsElena Markoska0Aslak Johansen1Mikkel Baun Kjærgaard2Sanja Lazarova-Molnar3Muhyiddine Jradi4Bo Nørregaard Jørgensen5Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230 Odese, DenmarkMærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230 Odese, DenmarkMærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230 Odese, DenmarkMærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230 Odese, DenmarkMærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230 Odese, DenmarkMærsk Mc-Kinney Møller Institute, University of Southern Denmark, 5230 Odese, DenmarkPerformance 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.https://www.mdpi.com/2571-5577/2/3/28performance testingmetadatasmart buildingsschemasfault detection and diagnostics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Elena Markoska Aslak Johansen Mikkel Baun Kjærgaard Sanja Lazarova-Molnar Muhyiddine Jradi Bo Nørregaard Jørgensen |
spellingShingle |
Elena Markoska Aslak Johansen Mikkel Baun Kjærgaard Sanja Lazarova-Molnar Muhyiddine Jradi Bo Nørregaard Jørgensen Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart Buildings Applied System Innovation performance testing metadata smart buildings schemas fault detection and diagnostics |
author_facet |
Elena Markoska Aslak Johansen Mikkel Baun Kjærgaard Sanja Lazarova-Molnar Muhyiddine Jradi Bo Nørregaard Jørgensen |
author_sort |
Elena Markoska |
title |
Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart Buildings |
title_short |
Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart Buildings |
title_full |
Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart Buildings |
title_fullStr |
Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart Buildings |
title_full_unstemmed |
Combining Performance Testing and Metadata Models to Support Fault Detection and Diagnostics in Smart Buildings |
title_sort |
combining performance testing and metadata models to support fault detection and diagnostics in smart buildings |
publisher |
MDPI AG |
series |
Applied System Innovation |
issn |
2571-5577 |
publishDate |
2019-08-01 |
description |
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. |
topic |
performance testing metadata smart buildings schemas fault detection and diagnostics |
url |
https://www.mdpi.com/2571-5577/2/3/28 |
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