Assessment of a methodology to evaluate constructive systems for industrialization: the case of dwellings in Spain.
Building monitoring systems deliver large volumes of information and advanced data analysis tools are available. A fault detection and diagnosis (FDD) problem in building energy systems can also be regarded as a pure machine learning problem. The aim of this work is to promote FDD with machine learn...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidad Politécnica de Madrid
2024-03-01
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| Series: | Anales de Edificación |
| Subjects: | |
| Online Access: | https://polired.upm.es/index.php/anales_de_edificacion/article/view/5304 |
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| Summary: | Building monitoring systems deliver large volumes of information and advanced data analysis tools are available. A fault detection and diagnosis (FDD) problem in building energy systems can also be regarded as a pure machine learning problem. The aim of this work is to promote FDD with machine learning applications in building environment. As a contribution, in this work raw time data series, obtained from a SCADA, are processed for further pattern construction of a building thermal facility. The thermal facility supplies the DHW, and heating demands of a residential building, consisting of 26 social dwelling units and located at Durango (northern Spain). Data recorded every 24 hours in cumulative values is included in the R software for computing statistical graphs. For DHW and heating consumption meter values, 229 valid data points are obtained, and the daily consumption ranges are between 1.94 - 5.90 m3 and 0 - 547.63 kWh respectively. |
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| ISSN: | 2444-1309 |