A Framework for Fully Automated Performance Testing for Smart Buildings

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Resumé

A significant proportion of energy consumption by buildings worldwide, estimated to ca. 40%, has yielded a high importance to studying buildings’ performance. Performance testing is a mean by which buildings can be continuously commissioned to ensure that they operate as designed. Historically, setup of performance tests has been manual and labor-intensive and has required intimate knowledge of buildings’ complexity and systems. The emergence of the concept of smart buildings has provided an opportunity to overcome this restriction. In this paper, we propose a framework for automated performance testing of smart buildings that utilizes metadata models. The approach features automatic detection of applicable performance tests using metadata queries and their corresponding instantiation, as well as continuous commissioning based on metadata. The presented approach has been implemented and tested on a case study building at a university campus in Denmark.
OriginalsprogEngelsk
TitelThird International Congress on Information and Communication Technology : ICICT 2018, London
RedaktørerXin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
ForlagSpringer
Publikationsdatookt. 2018
Sider235-243
ISBN (Trykt)978-981-13-1164-2
ISBN (Elektronisk)978-981-13-1165-9
DOI
StatusUdgivet - okt. 2018
BegivenhedInternational Congress on Information and Communication Technology - London, Storbritannien
Varighed: 27. feb. 201828. feb. 2018
http://www.icict.co.uk/

Konference

KonferenceInternational Congress on Information and Communication Technology
LandStorbritannien
ByLondon
Periode27/02/201828/02/2018
Internetadresse
NavnAdvances in Intelligent Systems and Computing
Vol/bind797
ISSN2194-5357

Fingeraftryk

Intelligent buildings
Metadata
Testing
Energy utilization
Personnel

Citer dette

Markoska, E., Johansen, A., & Lazarova-Molnar, S. (2018). A Framework for Fully Automated Performance Testing for Smart Buildings. I X-S. Yang, S. Sherratt, N. Dey, & A. Joshi (red.), Third International Congress on Information and Communication Technology: ICICT 2018, London (s. 235-243). Springer. Advances in Intelligent Systems and Computing, Bind. 797 https://doi.org/10.1007/978-981-13-1165-9_21
Markoska, Elena ; Johansen, Aslak ; Lazarova-Molnar, Sanja. / A Framework for Fully Automated Performance Testing for Smart Buildings. Third International Congress on Information and Communication Technology: ICICT 2018, London. red. / Xin-She Yang ; Simon Sherratt ; Nilanjan Dey ; Amit Joshi. Springer, 2018. s. 235-243 (Advances in Intelligent Systems and Computing, Bind 797).
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title = "A Framework for Fully Automated Performance Testing for Smart Buildings",
abstract = "A significant proportion of energy consumption by buildings worldwide, estimated to ca. 40{\%}, has yielded a high importance to studying buildings’ performance. Performance testing is a mean by which buildings can be continuously commissioned to ensure that they operate as designed. Historically, setup of performance tests has been manual and labor-intensive and has required intimate knowledge of buildings’ complexity and systems. The emergence of the concept of smart buildings has provided an opportunity to overcome this restriction. In this paper, we propose a framework for automated performance testing of smart buildings that utilizes metadata models. The approach features automatic detection of applicable performance tests using metadata queries and their corresponding instantiation, as well as continuous commissioning based on metadata. The presented approach has been implemented and tested on a case study building at a university campus in Denmark.",
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author = "Elena Markoska and Aslak Johansen and Sanja Lazarova-Molnar",
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Markoska, E, Johansen, A & Lazarova-Molnar, S 2018, A Framework for Fully Automated Performance Testing for Smart Buildings. i X-S Yang, S Sherratt, N Dey & A Joshi (red), Third International Congress on Information and Communication Technology: ICICT 2018, London. Springer, Advances in Intelligent Systems and Computing, bind 797, s. 235-243, International Congress on Information and Communication Technology, London, Storbritannien, 27/02/2018. https://doi.org/10.1007/978-981-13-1165-9_21

A Framework for Fully Automated Performance Testing for Smart Buildings. / Markoska, Elena; Johansen, Aslak ; Lazarova-Molnar, Sanja.

Third International Congress on Information and Communication Technology: ICICT 2018, London. red. / Xin-She Yang; Simon Sherratt; Nilanjan Dey; Amit Joshi. Springer, 2018. s. 235-243 (Advances in Intelligent Systems and Computing, Bind 797).

Publikation: Bidrag til bog/antologi/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

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T1 - A Framework for Fully Automated Performance Testing for Smart Buildings

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N2 - A significant proportion of energy consumption by buildings worldwide, estimated to ca. 40%, has yielded a high importance to studying buildings’ performance. Performance testing is a mean by which buildings can be continuously commissioned to ensure that they operate as designed. Historically, setup of performance tests has been manual and labor-intensive and has required intimate knowledge of buildings’ complexity and systems. The emergence of the concept of smart buildings has provided an opportunity to overcome this restriction. In this paper, we propose a framework for automated performance testing of smart buildings that utilizes metadata models. The approach features automatic detection of applicable performance tests using metadata queries and their corresponding instantiation, as well as continuous commissioning based on metadata. The presented approach has been implemented and tested on a case study building at a university campus in Denmark.

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Markoska E, Johansen A, Lazarova-Molnar S. A Framework for Fully Automated Performance Testing for Smart Buildings. I Yang X-S, Sherratt S, Dey N, Joshi A, red., Third International Congress on Information and Communication Technology: ICICT 2018, London. Springer. 2018. s. 235-243. (Advances in Intelligent Systems and Computing, Bind 797). https://doi.org/10.1007/978-981-13-1165-9_21