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Pregled bibliografske jedinice broj: 908055

Zbornik radova

Autori: Krstić, Hrvoje; Teni, Mihaela
Naslov: Analysis of energy performance and buildings characteristics obtained from Croatian energy management information system
( Analysis of energy performance and buildings characteristics obtained from Croatian energy management information system )
Izvornik: International Journal of Structural and Civil Engineering Research / Jay Kim ; Jang-Ho (ur.). -
Skup: International Conference on Architecture, Materials and Construction (ICAMC 2017)
Mjesto i datum: Amsterdam, Nizozemska, 11-13.12.2017.
Ključne riječi: Energy management information system, public sector buildings database, building characteristics, building technology, statistical analysis
( Energy management information system, public sector buildings database, building characteristics, building technology, statistical analysis )
Sažetak:
Analysis presented in this paper utilizes large-scale public sector buildings database obtained from the Croatian energy management information system – EMIS. EMIS system is an on-line application for monitoring and analysis of energy and water consumption in Croatian buildings. Those buildings are mostly public sector buildings, buildings owned by cities, counties and the Government of the Republic of Croatia. Part of EMIS system database presented in this paper comprises over 3500 public sector buildings and contains among other complex data relevant information regarding buildings characteristics and their energy performance. Analysis presented in this research was done in order to statistically analyze buildings from EMIS system database according to their age, purpose, building technology, climatic data, building size and number of users. Further, research results regarding existing average U- values of transparent and opaque parts of buildings as well as energy performance of buildings are also presented. Descriptive statistics of building characteristics for buildings dataset was conducted in order to get the mean value, standard deviation, minimal and maximal values of selected characteristic variables. Presented research is a preliminary analysis for further analysis that is more complex, clustering, machine learning and for the development of energy performance predictive models.
Vrsta sudjelovanja: Predavanje
Vrsta prezentacije u zborniku: Cjeloviti rad (više od 1500 riječi)
Vrsta recenzije: Međunarodna recenzija
Projekt / tema: HRZZ-IP-2016-06-8350
Izvorni jezik: eng
Kategorija: Znanstveni
Znanstvena područja:
Građevinarstvo
URL Internet adrese: http://www.ijscer.com/index.php?m=content&c=index&a=show&catid=148&id=399
Upisao u CROSBI: Hrvoje Krstić (hrvojek@gfos.hr), 27. Stu. 2017. u 10:01 sati
Napomene:
Amsterdam, Netherlands, 11-13 December, 2017. This work has been fully supported by Croatian Science Foundation under Grant No. IP-2016-06- 8350 "Methodological Framework for Efficient Energy Management by Intelligent Data Analytics" (MERIDA).



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