Naslov
Analysis of energy performance and buildings characteristics obtained from Croatian energy management information system

Autori
Krstić, Hrvoje ; Teni, Mihaela

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
International Journal of Structural and Civil Engineering Research / Jay Kim ; Jang-Ho - , 2017, 252-258

Skup
International Conference on Architecture, Materials and Construction (ICAMC 2017)

Mjesto i datum
Amsterdam, Nizozemska, 11.12.2017. - 13.12.2017

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
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.

Izvorni jezik
Engleski

Znanstvena područja
Građevinarstvo

Napomena
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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