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Pregled bibliografske jedinice broj: 1001896

Modelling influential factors of consumption in district heating systems


Maljković, Danica; Balen, Igor; Dalbelo Bašić, Bojana
Modelling influential factors of consumption in district heating systems // Book of Abstracts, 4th International Conference on Smart Energy Systems and 4th Generation District Heating / Henrik Lund (ur.). - Aalborg : Aalborg University , 2015. 59-59. / Lund, Henrik (ur.).
Aalborg: Aalborg University, 2018. 300, 1 (predavanje, međunarodna recenzija, sažetak, znanstveni)


Naslov
Modelling influential factors of consumption in district heating systems

Autori
Maljković, Danica ; Balen, Igor ; Dalbelo Bašić, Bojana

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Book of Abstracts, 4th International Conference on Smart Energy Systems and 4th Generation District Heating / Henrik Lund (ur.). - Aalborg : Aalborg University , 2015. 59-59. / Lund, Henrik - Aalborg : Aalborg University, 2018

Skup
4TH INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND 4TH GENERATION DISTRICT HEATING - AALBORG

Mjesto i datum
AALBORG, DANSKA, 13.-14.11.2018

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
district heating, heat cost allocator, energy efficiency, influential factors, consumption, correlation analysis, two step hierarchical regression analysis

Sažetak
Assessing the influential factors on measured (or allocated) heat consumption in district heating systems is often limited by the available data. Within a project of modelling consumption in district heating systems using machine learning, an access to a complete billing database of the largest Croatian district heating company was granted. These data comprise of the relevant billing data per each consumer from the period from 2010 till 2017. The company supplies approximately 126, 400 final consumers (both households and business) over 375 km of distribution network. The billing database has 40 vectors in a few million single inputs. Additionally, to these data, a questionnaire is distributed to the final consumers in several buildings labelled as “model buildings”, gathering behavioural and demographic data of final consumers (such as occupancy, mode of space usage, heat comfort level, age of occupants, etc.). The two sets of data are then merged, and a correlation analysis is performed. Further, two step hierarchical regression analysis is performed based on variables from billing database in the first step, with added behavioural and demographic variables obtained from the questionnaires in the second step. The models from two steps are compared, tested and interpreted. . Results of the most influential factors on heat consumption in district heating systems are given and the influence of the behavioural/demographic variables on the prediction accuracy of heating consumption is quantified and interpreted.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Strojarstvo



POVEZANOST RADA


Ustanove
Fakultet elektrotehnike i računarstva, Zagreb,
Fakultet strojarstva i brodogradnje, Zagreb,
Energetski institut

Profili:

Avatar Url Bojana Dalbelo-Bašić (autor)

Avatar Url Igor Balen (autor)

Citiraj ovu publikaciju

Maljković, Danica; Balen, Igor; Dalbelo Bašić, Bojana
Modelling influential factors of consumption in district heating systems // Book of Abstracts, 4th International Conference on Smart Energy Systems and 4th Generation District Heating / Henrik Lund (ur.). - Aalborg : Aalborg University , 2015. 59-59. / Lund, Henrik (ur.).
Aalborg: Aalborg University, 2018. 300, 1 (predavanje, međunarodna recenzija, sažetak, znanstveni)
Maljković, D., Balen, I. & Dalbelo Bašić, B. (2018) Modelling influential factors of consumption in district heating systems. U: Lund, H. (ur.)Book of Abstracts, 4th International Conference on Smart Energy Systems and 4th Generation District Heating / Henrik Lund (ur.). - Aalborg : Aalborg University , 2015. 59-59..
@article{article, editor = {Lund, H.}, year = {2018}, pages = {1}, chapter = {300}, keywords = {district heating, heat cost allocator, energy efficiency, influential factors, consumption, correlation analysis, two step hierarchical regression analysis}, title = {Modelling influential factors of consumption in district heating systems}, keyword = {district heating, heat cost allocator, energy efficiency, influential factors, consumption, correlation analysis, two step hierarchical regression analysis}, publisher = {Aalborg University}, publisherplace = {AALBORG, DANSKA}, chapternumber = {300} }