Pregled bibliografske jedinice broj: 1001896
Modelling influential factors of consumption in district heating systems
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.).
Aaalborg: Aalborg University, 2018. 300, 1 (predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 1001896 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
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 - Aaalborg : Aalborg University, 2018
Skup
4th International Conference on Smart Energy Systems ; 4th Generation District Heating
Mjesto i datum
Aalborg, Danska, 13.11.2018. - 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