000213600 001__ 213600
000213600 005__ 20181123105135.0
000213600 022__ $$a1876-6102
000213600 0247_ $$2doi$$a10.1016/j.egypro.2015.11.758
000213600 037__ $$aCONF
000213600 245__ $$aHeat demand estimation for different building types at regional scale considering building parameters and urban topography
000213600 269__ $$a2015
000213600 260__ $$bElsevier$$c2015
000213600 336__ $$aConference Papers
000213600 520__ $$aThis study aims towards an improved estimation of annual heat demand of the building stock for an entire region. This requires the holistic representation of aspects influencing the heat demand of buildings, namely their geometry, fabric, users and surrounding environment. A large data base for the building stock of the Swiss canton of Geneva was systematically assessed to identify parameters suited for representation of these aspects. Due to the expectable differences in heat demand, the building stock was categorized into 8 building types. For each type a multiple linear regression model was developed to predict the heat demand. An aspect which has so far been neglected by regression models of buildings’ heat demand is the influence of microclimate. Since this aspect is considerably influenced by the surrounding topography, parameters suited for the representation of the urban topography were defined and included in the regression.  The regression analysis revealed that all models were able to explain high shares of the variance (R²: 71.2% to 88.9%). The mean average errors for hotel, health-care, educational and office buildings were ranging between 30.2% and 39.8% while the error for residential buildings was 17.8%. The suitability and of the selected parameters for heat demand prediction was analyzed in detail for the residential building model and revealed that almost all chosen parameters were highly suited.
000213600 6531_ $$aenergy demand
000213600 6531_ $$acity-scale
000213600 6531_ $$abuilding types
000213600 6531_ $$amultiple linear regression
000213600 6531_ $$adensity parameters
000213600 6531_ $$aurban_systems
000213600 6531_ $$aFP7_CINERGY
000213600 6531_ $$aSCCER_FURIES
000213600 700__ $$aSchüler, Nils
000213600 700__ $$aMastrucci, Alessio
000213600 700__ $$0247677$$aBertrand, Alexandre$$g230849
000213600 700__ $$0240622$$aPage, Jessen$$g155816
000213600 700__ $$0240374$$aMaréchal, François$$g140973
000213600 7112_ $$a6th International Building Physics Conference$$cTorino, Italy$$dJune 14-17, 2015
000213600 773__ $$j78$$q3403-3409$$tEnergy Procedia
000213600 8560_ $$ffrancesco.baldi@epfl.ch
000213600 8564_ $$s603015$$uhttps://infoscience.epfl.ch/record/213600/files/IBPC2015_Article_final_PostPrint4infoscience.pdf$$yPostprint$$zPostprint
000213600 909C0 $$0252481$$pIPESE$$xU12691
000213600 909CO $$ooai:infoscience.tind.io:213600$$pconf$$pSTI
000213600 917Z8 $$x238654
000213600 917Z8 $$x238654
000213600 937__ $$aEPFL-CONF-213600
000213600 973__ $$aEPFL$$rREVIEWED
000213600 980__ $$aCONF