Dynamic energy analysis accurately studies the buildings’ thermal behaviour but requires consistent data. The study started with an analysis of the most commonly used occupancy profile databases available. Six were selected, and the impact of database choice was assessed by the simulation of a standard building using EnergyPlus, under different climatic conditions of Reykjavik, London, and Madrid. Nine types of building use profiles were simulated. The resulting energy consumption varied depending on the database used, with percentage differences up to 4000%-6000%, with average differences for cities falling within the range of 500% to 1000%, within the same building use category. Such discrepancies are highlighted as an issue to the wider use of building performance simulation in building design, a solution is proposed by harmonizing all assessed databases into a newly defined one, considered a more robust alternative for application in dynamic energy simulations, especially in the early stages of design.

A numerical analysis of occupancy profile databases impact on dynamic energy simulation of buildings

Roberto Rugani;Giacomo Salvadori;Fabio Fantozzi;
2024-01-01

Abstract

Dynamic energy analysis accurately studies the buildings’ thermal behaviour but requires consistent data. The study started with an analysis of the most commonly used occupancy profile databases available. Six were selected, and the impact of database choice was assessed by the simulation of a standard building using EnergyPlus, under different climatic conditions of Reykjavik, London, and Madrid. Nine types of building use profiles were simulated. The resulting energy consumption varied depending on the database used, with percentage differences up to 4000%-6000%, with average differences for cities falling within the range of 500% to 1000%, within the same building use category. Such discrepancies are highlighted as an issue to the wider use of building performance simulation in building design, a solution is proposed by harmonizing all assessed databases into a newly defined one, considered a more robust alternative for application in dynamic energy simulations, especially in the early stages of design.
2024
Rugani, Roberto; Picco, Marco; Salvadori, Giacomo; Fantozzi, Fabio; Marengo, Marco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1231087
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