Green building technologies and design-correlated choices may significantly contribute to supporting the transition toward net energy flows in the built environment. Nevertheless, large discrepancies are underlined between standard simulated and monitored building behaviours requiring approaches able to simply correlate real building behaviours and simulated ones to further support coherent certification and/or optimization. The paper focusses on the application of a semi-automatic methodology to compare and evaluate thermal behaviours of buildings considering monitored and simulated data. The approach is based on a new Python tool developed by the authors, able to manage EnergyPlus inputs and perform multi-source KPIs calculations. The mentioned tool is used here to support semi-automatic model verifications of real weather data by optimizing model parameters to fit monitored behaviours. The approach is applied in this chapter to two demo buildings, a municipality school and a residential unit, located in the Turin metropolitan area of Piedmont, in Northwest Italy.
Simulated Versus Monitored Building Behaviours: Sample Demo Applications of a Perfomance Gap Detection Tool in a Northern Italian Climate / Chiesa, Giacomo; Fasano, Francesca; Grasso, Paolo (INNOVATIVE RENEWABLE ENERGY). - In: Towards Net Zero Carbon Emissions in the Building Industry / Sayigh A.. - STAMPA. - Cham : Springer, 2023. - ISBN 978-3-031-15217-7. - pp. 109-133 [10.1007/978-3-031-15218-4_6]
Simulated Versus Monitored Building Behaviours: Sample Demo Applications of a Perfomance Gap Detection Tool in a Northern Italian Climate
Chiesa, Giacomo;Fasano, Francesca;Grasso, Paolo
2023
Abstract
Green building technologies and design-correlated choices may significantly contribute to supporting the transition toward net energy flows in the built environment. Nevertheless, large discrepancies are underlined between standard simulated and monitored building behaviours requiring approaches able to simply correlate real building behaviours and simulated ones to further support coherent certification and/or optimization. The paper focusses on the application of a semi-automatic methodology to compare and evaluate thermal behaviours of buildings considering monitored and simulated data. The approach is based on a new Python tool developed by the authors, able to manage EnergyPlus inputs and perform multi-source KPIs calculations. The mentioned tool is used here to support semi-automatic model verifications of real weather data by optimizing model parameters to fit monitored behaviours. The approach is applied in this chapter to two demo buildings, a municipality school and a residential unit, located in the Turin metropolitan area of Piedmont, in Northwest Italy.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2973082