Influence of Building Envelope Modeling Parameters on Energy Simulation Results

This study investigates the influence of input values for building energy model parameters on simulation results, with the aim of improving the reliability and sustainability of energy performance assessments. Dynamic simulations were conducted in TRNSYS for three theoretical multi-residential buildings, varying parameters such as referent model dimensions, infiltration rates, envelope thermophysical properties, and interior thermal capacitance. The case study, based in Slovenia, demonstrates that glazing-related parameters, particularly the solar heat gain coefficient (g-value), exert the most significant influence—reducing the g-value from 0.62 to 0.22 decreased simulated heating (qH,nd) and cooling (qC,nd) demands by 25% and 95%, respectively. In contrast, referent dimensions for modeled floor area proved least influential. For Building III (BSF = 0.36), dimensional variations altered results by less than ±1%, whereas, for Building I (BSF = 0.62), variations reached up to ±20%. In general, lower shape factors yield more robust energy models that are less sensitive to input deviations. These findings are critical for promoting resource-efficient simulation practices and ensuring that energy modeling contributes effectively to sustainable building design. Understanding which inputs warrant detailed attention supports more targeted and meaningful simulation workflows, enabling more accurate and impactful strategies for building energy efficiency and long-term environmental performance.

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Publication Details

Journal
Sustainability
Published
2025-06-07
DOI
https://doi.org/10.3390/su17125276
Citations
2
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
2.01

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article

Influence of Building Envelope Modeling Parameters on Energy Simulation Results

Mirko Komatina, Simon Muhič, Dimitrije Manić, Ante Čikić
2 citations
Sustainability
Building Energy and Comfort Optimization
2.01
article

Influence of Building Envelope Modeling Parameters on Energy Simulation Results

Mirko Komatina, Simon Muhič, Dimitrije Manić, Ante Čikić
article en
2 citations

Abstract

This study investigates the influence of input values for building energy model parameters on simulation results, with the aim of improving the reliability and sustainability of energy performance assessments. Dynamic simulations were conducted in TRNSYS for three theoretical multi-residential buildings, varying parameters such as referent model dimensions, infiltration rates, envelope thermophysical properties, and interior thermal capacitance. The case study, based in Slovenia, demonstrates that glazing-related parameters, particularly the solar heat gain coefficient (g-value), exert the most significant influence—reducing the g-value from 0.62 to 0.22 decreased simulated heating (qH,nd) and cooling (qC,nd) demands by 25% and 95%, respectively. In contrast, referent dimensions for modeled floor area proved least influential. For Building III (BSF = 0.36), dimensional variations altered results by less than ±1%, whereas, for Building I (BSF = 0.62), variations reached up to ±20%. In general, lower shape factors yield more robust energy models that are less sensitive to input deviations. These findings are critical for promoting resource-efficient simulation practices and ensuring that energy modeling contributes effectively to sustainable building design. Understanding which inputs warrant detailed attention supports more targeted and meaningful simulation workflows, enabling more accurate and impactful strategies for building energy efficiency and long-term environmental performance.

SustainabilityVol. 17(12)
University of Belgrade (RS), Higher Education Centre Novo Mesto (SI), University North (HR)
Science Fund of the Republic of Serbia
Openalex Percentile: Top 14%
Building Energy and Comfort Optimization
2.01
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Influence of Building Envelope Modeling Parameters on Energy Simulation Results — Mirko Komatina, Simon Muhič, et al. · Sustainability (2025) | TGRS Research Map | TGRS