4.6 Article

Evaluation of the Impact of Input-Data Resolution on Building-Energy Simulation Accuracy and Computational Load-A Case Study of a Low-Rise Office Building

Journal

BUILDINGS
Volume 13, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/buildings13040861

Keywords

building-energy modelling (BEM); EnergyPlus; data resolution; optimization; sensitivity analysis

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Building-energy consumption is the primary objective of urban energy consumption, aiming to optimize building operation and management techniques for sustainable building and built environments. However, there is a lack of accurate quantitative study on the relationship between accuracy of building-energy modelling (BEM) and computational load. This study quantitatively explores the effects of different resolution accuracies of building-model input data on energy simulation results and computational load.
Building-energy consumption is the primary aim of urban energy consumption, which can aid in optimization of building operation and management techniques, creating sustainable building and built environments. However, modellers' understanding of the relationship between building-energy modelling (BEM) accuracy and computational load is still qualitative and deprived of accurate quantitative study. Based on a bottom-up engineering methodology, this study aims to quantitatively explore the effects of building-model input data with different resolution accuracies on energy simulation results, including evaluation of computational load. According to the actual parameters of the case-study building, 108 models with varying input resolution levels were developed to estimate hourly energy usage and annual mean ambient temperature. The results demonstrated that with input parameters at low resolution levels, geometric parameters such as exterior windows, interior windows, and shading exhibited significantly lower computational loads, resulting in reduced errors in the final simulation performance, whereas the occupancy schedule, thermal zoning, and HVAC configuration parameters exhibited significant declines in simulation performance and accuracy. This study presents a methodology applicable to the majority of low-rise, rectangular office structures. Future work would concentrate on carrying out comparison tests for different building forms and types while gradually improving the automation of the process to enable use of the appropriate accuracy level in assessing the crucial issue of energy-modelling input.

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