Effect of Floor Shape Optimization on Energy Consumption for U-Shaped Office Buildings in the Hot-Summer and Cold-Winter Area of China
Xiaoyu Ying, Wenzhe Li
Abstract
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Xiaoyu Ying, Wenzhe Li
Abstract
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This paper explored the effects of the side proportion of building floor shape on building energy consumption. It is based on the analysis of regression models that were developed in the present study. The simplified building models can be used to conduct a parametric study to investigate the effect of building plane shape parameters on total heating and cooling load. DesignBuilder was used to build and simulate individual building configuration. Energy consumption simulations for forty-eight U-shaped buildings with different plane layouts were performed to create a comprehensive dataset covering general ranges of side proportions of U-shaped buildings and building orientations. Statistical analysis was performed using MATLAB to develop a set of regression equations predicting energy consumption and optimizing floor shapes. Furthermore, perimeter-area ratio (PAR), width ratio, and depth ratio were considered as three factors to characterize the quantitative relationship between floor shape and energy consumption. It is envisioned that the binary quadratic polynomial regression models, visualized as a smooth surface in space and mapped to a vortex image on the plane, can be used to estimate the energy consumption in the early stages of the design when different building schemes and design concepts are being considered.
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This paper explored the effects of the side proportion of building floor shape on building energy consumption. It is based on the analysis of regression models that were developed in the present study. The simplified building models can be used to conduct a parametric study to investigate the effect of building plane shape parameters on total heating and cooling load. DesignBuilder was used to build and simulate individual building configuration. Energy consumption simulations for forty-eight U-shaped buildings with different plane layouts were performed to create a comprehensive dataset covering general ranges of side proportions of U-shaped buildings and building orientations. Statistical analysis was performed using MATLAB to develop a set of regression equations predicting energy consumption and optimizing floor shapes. Furthermore, perimeter-area ratio (PAR), width ratio, and depth ratio were considered as three factors to characterize the quantitative relationship between floor shape and energy consumption. It is envisioned that the binary quadratic polynomial regression models, visualized as a smooth surface in space and mapped to a vortex image on the plane, can be used to estimate the energy consumption in the early stages of the design when different building schemes and design concepts are being considered.
Key concepts: Energy consumption, Parametric statistics, Glazing, Plane (geometry), Polynomial regression, Regression analysis, Structural engineering, Geometry