The present study describes the development of a multi-linear regression model to predict the effect of building shape on total energy consumption in two different climate regions (i.e. cold-dry and warm-marine). Seven building shapes including H-shape, T-shape, rectangle, etc. were considered in this study. The simplified model can be used to conduct a parametric study in order to investigate the effect of building parameters on total heating and cooling load. Building simulation software programs, including eQUEST and DOE-2 were used to build and simulate individual building configuration that were generated using Monte Carlo simulation techniques. Ten thousand simulations for seven building shapes were performed to create a comprehensive dataset covering the full ranges of design parameters. Statistical analysis was performed using R statistical analysis program to develop a set of linear regression equations predicting energy consumption of each design scenario. In addition, the influence of several design parameters on building energy consumption was further investigated using the sensitivity analysis procedure. The difference between regression-predicted and DOE-2 simulated annual building energy consumption were largely within 5%. It is envisioned that the developed regression models can be used to estimate the total energy consumption in the early stages of the design when different building schemes and design concepts are being considered.
Energy conservation, Architectural design, Buildings, Climate models, Computer software, Design, Energy utilization, Forecasting, Intelligent systems, Linear regression, Monte Carlo methods, Office buildings, Regression analysis, Sensitivity analysis, Statistical methods, Sustainable development, Annual energy consumption, Building energy consumption, Building energy performance, DOE-2 simulation, eQUEST simulation, Linear regression equation, Monte carlo simulation technique, Regression equation, Building energy performance, DOE-2 simulation, eQUEST simulation, Monte Carlo simulation, Regression equations
Construction Engineering and Management | Manufacturing
Mohammad Mottahedi, Atefeh Mohammadpour, Shideh Shams Amiri, David Riley, and Somayeh Asadi (2015).
Multi-linear Regression Models to Predict the Annual Energy Consumption of an Office Building with Different Shapes. Procedia Engineering.118, 622-629. Elsevier Ltd.