Novel methodology of urban energy simulations integrating open-source platforms

In this research, a novel open-source methodology is presented to perform building cluster and neighborhood simulation by integrating individual archetypes building energy models (BEM). This methodology merges various building Energy Plus models employing a programming language. For the demonstration of generalized methodology, Matlab is used, however, methodology can be implemented by other programming languages such as Python. A given BEM can be employed multiple times to avoid its remodeling in a traditional cluster model setup. The proposed workflow is successfully validated for low, mid, and high-rise mixed-use building clusters with a maximum deviation of ± 2.70% in various annual performance parameters compared to the summation of individual BEM simulations. A sensitivity analysis is also performed to quantify the root mean square deviation (RMSD) between cluster and individual BEM simulations by varying building distance to height ratios along north–south and east–west axes. A significance index on a ten-point scale is proposed to evaluate the importance of cluster simulations over the individual BEM simulations (where the sum of individual BEM results can be used to replace cluster simulations). For instance, the significance index found is to be highest for high-rise building cluster, suggesting thus that building cluster simulations yield more adequate results than individual BEM simulations.