Automating Microclimate Evaluation and Optimization during Urban Design: A Rhino–Grasshopper Workflow

Abstract

Though building-scale energy demand and indoor thermal comfort have been extensively covered by recent studies, the automation of middle- and larger-scale outdoor microclimate evaluation in parametric design is less covered. The relatively slow computation and the need for sophisticated expertise are some of the current issues. This paper proposes a Rhino–Grasshopper custom script to automatically compute spatial indicators for a quick thermal comfort estimation. The Galapagos evolutionary algorithm is used to optimize thermal comfort and select the best combinations of spatial indicators. In a summer case study located in Shantou, China, the proposed workflow was three times faster than a non-automated indicator calculation in ArcGIS, while the optimization method achieved 25% to 33% reduction in land areas under extreme heat stress. This automated process applies to existing states and new urban designs. It is adaptable to customized prediction models under different climatic zones.