Abstract: Building energy models on the basis of the original building information modeling (BIM) model were established to research the passive energy-saving strategies. This model adopted the gbXML data standard for data sharing, which imported a parametric building performance simulation model on the Grasshopper platform. In addition, the solar radiation analysis was performed on the outer surface of the target building to determine the variables index of the passive energy-saving technology, such as the angle and depth of the west overhangs, the window-to-wall ratio on the south and west sides, and the thickness of the insulation board. This platform established the objective function based on the spatial daylight autonomy (sDA300/50%), annual cooling and heating energy consumption, which employed OpenStudio for building energy analysis and Daysim for annual dynamic natural lighting analysis. Finally, using the NSGA-II algorithm for multi-objective optimization, the Pareto solution set was obtained. The result shows that on cold zone B, the fixed shading cannot balance cooling and heating energy 

Key words: building information modeling, passive building, energy-saving factor, building performance analysis, multi-objective optimization