智能城市2026，Vol.12Issue(2)：1-8,8.DOI:10.19301/j.cnki.zncs.2026.02.001
基于Rhino+Grasshopper的被动式建筑节能因子多目标优化研究
Research on multi-objective optimization of passive building energy-saving factors based on Rhino+Grasshopper
摘要
Abstract
The article proposes a systematic framework that integrates orthogonal experimental design and multi-objective genetic algorithm.Taking a 6-story residential building in Nanjing as a case study,the Rhino+Grasshopper platform and Ladybug,Honeybee,Octopus tools are integrated to carry out multi-parameter coupling optimization of window-to-wall ratio(WWR),shading devices,glass types,and insulation materials.Results indicate that the south-facing window-to-wall ratio is the most significant factor influencing energy consumption,while glass type is the key parameter governing daylighting performance.A shutter width between 0.1 and 0.2 meters achieves an optimal balance between daylighting and energy consumption.At this setting,the space's daylight autonomy rate sDA300/50%increases substantially by 102.8%,with energy consumption rising by only 7.7%.The combination of polyurethane insulation and double Low-E insulating glass is widely distributed within the Pareto solution set,forming the foundational configuration for achieving high performance.In addition,the L18(36)orthogonal table combined with the second-generation non-dominated sorting genetic algorithm(NSGA-Ⅱ)generates a Pareto optimal solution set,verifying the reliability of the lighting energy balance solution.关键词
能耗性能/建筑采光/多目标优化/NSGA-ⅡKey words
energy performance/building daylighting/multi-objective optimization/NSGA-Ⅱ分类
建筑与水利引用本文复制引用
秦世艳,蒋博雅..基于Rhino+Grasshopper的被动式建筑节能因子多目标优化研究[J].智能城市,2026,12(2):1-8,8.基金项目
教育部人文社会科学研究项目(25YJCZH105) （25YJCZH105）
江苏省社会科学基金项目研究成果(24ZHC012) （24ZHC012）
中国建设教育协会科研资助项目(2025022) （2025022）
