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Supervised by Ministry of Industry and Information Technology of The People''s Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

Related citation:Hui Ren,Shoulong Wang.Development and Application of Decision Support Model for the Performance Optimization of Office Buildings Based on Grasshopper[J].Journal of Harbin Institute Of Technology(New Series),2021,28(4):1-15.DOI:10.11916/j.issn.1005-9113.2019055.
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Development and Application of Decision Support Model for the Performance Optimization of Office Buildings Based on Grasshopper
Author NameAffiliation
Hui Ren School of Architecture, Harbin Institute of Technology, Harbin 150001, China 
Shoulong Wang Department of Chemical Engineering and Safety, Binzhou University, Binzhou 256600, Shandong, China 
With the expansion of the office building area, the energy consumption of office buildings is growing. High-performance building design contributes to energy saving and the development of green buildings. However, there is a lack of high-performance building tools and the workflow is often time-consuming. The building performance simulation, multiple objective optimizations, and the decision support model are the new approaches of high-performance building design. This paper proposes a newly developed decision support model, a high-performance building decision model named HPBuildingDSM, which integrates the building performance simulation, building performance multiple objective optimizations, building performance sampling, and parameter sensitivity analysis to design high-performance office buildings. In this research, the HPBuildingDSM was operated to search for the desirable office building design results with low-energy and high-quality daylighting performances. The simulated results had better daylighting performance and lower energy consumption, whose UDI100-2000 was 37.94% and annual energy consumption performance was 76.28 kWh/(m2·a), indicating a better building performance than the optimized results in the previous case study.
Key words:  decision support model  building performance simulation  building performance optimization  building performance simulation  sensitivity analysis  HPBuildingDSM tool
Descriptions in Chinese:



(1. 哈尔滨工业大学 建筑学院,哈尔滨 150001;

2.滨州大学 化学工程与安全系,山东 滨州 256600)



1)本研究通过Python编程法以及HUMAN UI、LADYBUG&HONEYBEE等插件将建筑性能模拟技术、设计参量敏感性分析技术及建筑性能多目标优化技术整合到Grashopper平台中以实现高性能建筑设计决策模型(HPBuildingDSM)的构建;


3)研究应用Python编程技术将Gradient Boosting算法置入Grasshopper电池块中以构建建筑设计参量敏感性分析模块,使得建筑性能模拟结果可直接输入至该模块实现建筑设计参量的敏感性分析以获得各种设计参量对建筑性能的敏感度;