A multi-objective optimization design method for gymnasium facade shading ratio integrating energy load and daylight comfort

被引:60
作者
Fan, Zhaoxiang [1 ]
Liu, Mengxuan [1 ]
Tang, Shuoning [1 ,2 ]
机构
[1] Tongji Univ, Coll Architecture & Urban Planning, Shanghai, Peoples R China
[2] Tongji Univ Architectural Design Grp Co Ltd, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Image density atlas (IDA); Facade shading ratio (FSR); Multi-objective optimization (MOO); Genetic algorithm; Daylight comfort; Solar radiation; BUILDING DESIGN; ARTIFICIAL-INTELLIGENCE; MULTIZONE OPTIMIZATION; COMPUTATIONAL DESIGN; VISUAL COMFORT; PERFORMANCE; ALGORITHMS; SIMULATION; DEVICES; IMPACT;
D O I
10.1016/j.buildenv.2021.108527
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The large-scale use of curtain walls in stadiums and other public buildings will cause glare and increase the burden of energy consumption, especially in summer. In the early stage of the design, the optimization of the shading devices directly affects the decision-making of the building facade. This research proposes a multi-objective facade optimization method (MOO) for stadium design, using image density atlas (IDA) to provide decision-making basis for facade shading ratio (FSR) optimization in the preliminary design process of gymna-sium. In contrast to the traditional design method, the optimized design framework proposed in this study will achieve the balance optimization among contradictory goals of daylight comfort and solar radiation at the same time to optimize the daylighting performance while avoiding glare and reducing energy burden. In this study, a gymnasium in Xiong'an, Beijing was selected as the test case. Researchers took the hourly average illuminance, hourly average solar radiation accumulation, and glare index during the opening hours of the gymnasium in summer (August) as the optimization goals. Then, the genetic algorithm SPEA-2 was used to explore the Pareto frontier solution set of FSR. The optimization scheme FSR = 0.37 is formed through comparison and screening. The research results achieved a 38.5% reduction in DGP, a 54% reduction in solar radiation, and control of illuminance loss within the acceptable range. The case study reveals the importance of FSR optimization to the indoor daylight environment of gymnasium in summer, and how parameter changes affect the rules of various metrics.
引用
收藏
页数:15
相关论文
共 59 条
[1]   Multi-objective optimization of passive energy efficiency measures for net-zero energy building in Morocco [J].
Abdou, N. ;
El Mghouchi, Y. ;
Hamdaoui, S. ;
El Asri, N. ;
Mouqallid, M. .
BUILDING AND ENVIRONMENT, 2021, 204
[2]   Building Applications, Opportunities and Challenges of Active Shading Systems: A State-Of-The-Art Review [J].
Al Dakheel, Joud ;
Aoul, Kheira Tabet .
ENERGIES, 2017, 10 (10)
[3]   Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality [J].
Ascione, Fabrizio ;
Bianco, Nicola ;
De Stasio, Claudio ;
Mauro, Gerardo Maria ;
Vanoli, Giuseppe Peter .
APPLIED ENERGY, 2016, 174 :37-68
[4]   Current trends and future challenges in the performance assessment of adaptive facade systems [J].
Attia, Shady ;
Bilir, Senem ;
Safy, Taha ;
Struck, Christian ;
Loonen, Roel ;
Goia, Francesco .
ENERGY AND BUILDINGS, 2018, 179 :165-182
[5]   An efficient metamodel-based method to carry out multi-objective building performance optimizations [J].
Bre, Facundo ;
Roman, Nadia ;
Fachinotti, Victor D. .
ENERGY AND BUILDINGS, 2020, 206
[6]   Optimization of useful daylight illuminance vs. drag force for vertical shading fins/panels [J].
Brzezicki, Marcin ;
Regucki, Pawel .
SCIENCE AND TECHNOLOGY FOR THE BUILT ENVIRONMENT, 2020, 27 (03) :367-376
[7]   NATURWALL© - A solar timber facade system for building refurbishment: optimization process through in field measurements [J].
Callegari, Guido ;
Spinelli, Antonio ;
Bianco, Lorenza ;
Serra, Valentina ;
Fantucci, Stefano .
6TH INTERNATIONAL BUILDING PHYSICS CONFERENCE (IBPC 2015), 2015, 78 :291-296
[8]   Multi-objective optimization of a nearly zero-energy building based on thermal and visual discomfort minimization using a non-dominated sorting genetic algorithm (NSGA-II) [J].
Carlucci, Salvatore ;
Cattarin, Giulio ;
Causone, Francesco ;
Pagliano, Lorenzo .
ENERGY AND BUILDINGS, 2015, 104 :378-394
[9]   Enhancing building energy efficiency by adaptive facade: A computational optimization approach [J].
Dac-Khuong Bui ;
Tuan Ngoc Nguyen ;
Ghazlan, Abdallah ;
Ngoc-Tri Ngo ;
Tuan Duc Ngo .
APPLIED ENERGY, 2020, 265
[10]   Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO) [J].
Delgarm, N. ;
Sajadi, B. ;
Kowsary, F. ;
Delgarm, S. .
APPLIED ENERGY, 2016, 170 :293-303