Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential Building
This paper proposes an optimization process based on a parametric platform for building climate responsive design. Taking residential buildings in six typical American cities as examples, it proposes thermal environment comfort (Discomfort Hour, DH), building energy demand (BED) and building global...
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doaj-db4eee342e0e43c79ac9812c464b191f2020-11-25T03:41:58ZengMDPI AGAlgorithms1999-48932020-09-011323823810.3390/a13090238Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential BuildingZhixing Li0Paolo Vincenzo Genovese1Yafei Zhao2School of Architecture, Tianjin University, Tianjin 300072, ChinaSchool of Architecture, Tianjin University, Tianjin 300072, ChinaSchool of Architecture, Tianjin University, Tianjin 300072, ChinaThis paper proposes an optimization process based on a parametric platform for building climate responsive design. Taking residential buildings in six typical American cities as examples, it proposes thermal environment comfort (Discomfort Hour, DH), building energy demand (BED) and building global cost (GC) as the objective functions for optimization. The design variables concern building orientation, envelope components, and window types, etc. The optimal solution is provided from two different perspectives of the public sector (energy saving optimal) and private households (cost-optimal) respectively. By comparing the optimization results with the performance indicators of the reference buildings in various cities, the outcome can give the precious indications to rebuild the U.S. residential buildings with a view to energy-efficiency and cost optimality depending on the location.https://www.mdpi.com/1999-4893/13/9/238building climate responsive designmulti-objective optimizationenergy saving optimalcost-optimal |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhixing Li Paolo Vincenzo Genovese Yafei Zhao |
spellingShingle |
Zhixing Li Paolo Vincenzo Genovese Yafei Zhao Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential Building Algorithms building climate responsive design multi-objective optimization energy saving optimal cost-optimal |
author_facet |
Zhixing Li Paolo Vincenzo Genovese Yafei Zhao |
author_sort |
Zhixing Li |
title |
Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential Building |
title_short |
Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential Building |
title_full |
Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential Building |
title_fullStr |
Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential Building |
title_full_unstemmed |
Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential Building |
title_sort |
study on multi-objective optimization-based climate responsive design of residential building |
publisher |
MDPI AG |
series |
Algorithms |
issn |
1999-4893 |
publishDate |
2020-09-01 |
description |
This paper proposes an optimization process based on a parametric platform for building climate responsive design. Taking residential buildings in six typical American cities as examples, it proposes thermal environment comfort (Discomfort Hour, DH), building energy demand (BED) and building global cost (GC) as the objective functions for optimization. The design variables concern building orientation, envelope components, and window types, etc. The optimal solution is provided from two different perspectives of the public sector (energy saving optimal) and private households (cost-optimal) respectively. By comparing the optimization results with the performance indicators of the reference buildings in various cities, the outcome can give the precious indications to rebuild the U.S. residential buildings with a view to energy-efficiency and cost optimality depending on the location. |
topic |
building climate responsive design multi-objective optimization energy saving optimal cost-optimal |
url |
https://www.mdpi.com/1999-4893/13/9/238 |
work_keys_str_mv |
AT zhixingli studyonmultiobjectiveoptimizationbasedclimateresponsivedesignofresidentialbuilding AT paolovincenzogenovese studyonmultiobjectiveoptimizationbasedclimateresponsivedesignofresidentialbuilding AT yafeizhao studyonmultiobjectiveoptimizationbasedclimateresponsivedesignofresidentialbuilding |
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1724527112643149824 |