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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Main Authors: Zhixing Li, Paolo Vincenzo Genovese, Yafei Zhao
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Algorithms
Subjects:
Online Access:https://www.mdpi.com/1999-4893/13/9/238
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author Zhixing Li
Paolo Vincenzo Genovese
Yafei Zhao
author_facet Zhixing Li
Paolo Vincenzo Genovese
Yafei Zhao
author_sort Zhixing Li
collection DOAJ
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.
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spelling doaj.art-db4eee342e0e43c79ac9812c464b191f2023-11-20T14:31:20ZengMDPI AGAlgorithms1999-48932020-09-0113923810.3390/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
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
title 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_short 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
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