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Passive design optimization of newly-built residential buildings in Shanghai for improving indoor thermal comfort while reducing building energy demand

Gou, Shaoqing; Nik, Vahid M. LU ; Scartezzini, Jean Louis; Zhao, Qun and Li, Zhengrong (2018) In Energy and Buildings 169. p.484-506
Abstract

The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which... (More)

The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay's theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Artificial neural network, Energy demand, Genetic algorithm, Multi-objective optimization, Passive design, Residential buildings, Thermal comfort
in
Energy and Buildings
volume
169
pages
23 pages
publisher
Elsevier
external identifiers
  • scopus:85042431379
ISSN
0378-7788
DOI
10.1016/j.enbuild.2017.09.095
language
English
LU publication?
yes
id
9ddf8972-27b0-4eb6-a172-405ba5352d18
date added to LUP
2018-05-22 13:31:47
date last changed
2019-10-15 06:38:26
@article{9ddf8972-27b0-4eb6-a172-405ba5352d18,
  abstract     = {<p>The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay's theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice.</p>},
  author       = {Gou, Shaoqing and Nik, Vahid M. and Scartezzini, Jean Louis and Zhao, Qun and Li, Zhengrong},
  issn         = {0378-7788},
  keyword      = {Artificial neural network,Energy demand,Genetic algorithm,Multi-objective optimization,Passive design,Residential buildings,Thermal comfort},
  language     = {eng},
  month        = {06},
  pages        = {484--506},
  publisher    = {Elsevier},
  series       = {Energy and Buildings},
  title        = {Passive design optimization of newly-built residential buildings in Shanghai for improving indoor thermal comfort while reducing building energy demand},
  url          = {http://dx.doi.org/10.1016/j.enbuild.2017.09.095},
  volume       = {169},
  year         = {2018},
}