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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 (författare)
Tongji University
Nik, Vahid, 1979 (författare)
Chalmers University of Technology,Lund University,Lunds universitet,Avdelningen för Byggnadsfysik,Institutionen för bygg- och miljöteknologi,Institutioner vid LTH,Lunds Tekniska Högskola,Division of Building Physics,Department of Building and Environmental Technology,Departments at LTH,Faculty of Engineering, LTH
Scartezzini, J. L. (författare)
Ecole Polytechnique Federale de Lausanne (EPFL),Swiss Federal Institute of Technology in Lausanne (EPFL),Swiss Federal Institute of Technology
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Zhao, Qun (författare)
Tongji University
Li, Zhengrong (författare)
Tongji University
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 (creator_code:org_t)
Elsevier BV, 2018
2018
Engelska.
Ingår i: Energy and Buildings. - : Elsevier BV. - 0378-7788. ; 169, s. 484-506
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • 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.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Byggproduktion (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Construction Management (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Energisystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Energy Systems (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Husbyggnad (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Building Technologies (hsv//eng)

Nyckelord

Multi-objective optimization
Passive design
Artificial neural network
Genetic algorithm
Thermal comfort
Residential buildings
Energy demand
Artificial neural network
Energy demand
Genetic algorithm
Multi-objective optimization
Passive design
Residential buildings
Thermal comfort

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