Performance optimization of high-rise residential buildings in cold regions considering energy consumption

With the acceleration of urbanization, high-rise residential buildings has become a significant aspect of urban living. However, while high-rise residential buildings provide much housing, they also bring significant energy consumption. To raise the energy utilization efficiency of high-rise residen...

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Vydáno v:Discover applied sciences Ročník 7; číslo 2; s. 105 - 14
Hlavní autor: Song, Liwei
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 27.01.2025
Springer Nature B.V
Springer
Témata:
Accuracy
Algorithms
Applied and Technical Physics
Architecture
Artificial intelligence
Building design
Buildings
Chemistry/Food Science
Climate change
Cold
Cold regions
Decomposition
Earth Sciences
Enclosure structure
Energy conservation
Energy consumption
Energy efficiency
Energy modeling
Energy utilization
Engineering
Environment
Environmental impact
Flooring
Green buildings
Grey wolf optimization algorithm
Heat transfer
High rise buildings
High-rise residential buildings
Housing
Materials Science
Multi-objective optimization
Multiple objective analysis
Optimization
Optimization algorithms
Residential areas
Residential buildings
Residential development
Residential energy
Simulation
Sustainable development
Thermal comfort
Urbanization
Wide area networks
Grey wolf optimization algorithm
Energy consumption
Multi-objective optimization
Enclosure structure
High-rise residential buildings
ISSN:3004-9261, 2523-3963, 3004-9261, 2523-3971
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Shrnutí:With the acceleration of urbanization, high-rise residential buildings has become a significant aspect of urban living. However, while high-rise residential buildings provide much housing, they also bring significant energy consumption. To raise the energy utilization efficiency of high-rise residential buildings, reduce energy consumption, and achieve sustainable development, this study focuses on high-rise residential buildings in cold regions. Through methods such as parametric modeling, joint simulation of building performance, multi-objective optimization algorithms, and improved grey wolf optimization algorithms, multi-objective optimization experiments are conducted to achieve optimal energy-saving effects. The outcomes denote that the average energy consumption of buildings remains at around 20.5 kW h/m 2 , and the maximum value of the last generation thermal comfort solution set is maintained at 62%, while the minimum value is maintained at 58%. The improved grey wolf optimization algorithm reduces training time, has better predictive ability, and can more accurately characterize changes in energy consumption of high-rise buildings. This study provides practical design methods and strategy references for high-rise residential buildings in the design phase by analyzing data, mining patterns, and summarizing design strategies.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:3004-9261
2523-3963
3004-9261
2523-3971
DOI:10.1007/s42452-025-06526-z