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Multi-objective optimization for energy consumption, daylighting and thermal comfort performance of rural tourism buildings in north China
- Source :
- Building and Environment. 176:106841
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- The rapid development of rural tourism in north China is leading to the extensive growth of rural tourism buildings (RTBs), but the requirements for a comfortable indoor environment will further stimulate high energy consumption (EC) by RTBs. To promote the scientific design of RTBs in north China, three villages in Tianjin are used as research areas. A field survey is carried out, and two-in-one courtyards, triad courtyards and quadrangle courtyards (referred to as Type 1, Type 2 and Type 3, respectively) are found to be the dominant RTB types in the villages. Benchmark models of the three RTB types are extracted and built by using Rhino-Grasshopper, and the performance of the building types in terms of EC, indoor daylighting and thermal comfort is comprehensively considered. The Pareto-based multi-objective optimization tool of Octopus is applied to explore early designs of RTB shape and the window-to-wall ratio (WWR) for the above performance. The Pareto front solution sets and the best optimal solutions obtained by Utopian point method are presented for the three RTB types, and the suggested values for the design variables for the three RTB types are also displayed. A skylight-covered atrium design is found to help improve EC performance, and heating and cooling EC can be regarded as the key points of the RTB energy-saving design. Overall, the method contributes to the scientific design of RTBs, and the findings proposed herein can provide guidance for RTB development in north China and other areas with similar conditions.
- Subjects :
- Architectural engineering
Environmental Engineering
Computer science
Geography, Planning and Development
Rural tourism
0211 other engineering and technologies
Pareto principle
Thermal comfort
02 engineering and technology
Building and Construction
Energy consumption
010501 environmental sciences
01 natural sciences
Multi-objective optimization
Extensive growth
Benchmark (surveying)
021108 energy
Daylighting
0105 earth and related environmental sciences
Civil and Structural Engineering
Subjects
Details
- ISSN :
- 03601323
- Volume :
- 176
- Database :
- OpenAIRE
- Journal :
- Building and Environment
- Accession number :
- edsair.doi...........db421a7b8d1821f54f2b617a10891560