Loading…
Multi-objective optimization of transparent building envelope of rural residences in cold climate zone, China
Due to the lack of effective supervision, guidance, training mechanism, there are serious problems in daylighting, energy efficiency, and thermal comfort of the existing rural residences in cold climate zone, China. In this paper, the multi-objective optimization was introduced to study the shape, s...
Saved in:
Published in: | Case studies in thermal engineering 2022-06, Vol.34, p.102052, Article 102052 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Due to the lack of effective supervision, guidance, training mechanism, there are serious problems in daylighting, energy efficiency, and thermal comfort of the existing rural residences in cold climate zone, China. In this paper, the multi-objective optimization was introduced to study the shape, size and constructure of the transparent building envelope of rural residences in cold climate zone, China. It began with the field investigation and the establishment of the prototypical models. Then the daylighting, heating and cooling load and thermal comfort of the building were simulated, and the multi-objective optimization was performed. The results indicated that the multi-objective optimization of the transparent building envelope could significantly improve daylighting, energy efficiency, and thermal comfort performance of the rural residences. The best values of the northward, the westward and the southward window-to-wall ratio are 0.10, 0.11, 0.12 respectively for the no-sunspace model, and that is 0.13, 0.13, 0.43 respectively for the sunspace model. Compared with the prototypical models, the useful daylight illuminances for the optimal no-sunspace model and sunspace model increased by 6% and 17% respectively, the heating and cooling load decreased by 23% and 17% respectively, and the predicted percentage of dissatisfied decreased by 12% and 9% respectively. |
---|---|
ISSN: | 2214-157X 2214-157X |
DOI: | 10.1016/j.csite.2022.102052 |