Optimized Design of Skylight Arrangement to Enhance the Uniformity of Indoor Sunlight Illumination

Author:

Jia Bowen1ORCID,Li Wenjie1,Chen Guanyu1,Sun Wenbin1,Wang Bowen2ORCID,Xu Ning1

Affiliation:

1. School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China

2. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Abstract

The use of skylights in buildings introduces natural light into the interior space, thereby reducing the reliance on artificial lighting and aligning with the principles of low carbon and environmental sustainability. To ensure optimal indoor lighting quality, it is essential to optimize the arrangement of skylights to strike a balance between high average illumination and uniformity of illumination. Recent initiatives by the Chinese government have emphasized the construction and renovation of numerous gymnasiums. In this research, a novel approach based on optimized algorithms was employed to design skylights and improve the uniformity of indoor illuminance. Simulation results demonstrated that the skylight arrangements derived from the optimization algorithms exhibited significantly higher levels of illumination uniformity, while maintaining comparable average illumination and skylight areas, when compared to conventional designs. Additionally, the study employed genetic algorithms to optimize the skylight arrangement for a specific gymnasium, resulting in a remarkable 32% increase in illumination uniformity. The study also accounted for obstacles and seating in the skylight design, and the genetic algorithm generated desirable skylight arrangements with respective increases of 32% and 21% in illumination uniformity for scenarios involving obstacles and seating. Overall, this study underscores the potential of optimized algorithms in the design of skylights for green buildings, offering valuable insights for future research endeavors in this field.

Funder

National Key R&D Program of China

Hubei Provincial Natural Science Foundation of China

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3