Multi-objective optimization design for windows and shading configuration considering energy consumption and thermal comfort: A case study for office building in different climatic regions of China

能源消耗 计算机科学 窗口(计算) 多目标优化 环境科学 帕累托原理 寒冷的冬天 底纹 模拟 建筑工程 空调 太阳增益 冷负荷 热的 气象学 机械工程 工程类 运营管理 物理 计算机图形学(图像) 机器学习 电气工程 操作系统
作者
Jing Zhao,Yahui Du
出处
期刊:Solar Energy [Elsevier BV]
卷期号:206: 997-1017 被引量:171
标识
DOI:10.1016/j.solener.2020.05.090
摘要

Abstract As a large energy-consuming part of the envelope, windows and shading system play a significant role in building savings. Once established in the primary design stage, it is difficult to make changes later, especially for high-rise buildings with large areas of glass. Moreover, strongly influenced by solar radiation, the configuration of windows and shading system conflicts with each other in terms of energy consumption and indoor comfort, the optimal configuration of windows and shading system under different climatic regions has not been well solved at yet. This paper proposes an easy-operation, useful, and efficient multi-objective optimization method, using a smart optimization algorithm NSGA-II in combination with DesignBuilder energy simulation software, especially beneficial for non-programming designers. In this research, a typical high-rise office building with a large area window has been selected as a case study. Building orientation, the configuration of windows and shading system, including materials for each layer of the double-layer window, installation angle and depth of overhangs have been taken into consideration, aiming to minimize the heating, cooling, lighting energy consumption and discomfort hours, and to find the mutual relationship between each other. A set of Pareto solutions can be obtained after optimization, and the most recommended variable parameters of windows and shading system in four cities representing severe cold climate, cold climate, hot summer and cold winter climate, and hot summer and warm winter climate can be identified, respectively. Besides, Pareto optimal solutions can give designers different scheme choices based on preferences, which are of great significance to provide guidance and suggestion for designers in the early design of buildings.
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