Applications of artificial intelligence for energy efficiency throughout the building lifecycle: An overview

被引:13
|
作者
Yussuf, Raheemat O. [1 ]
Asfour, Omar S. [1 ,2 ,3 ]
机构
[1] King Fahd Univ Petr & Minerals, Architecture & City Design Dept, Dhahran, Saudi Arabia
[2] King Fahd Univ Petr & Minerals, Interdisciplinary Res Ctr Construct & Bldg Mat, Dhahran, Saudi Arabia
[3] King Fahd Univ Petr & Minerals, POB 2483, Dhahran 31261, Saudi Arabia
关键词
Artificial Intelligence; Buildings; Building Lifecycle; Energy Efficiency; MODEL-PREDICTIVE CONTROL; MACHINE LEARNING-MODELS; DESIGN; PERFORMANCE; SYSTEM; OPTIMIZATION; FRAMEWORK; SELECTION;
D O I
10.1016/j.enbuild.2024.113903
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The use of Artificial Intelligence (AI) technologies in buildings can assist in reducing energy consumption through enhanced control, automation, and reliability. This review aims to explore the use of AI to enhance energy efficiency throughout various stages of the building lifecycle, including building design, construction, operation and control, maintenance, and retrofit. The review encompasses multiple studies in the field published between 2018 and 2023. These studies were identified through keyword searches that best represent the topic, using various research databases. In addition to summarizing the technologies and approaches related to AI and energy efficiency, this review discusses future opportunities for the application of AI in energy efficiency within these lifecycle stages. The review highlights that AI-based solutions are currently employed in building design generation and optimization, decision-making, predictive and adaptive control, fault detection and diagnosis, as well as energy benchmarking. These applications effectively facilitate energy efficiency in buildings to meet today's energy needs. However, further research is needed to explore the use of AI in the construction phase to support the development of energy-efficient construction techniques and systems, in addition to scheduling and predictive decision-making.
引用
收藏
页数:14
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