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• W3082204006 endingPage "11929" @default.
• W3082204006 startingPage "11908" @default.
• W3082204006 abstract "In this study, artificial intelligence (AI) control tools were developed to construct an AI implementation framework for energy saving for buildings. Although numerous AI studies related to energy conservation have been conducted, most of them have reported computing algorithms and control effects for single objects. This is the first study to use a framework to integrate five-category AI control tools to execute three-level building energy conservation; the three levels consist of equipment-level control, facility-level control, and whole building energy saving. Energy-saving effects were tested in a real building. The complex three-floor building primarily with a total area of 9072 m2 serves as an office space and a semiconductor production line. Seventy percent energy consumption comes from air conditioning system and motor power. Twenty percent is lighting system and the other 10% is plug power and office automation equipment. Before implementation, the yearly energy cost reached US$1004339. In 2018, an AI implementation framework was introduced to systematically deploy AI at the site. A total of 47.5%, 37%, and 36.9% of energy was saved at equipment, facility, and whole building levels; up to US$385203 was saved. These energy savings proved the feasibility of the implementation framework. Furthermore, unmet demands of AI studies were met, and an approach to fill the research gap is discussed." @default.
• W3082204006 created "2020-09-08" @default.
• W3082204006 creator A5033173613 @default.
• W3082204006 creator A5048715732 @default.
• W3082204006 creator A5050269993 @default.
• W3082204006 creator A5087698566 @default.
• W3082204006 date "2020-09-01" @default.
• W3082204006 modified "2023-10-14" @default.
• W3082204006 title "Artificial intelligence implementation framework development for building energy saving" @default.
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