Research on Energy Consumption Analysis and Optimization of Dormitory Buildings Based on Data Mining

Jiayuan Wang, Zhuoling Zhong, Cheng Fan (), Bo Yu and Yong Sun
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Jiayuan Wang: Shenzhen University
Zhuoling Zhong: Shenzhen University
Cheng Fan: Shenzhen University
Bo Yu: Shenzhen University
Yong Sun: Shenzhen University

A chapter in Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate, 2021, pp 1695-1710 from Springer

Abstract: Abstract Data mining (DM) is gradually applied to building energy domain with its high efficiency and intelligence to solve the problems that traditional statistical methods can’t effectively identify hidden knowledge in massive data. This study aims to construct a DM framework to analyze and optimize the dormitory building energy consumption. The daily energy consumption of each dormitory is recorded by smart meters in real time. Combining with the student basic information, the exploration analysis, cluster analysis, and decision tree are used to explore the students’ energy consumption characteristics. Finally, a dynamic optimization model is built to optimize the building energy. The results show that it can achieve energy saving potential of 15.8% through change the allocation of students, which is conducive to building energy efficiency.

Keywords: Data mining; Dormitory building; Smart meter; Energy consumption characteristics; Dynamic (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-15-8892-1_119

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DOI: 10.1007/978-981-15-8892-1_119

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