Research on inefficiency analysis method of building energy utilizing time series data

Sustainable Built Environment Conference 2019 Tokyo Built Environment in an era of climate change: how can cities and buildings adapt?

生态环境科学

Bumpei, Magori^1 ; Yashiro, Tomonari^1

Institute Industrial Science, University of Tokyo, Japan^1

关键词: Analytical method;    Building automation systems;    Building energy consumption;    Building energy efficiency;    Building management;    Building management system;    Internet of Things (IOT);    System improvements;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/294/1/012052/pdf
DOI  :  10.1088/1755-1315/294/1/012052

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Purpose; Our research purpose is to utilize time series data related to building energy and perform an inefficiency analysis of building energy efficiency. Development; We developed a cloud building energy and environment monitoring system (cloud Building Management System (BEMS)) and an optimized control system (an artificial intelligence [AI] control system). Methodology; First, we designed an inefficiency analysis model and the analysis steps. Next, this model was tested in several actual buildings, and the method was confirmed to be adaptable. Finally, through iterative adaptations based on the results, we significantly improved our method. Findings; (1) The developed cloud BEMS and AI control system were confirmed to be useful for a) improvement of building management, b) improvement of equipment and system, and c) renovation. (2) Our analytical method and its steps can quantify inefficiency. (3) When using this methodology, we can quantitatively predict before implementation the effect of a) building improvement, b) equipment and system improvement, and c) renovation. Originality/value; Cloud BEMS collects time series data related to building energy consumption from sensors and building automation systems and accumulates data in a cloud server. The AI control system and analytical method finds energy inefficiencies and improves the operation of the building. Moreover, this improvement in operation is unmanned and carried out automatically. Keywords; Sustainable, Internet of things (IoT), machine learning, artificial intelligence (AI), energy management system (EMS), energy conservation, environment efficiency, optimized control, CO2 reduction. Paper type; Academic paper.