Detecting Anomalous Energy Consumption from Profiles

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

Abe, Hiroto^1 ; Bogaki, Kazuaki^1 ; Rijal, H.B.^1 ; Sugiyama, Mahito^2

Tokyo City University, Japan^1

National Institute of Informatics^2

关键词: Condominium housing;    Critical issues;    Electric energy consumption;    Energy consumption analysis;    Human wellbeing;    Large amounts;    Prediction model;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/294/1/012072/pdf
DOI  :  10.1088/1755-1315/294/1/012072

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Controlling and reducing electric energy consumption is a critical issue across all over the countries for human wellbeing. However, approaches to achieve energy consumption reduction of individual occupants have not been established yet as both problems of collecting a large amount data of energy consumption and constructing prediction models are challenging. Here we show a case-study of energy consumption analysis, in which households with anomalous energy consumption can be completely detected using a questionnaire about their profiles without seeing actual energy consumption. Our approach is based on simple data mining techniques of outlier detection and decision trees, hence it can be easily implemented in the condominium housing market.