A Framework for the Automatic Integration and Diagnosis of Building Energy Consumption Data

Sensors

Jia-Rui Lin¹  Yun-Yi Zhang¹  Shuang Yuan¹  Zhen-Zhong Hu¹ 

[1] Department of Civil Engineering, Tsinghua University, Beijing 100084, China;

关键词: building energy consumption;    data integration;    energy usage diagnosis;    artificial neural network;   

DOI  :  10.3390/s21041395

来源: DOAJ

【 摘 要 】

Buildings account for a majority of the primary energy consumption of the human society, therefore, analyses of building energy consumption monitoring data are of significance to the discovery of anomalous energy usage patterns, saving of building utility expenditures, and contribution to the greater environmental protection effort. This paper presents a unified framework for the automatic extraction and integration of building energy consumption data from heterogeneous building management systems, along with building static data from building information models to serve analysis applications. This paper also proposes a diagnosis framework based on density-based clustering and artificial neural network regression using the integrated data to identify anomalous energy usages. The framework and the methods have been implemented and validated from data collected from a multitude of large-scale public buildings across China.

【 授权许可】

Unknown