维普中文期刊产品整合服务

A data analytics-based tool for the detection and diagnosis of anomalous daily energy patterns in buildings

查看全文 作　　者：Marco Savino [1,2]Piscitelli;Silvio [1]Brandi;Alfonso [1]Capozzoli;Fu [2]Xiao 高影响力作者 机构地区：[1]Department of Energy“Galileo Ferraris”,TEBE research group,Politecnico di Torino,Turin,Italy;[2]Department of Building Services Engineering,The Hong Kong Polytechnic University,Hong Kong,China高影响力机构 出　　处：《Building Simulation》索引2021年第14卷第1期,共17页高影响力期刊 基　　金：The authors also gratefully acknowledge the support of this research by the Research Grant Council of the Hong Kong SAR(152133/19E). 摘　　要：In this paper,a tool for the detection and diagnosis of anomalous electrical daily energy patterns relative to a transformer substation of a university campus was developed and tested.Through an innovative pattern recognition analysis consisting in a multi-step clustering process,six clusters of anomalous daily load profiles were identified and isolated in two-year historical data of total electrical energy consumption.The infrequent electrical load profiles were found to be strongly affected,in terms of both shape and magnitude,by the energy consumption behaviour related to the heating/cooling mechanical room.Then,a fault-free predictive model,which uses artificial neural network(ANN)in combination with a Regression Tree,was developed to detect anomalous trends of the electrical energy consumption.The model was able to detect the 93.7%of the anomalous profiles and only the 5%of fault-free days were wrongly predicted as anomalous.Eventually,a diagnosis phase was conceived and validated with a testing data set.A number of daily abnormal load profiles were detected and compared with the centroids of the anomalous clusters identified in the pattern-recognition stage.The work led to the development of a flexible intelligent tool useful for operating a continuous commissioning of the campus facilities. 关 键 词：anomaly detection data analytics energy management pattern recognition prediction models
相关文献

参考文献(40)

引证文献(4)

网站首页 | 关于我们 | 联系我们 | 产品服务 | 客服中心 | 广告服务 | 版权声明 | 网站联盟 | 友情链接 | 售卡网点

版权所有© 渝B2-20050021-1　渝公网安备 50019002500403号　违法和不良信息举报中心

互联网出版许可证 新出网证(渝)字10号 全国400电话 - 免长途话费