Large scale smart meter data assessment for energy benchmarking and occupant behaviour profile development

SUSTAINABLE BUILT ENVIRONMENT D-A-CH CONFERENCE 2019

生态环境科学

Horváth, M.^1 ; Adams, J.N.^2 ; Deme Bélafi, Z.^1 ; Czétány, L.^1 ; Szalay, Z.^3 ; Várnagy, S.^4 ; Reith, A.^4 ; Csoknyai, T.^1

Budapest University of Technology and Economics, Faculty of Mechanical Engineering, Muegyetem rkp. 3-9., Budapest

1111, Hungary^1

University of Tennessee, Knoxville

TN

37996-2250, United States^2

Budapest University of Technology and Economics, Faculty of Civil Engineering, Muegyetem rkp. 3-9., Budapest

1111, Hungary^3

ABUD Engineering Studio, Kisfaludy u. 38., Budapest

1082, Hungary^4

关键词: Building designers;    Consumption habit;    Data analysis techniques;    Energy benchmarking;    Energy calculation;    Energy efficient building;    Occupant behaviour;    Profile development;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/323/1/012121/pdf
DOI  :  10.1088/1755-1315/323/1/012121

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

This paper will present objectives and first results of the research project entitled "Large Scale Smart Meter Data Assessment for Energy Benchmarking and Occupant Behaviour Profile Development of Building Clusters," implemented in the geographical scope of Hungary. The project seeks to utilize a new and unique opportunity for accessing and processing an enormous dataset collected by smart meters. Recently in Hungary, nearly 10 000 buildings have been equipped with smart meters within the "Central Smart Grid Pilot Project". By means of advanced data analysis techniques, consumption trends and motivations of building users are being investigated. The aims are to help building designers and engineers design more energy efficient buildings at lower investment costs by avoiding system oversizing, and to obtain better knowledge about hourly, daily and monthly energy consumption trends. Furthermore, standard net demand values for normative energy calculations can be updated and specified more precisely since consumption habits change with time and depend on the region.