A systematic procedure to study the influence of occupant behavior on building energy consumption

Zhun Yu, Benjamin C.M. Fung, Fariborz Haghighat, Hiroshi Yoshino, Edward Morofsky

Research output: Contribution to journalArticlepeer-review

361 Citations (Scopus)

Abstract

Efforts have been devoted to the identification of the impacts of occupant behavior on building energy consumption. Various factors influence building energy consumption at the same time, leading to the lack of precision when identifying the individual effects of occupant behavior. This paper reports the development of a new methodology for examining the influences of occupant behavior on building energy consumption; the method is based on a basic data mining technique (cluster analysis). To deal with data inconsistencies, min-max normalization is performed as a data preprocessing step before clustering. Grey relational grades, a measure of relevancy between two factors, are used as weighted coefficients of different attributes in cluster analysis. To demonstrate the applicability of the proposed method, the method was applied to a set of residential buildings' measurement data. The results show that the method facilitates the evaluation of building energy-saving potential by improving the behavior of building occupants, and provides multifaceted insights into building energy end-use patterns associated with the occupant behavior. The results obtained could help prioritize efforts at modification of occupant behavior in order to reduce building energy consumption, and help improve modeling of occupant behavior in numerical simulation.

Original languageEnglish
Pages (from-to)1409-1417
Number of pages9
JournalEnergy and Buildings
Volume43
Issue number6
DOIs
Publication statusPublished - 2011 Jun

Keywords

  • Building energy consumption
  • Cluster analysis
  • Data mining
  • Grey relational analysis
  • Occupant behavior

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Mechanical Engineering
  • Electrical and Electronic Engineering

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