Investigating Primary Factors Affecting Electricity Consumption in Non-Residential Buildings Using a Data-Driven Approach

구분: 게재

국내/국외, SCI(E)/일반 학술지 구분:? 국제학술지(SCIE)

학술회의/학술지명: ENERGIES

논문제목: Investigating Primary Factors Affecting Electricity Consumption in Non-Residential Buildings Using a Data-Driven Approach

게제일 : 2019.10.24

주저자명 : 조수연

게재링크 : https://doi.org/10.3390/en12214046

논문 파일 다운로드

energies-12-04046

Abstract

Although the latest energy-effcient buildings use a large number of sensors and measuring instruments to predict consumption more accurately, it is generally not possible to identify which data are the most valuable or key for analysis among the tens of thousands of data points. This study selected the electric energy as a subset of total building energy consumption because it accounts for more than 65% of the total building energy consumption, and identified the variables that contribute to electric energy use. However, this study aimed to confirm data from a building using clustering in machine learning, instead of a calculation method from engineering simulation, to examine the variables that were identified and determine whether these variables had a strong correlation with energy consumption. Three dierent methods confirmed that the major variables related to electric energy consumption were significant. This research has significance because it was able to identify the factors in electric energy, accounting for more than half of the total building energy consumption, that had a major eect on energy consumption and revealed that these key variables alone, not the default values of many dierent items in simulation analysis, can ensure the reliable prediction of energy consumption.