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공동주택단지의 공간 특성이 단지내 전기소비량에 미치는 영향 - 서울시 1,122개 공동주택 단지를 대상으로

A Study on Impact of Apartment Complex’ Spatial Characteristics on Electricity Consumption: Evidence from Seoul, Korea

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초록

공동주택 단지는 개별 주택과는 전혀 다른 전기소비 특성을 보일 수 있다. 표준화된 다수 주택들이 집합된 건물동 을 이룰 뿐 아니라, 공동시설과 공용공간에서도 전기가 소비된다. 기존 연구는 주로 개별 주택의 전기소비 모형을 구축 해왔으며, 단지 단위의 개념은 미기후 시각의 접근 외에는 활발하지 못했다. 본 연구의 목적은 공동주택 단지의 공간 특성과 단지별 전기소비량의 관계를 밝히는데 있다. 건축물장 외에 주민등록장을 연계하여 인구를 고려함으로써 기 존 연구 결과를 확장하였다. 이를 위해 주요 특성요소를 연쇄구조로 구성하는 통계기법인 STIRPAT(Stochastic Impacts by Regression on Population, Affluence, and Technology) 모형을 응용하였다. 결과로, 공동주택 단지 의 전기소비량에 영향을 미치는 변수는 인구 외에 인구밀도, 건폐율, 층수, 호당면적, 소득수준(단위면적당 주택거래가 격), 사용월수, 평균기온이 유의한 것으로 파악되었다. 또 저건폐율-고층 단지가 고건폐율-저층 단지보다 건폐율과 층수 의 증가에 따른 전기소비증가는 덜하고, 인구밀도 증가에 의한 전기소비감소는 적음도 확인하였다. 본 연구는 향후 공공 주택지구 등 공동주택단지 공급시 국지적인 전기소비량 추정에 활용할 수 있을 것으로 기된다.

Abstract

The apartment complex can have big difference for electricity consumption factors from the individual houses. Not only does standardized multi-homes make one building, but electricity is also consumed in public facilities and public spaces. Literatures have constructed electricity consumption models of individual houses, and the concept of apartment complex was seldom studied except the approach of microeconomic view. To expand the literatures results to population factor, the resident registration ledger was used in addition to the building ledger, applying the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology). As a result, variables affecting the electricity consumption of the apartment complex are population, population density, BCR(building coverage ratio), number of floors, floor area per a house unit, the income level (house trade price per unit area), number of months used. In addition, the low BCR-High Rise type complexes showed less electricity consumption due to the increase of BCR and floors than the High BCR-Townhouse type complexes. On the other hand, the latter was more effective in reducing electricity consumption due to the increase in population density than the former. The results of this study are expected to be applicable to the estimation of local electricity consumption in the case of public housing districts.

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