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Exploration of Residential Electricity Consumption in Different Neighborhood Contexts in Seoul under Progressive Electricity Tariff System
전기요금 누진제도 개편이 주택용 전기사용량에 미치는 영향: 도시요소의 차이를 중심으로

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Authors
김경도
Advisor
Steven Jige Quan
Issue Date
2020
Publisher
서울대학교 대학원
Keywords
Progressive tariff systemEUI (Energy Use Intensity)Built environmental factorsSocial economic factorsInteraction termModerate effect
Description
학위논문 (석사) -- 서울대학교 대학원 : 환경대학원 환경계획학과, 2020. 8. Steven Jige Quan.
Abstract
In December 2016, the government and KEPCO (Korea Electric Power Corporation) modified the progressive tariff system for the purpose of reducing electricity bills. The progressive tariff system was changed into a three-block system, with the highest block paying triple the amount of the lowest block. The research related to the progressive tariff system so far can be divided into before and after the modification of the residential progressive tariff system. The studies prior to the modification were scenario analysis. After the modification of the residential electricity tariff system, the studies used household statistics survey data from the National Statistical Office, which is indirect data. There were a few national studies have been conducted on the modified tariff system using real consumption data. The research considered only the characteristics of households, such as the family size, number of children, presence of disabled people, and status of basic livelihood security recipient when analyzing the impact of the modified tariff system on electricity consumption.

However, the household electricity consumption was influenced by various factors: urban geometry, building design, systems efficiency, and occupant behavior. Therefore, a better understanding of the building electricity consumption and its change due to new progressive tariff system in urban contexts should control both the social economic variables of occupants and the built environmental variables such as the geometry and building density. Therefore, the aim of this study is to analyze; 1)How the social economic and built environmental characteristics of the neighborhood have had an effect on electricity consumption, 2) How the new progressive tariff system had an effect on electricity consumption, 3) How changes in electricity consumption in neighborhood with different social economic condition after the implementation of new progressive tariff system.

In this study, two different datasets were used for analysis of effect of new electricity tariff system, socio-economic factors and built environmental factors on EUI (Energy Use Intensity) due to the limitations of data access. Electricity consumption of multi-family house complex units was from the Building Energy System. This was electricity consumption by parcel, and one parcel had an electricity consumption data. That is, the electricity consumption data of the multi-family house complex unit was the electricity consumption of the entire parcel or complex, and the electricity consumption by household in the parcel or complex is aggregated. On the other hand, household electricity consumption data was from the Household Energy Standing Survey. Although this is individual data for each household, there is no location information, so it is not possible to take into account the influence of the built environment on electricity consumption, such as green space. Therefore, using the two data 'Multi-family house complex' and 'Household', the effect of neighborhood contexts on residential electricity consumption was analyzed and the changes in residential electricity consumption depends on social economic condition after the implementation of new progressive tariff system also analyzed .

The dependent variable in complex unit data was EUI (Energy Use Intensity=Total electricity consumption/Total floor area), and in household unit data was EUI (Energy Use Intensity=Household electricity consumption/house area). The independent variable was HDD+CDD (Heating and Cooling Degree Day), 4 variables in built environmental factor and 3 variables in social economic factor. In complex unit data: Building age, FAR (Floor Area Ratio), BCR (Building Coverage Ratio), Green area within 500m radius, Price per area, Occupancy, and Ratio of over 65-year-old. In household unit data: Building age, Orientation, Number of bedroom, Number of living room, Income, Occupancy, and Ration over 65-year-old.

To answering the first sub research question panel analysis used. In the result of panel analysis using both complex and household unit data, the coefficients of social economic factors were different. In both results, Occupancy and ratio of elderly people showed positive correlation with EUI, but price per area and income showed different correlation. ITS-Panel analysis, which integrates Interrupted Time Series into Panel analysis, was used to analyze changes in electricity consumption after the implementation of the new tariff system. In the result of ITS-Panel analysis using both complex and household unit data, the coefficient of Trend was different. In the analysis of complex unit data, the trend showed a positive correlation with the EUI, but the trend variable in the household unit data was insignificant. That is, after the implementation of new tariff system, the EUI in complex unit data increased, but the EUI in household unit data was independent of the new tariff system.

In complex unit data, among the interaction terms, only Orientation x Trend and Ratio over 65-year-old x Trend showed statistically significant correlation. The ratio over 65-year-old variable had a positive correlation with EUI (Energy Use Intensity), and after the implementation of new progressive tariff system, the positive correlation has been strengthened. On the other hand, The Occupancy have a positive correlation with EUI (Energy Use Intensity), but after the implementation of new progressive tariff system, the positive correlation has been reduced.

In this study, two datasets with different unit of analysis were used, which means the need for integrated and specific data for the study of residential electricity consumption. Comprehensive data, including household electricity consumption and socio-economic and built environmental characteristics of the household with location information, will allow accurate analysis of various factors on residential electricity consumption and the effects of the new electricity tariff system.
2016년 12월 정부와 한국전력은 지속되는 폭염으로 인한 전기요금 부담 경감을 위해 누진제도를 완화했다. 새로운 누진제도는 누진 구간을 3단계로 축소하고 누진율은 3배로 완화했다. 누진제도에 관한 선행연구는 새로운 누진제도의 시행 전과 후로 나뉜다. 시행 이전에는 시나리오 분석 중심의 연구가 진행되었으며, 시행 후에는 가가계통계자료를 이용한 시행 전후의 전기사용량 변화를 비교하는 연구들이 이루어졌지만 실제 사용량은 이용한 연구는 찾아보기 어려웠다. 몇몇의 새로운 누진제 시행 후 전기 사용량의 변화 분석에 대해 실제 사용량 데이터를 이용한 실증 연구가 있었지만 그 연구들은 가계소득과 같은 사회 경제적 특성만 독립변수로 고려했다.

하지만 전기 사용량에는 도시 지형적 요인, 건물 형태, 냉난방 시스템의 효율, 그리고 거주자의 행동 등 다양한 요인이 영향을 미친다. 따라서 완화된 누진제 시행 후 전기 사용량의 변화는 위의 다양한 변수들에 의해 달라질 것이다. 이에 대해 본 논문은 새로운 누진제도의 시행 후 전기 사용량의 변화를 분석하고, 전기 사용량의 변화에 대한 사회경제적 변수와 건축 환경적 변수들의 영향을 분석했다. 또한 새로운 정책의 도입과 사회경제적 요인의 조절효과 분석을 통해 새로운 누진제도에 따른 사회경제적 요인들의 영향 변화를 분석했다.

본 연구에서는 새로운 전기 요금 누진제도, 사회 경제적 요소 및 건축환경적 요소의 EUI (Energy Use Intensity)에 대한 영향을 분석하기 위해 아파트단지 단위와 가구 단위의 두 가지 데이터셋을 사용했다. 아파트 단지 단위의 전기 사용량을 이용해서 FAR, BCR과 같은 밀도와 주변의 녹지 비율이 전기사용량에 미치는 영향을 확인할 수 있었다. 또한 새로운 전기요금제도의 시행 후 전기 에너지 사용량 변화를 확인하고 사회 경제적 요인에 따른 변화도 확인할 수 있었다. 하지만 아파트 단지 단위의 사회 경제적 변수들은 aggregate된 변수로서 개별 가구의 특성이 전기 사용량에 미치는 영향에 대해서 설명하기는 부족했다. 이를 보완하기위해 개별 가구의 특성과 전기 사용량 데이터를 갖는 가구단위 데이터 셋을 추가적으로 분석했다.

본 연구에서는 분석단위가 다른 두 개의 데이터 셋을 이용했는데 이는 주택용 전기에너지 연구를 위한 통합적인 데이터의 필요성을 의미한다. 가구단위의 주택용 전기 사용량과 해당 가구의 사화경제적 특성 및 해당 가구의 위치를 포함한 건축환경의 특성을 모두 포함하는 통합적이고 구체적인 데이터의 제공은 주택용 전기 사용량에 영향을 미치는 다양한 요인들의 분석과 새로운 전기 요금 제도의 효과를 정확히 분석할 수 있게 할 것이다.
Language
eng
URI
https://hdl.handle.net/10371/171036

http://dcollection.snu.ac.kr/common/orgView/000000162802
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Graduate School of Environmental Studies (환경대학원)Dept. of Environmental Planning (환경계획학과)Theses (Master's Degree_환경계획학과)
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