Volume 10: Proceedings of 12th International Conference on Applied Energy, Part 2, Thailand/Virtual, 2020

Effect of New Progressive Tariff on Electricity Use in Seoul Apartments: Evidence from Multisource Big Data and Urban Geospatial Data Steven Jige Quan, Kyungdo Kim

Abstract

A new electricity progressive tariff (PT) was introduced to South Korea in 2017 to alleviate financial burden of households from air conditioning use in hot summers. Although people were concerned that this policy may lead to additional household energy use across the year, very limited evaluations have been conducted partially due to the lack of extensive and targeted datasets. This study examines how the new PT influences residential electricity use in different apartments in Seoul. A combined dataset was collected from both multisource big data and urban geospatial data. The significance of household electricity use changes of 402 apartments was estimated based on the dataset with interrupted time series analysis. Relationships between the significance of change and energy use, household socioeconomic status, and built environment of apartments and neighborhoods were further examined using logistic regression. Results showed that significant changes are likely to occur with reduced previous electricity use, high adult male ratio, and high apartment density. The findings of this study can help policymakers further evaluate the new policy for sustainability goals, including social welfare, urban energy, and economic development.

Keywords progressive tariff, energy policy evaluation, residential electricity use, energy use behavior, interrupted time series analysis, built environment

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