Did new electricity progressive tariff system change energy usage pattern in Seoul apartments? Evidence from integrated multisource dataset and combined analytical models

Abstract

A new electricity progressive tariff (PT) system was introduced to cities in South Korea at the end of 2016 to replace the previous one as a policy response to increased energy demand and costs in hotter summers. Public concerns have been raised over its effects on annual energy use and energy poverty. However, studies on this topic are very few due to the lack of relevant data. In the broader literature on the effect of the PT system, studies are limited in that they mostly focus on household characteristics. This study contributes to the literature and practical discussions by examining how the new PT system influences residential electricity use in 243 sample apartments in Seoul, considering a wide range of factors that impact energy use decisions. An integrated urban dataset was developed based on urban big data from multiple sources, and a combination of two models was used for analysis. The interrupted time series analysis was adopted to find whether the change in household electricity use was significant for each apartment using the dataset. A logistic regression model was then used to examine the relationships between the significance of change and influential factors in energy use and billing, household, apartment, and neighborhood. Results suggest that nearly half of the sample apartments significantly increased electricity usage, and energy and built environment factors significantly influenced the change. Furthermore, higher-income groups were found to benefit more from the new PT system. The findings provide a reference for policymakers to evaluate the new policy and develop strategies toward broad sustainability goals. Given the wicked nature of urban energy policy, suggestions were made on policy implementation design and urban data integration for more rigorous evaluation.