Hyeyoung Sim (2024)
Doctor of Philosophy in City Planning in Environmental Studies
Seoul National University
Advisor: Sun-Jin Yun
The revitalization of electric vehicle charging stations (EVCS) plays a pivotal role in the transition from internal combustion engine vehicles to electric vehicles (EVs). Ensuring stable charging for EV users is imperative to facilitate this transition, as lengthy charging times remain a significant barrier to EV adoption. To achieve this, a reliable supply of EVCSs is essential. Previous research has suggested that while the equitable distribution of EVCSs may enhance accessibility, it may also lead to reduced charging behavior due to longer charging times and frequent charging failures. Consequently, establishing hub-type dense charging areas may be more effective rather than emphasizing equal spatial distribution. Therefore, the expansion policy for government-type public EVCSs, which typically aims for quantitative expansion and equal location, faces limitations. Understanding the actual usage patterns around EVCSs and the influencing factors is crucial to overcoming these limitations. Charging behavior has predominantly been studied from the perspective of EV drivers, focusing on categorization and identification of influencing factors. However, discussions regarding categorization have largely overlooked charging stations themselves. Factors influencing charging behavior encompass various aspects, including drivers, EVCSs, and environmental factors. Notably, the unique characteristics of charging behavior, such as its time-intensive nature, warrant careful consideration, yet there has been a notable lack of focus on the neighborhood context surrounding charging stations. The efficient operation of public EVCSs as valuable resources necessitates a comprehensive understanding of their characteristics and management strategies informed by influencing factors. This study seeks to categorize EVCSs based on charging behavior and develop tailored management plans for each type. Additionally, it aims to analyze the factors influencing charging performance across different types of EVCSs and investigate the impact of alternative charging facilities. A thorough investigation of 312 publicly accessible charging stations in Seoul was conducted to enhance the government's expansion strategies. Unlike previous studies that predominantly centered on EV drivers, this research shifts the focus to the charging stations themselves, categorizing them based on charging behavior dynamics. Utilizing the Gaussian Mixture Model, the study classifies the 312 EVCSs into four distinct types: short-term operation, short-term concentrated, core charging, and overretention. The short-term operation type comprises charging stations that facilitate temporary charging exclusively from 9 a.m. to 5 p.m., predominantly clustered around short-term concentrated and core charging stations. Conversely, the short-term concentrated type exhibits charging demand concentrated at specific times, particularly in the afternoon and evening of the week, with minimal instances of hogging behavior. The core charging type demonstrates stable charging frequency compared to other types, representing the highest level of charging behavior. In contrast, the overretention type primarily entails continued parking post-completion of charging. Furthermore, the study employed a model to analyze factors influencing charging behavior, considering the total model encompassing all 312 public EVCSs and specific models for short-term concentrated, core charging, and overretention types. The panel 2SLS model was deemed suitable for specific scenarios, such as the total model on weekdays and weekends, the core charging model on weekdays, and the overretention model on weekends. Commercial district activity emerged as a significant influencer of charging frequency, particularly during weekday afternoons and weekend mornings. This underscores the importance of strategic measures to optimize charging station usage, such as increasing charger capacity and adjusting parking fees, particularly for core charging type EVCSs. Additionally, installing slow chargers may effectively incentivize usage, especially for short-term concentrated and overretention types characterized by high rates of non-use. During weekend mornings, a notable positive correlation is evident between commercial district activity and charging frequency at overretention-type stations, suggesting increased demand for public rapid charging. However, significant commercial district activity focused on stations with frequent hogging behavior implies that most commercial district use around charging stations coincides with charging sessions, resulting in frequent instances of hogging behavior lasting over 60 minutes. Notably, stations classified as overretention types already offer a 50% reduction in parking fees for durations exceeding an hour. Hence, diversifying charging capacities, such as by installing slow chargers, may be more appropriate for overretention types than merely augmenting existing capacities. Alternative charging options exhibit significant impacts only during weekday afternoon hours, indicating concentrated charging demand periods. Despite the low penetration rate of electric vehicles and charging stations, alternative EVCS possibilities were found to be insignificant at different times. Contrary to conventional wisdom, the study emphasizes the importance of considering convenience facilities surrounding charging stations over spatial equity between facilities. This underscores the need for a nuanced approach to charging station deployment and management, informed by neighborhood context and charging behavior dynamics. In conclusion, the study provides invaluable insights for policymakers and urban planners, offering a holistic understanding of EVCS usage patterns and influencing factors. These findings serve as fundamental guidelines for strategically selecting and managing charging station locations, ultimately facilitating the widespread adoption of electric vehicles.