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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jeon, Seungho | - |
| dc.contributor.author | Roh, Minyoung | - |
| dc.contributor.author | Kim, Muntae | - |
| dc.contributor.author | Oh, Jaeick | - |
| dc.contributor.author | Kim, Suduk | - |
| dc.date.issued | 2025-05-01 | - |
| dc.identifier.uri | https://aurora.ajou.ac.kr/handle/2018.oak/38341 | - |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105005216303&origin=inward | - |
| dc.description.abstract | Electrification is a primary strategy to achieve carbon neutrality. The expected surge in future electricity demand by battery electric vehicle (BEV) necessitates the reinforcement and construction of transmission and distribution (T&D) network. This study aims to evaluate the spatial heterogeneity impact of BEV adoption from the viewpoint of regionally balanced development on future T&D network under the ‘NetZero’ scenario. As a methodology, we developed and utilized the integrated assessment model, GCAM-EML, a version of global change analysis model (GCAM) with a regional resolution of 229 municipalities in South Korea. Under the ‘NetZero’ scenario, the national electricity demand is projected to increase by 2.18 times. Due to the rise in distributed power sources, the distribution of regional generation appears to be more uniform compared to the present or the ‘Ref’ scenario. On the other hand, electricity consumption of BEVs is predominantly focused in Seoul Capital Area, constituting 47 % of the national consumption. By computing the Gini coefficient based on the share of generation and BEV electricity consumption in each municipality, it was observed that under the ‘NetZero scenario’, the Gini coefficient decreases over time. This indicates an improvement in the ability of municipalities to meet BEVs' electricity demand locally, suggesting that the burden on T&D network due to future BEV adoption may decrease. | - |
| dc.description.sponsorship | As mentioned above South Korea has unique conditions compared to other countries, and even within its own borders, there is regional heterogeneity among its municipalities. (For details on the spatial distribution by municipality regarding population, gross regional domestic product (GRDP), electricity consumption, electricity generation, BEVs' electricity consumption, and installed BEVs' charger capacity, please refer to the Supplementary Data). The country is composed of 17 provinces, encompassing a total of 229 municipalities. Although South Korea's population has been declining since 2019, some regions still experience population growth. Statistics Korea project that by 2052, Gyeonggi province will experience the smallest population decline (0.08 % annually), whereas Ulsan province will face the largest (1.05 % annually) [12]. SCA, which includes Seoul, Incheon and Gyeonggi provinces, is a densely urbanized region. It comprises only 11.8 % of the national territory yet houses 50.5 % of the population and accounts for 51.9 % of GDP. To support such a large population, the building sector in the SCA uses 49.6 % of the country's total electricity for buildings. Additionally, the region is home to a major semiconductor industry, known for its intensive electricity usage. Due to such semiconductor industry, the industrial sector in the SCA uses 28.6 % of the country's total electricity for industry in 2020. BEVs and charging stations are also concentrated around the SCA region. In the SCA, total vehicle registrations comprise 44.1 % of the national total, and BEVs also hold a significant share at 41.8 %. Additionally, 40.7 % of the country's BEV charging infrastructure capacity is installed in the SCA. Those socioeconomic disparities between regions lead to variations in BEV distribution, a trend observable in other countries as well [13,14], and such disparities have also been shown to influence the effectiveness of environmental policies across cities, leading to uneven emission outcomes [15]. In terms of electricity supply, significant amounts of electricity are generated on the West and East coastlines due to coal-fired plants on the West coast and nuclear plants on the East coast (see Note 1 in the supplementary data for details). Therefore, the power grid in South Korea is designed to facilitate the T&D of electricity produced from different regions to the SCA [16].This work was supported by Korea Ministry of Environment (MOE) as Graduate School specialized in Climate Change. This work was supported by Ajou University, in particular through financial support from the Energy Center Research Institute. We would like to express our gratitude to Dr. Hweemoon Kim for his valuable assistance in the preparation of this manuscript. | - |
| dc.language.iso | eng | - |
| dc.publisher | Elsevier Ltd | - |
| dc.subject.mesh | Battery-electric vehicles | - |
| dc.subject.mesh | Change analysis | - |
| dc.subject.mesh | Electricity demands | - |
| dc.subject.mesh | Gini coefficients | - |
| dc.subject.mesh | High resolution | - |
| dc.subject.mesh | High-resolution integrated assessment model | - |
| dc.subject.mesh | Integrated assessment models | - |
| dc.subject.mesh | Netzero | - |
| dc.subject.mesh | Power grids | - |
| dc.subject.mesh | Transmission and distribution | - |
| dc.title | How electric vehicles impact the power grid: A spatially high-resolution analysis of charging demand and power system dynamics | - |
| dc.type | Article | - |
| dc.citation.title | Energy Strategy Reviews | - |
| dc.citation.volume | 59 | - |
| dc.identifier.bibliographicCitation | Energy Strategy Reviews, Vol.59 | - |
| dc.identifier.doi | 10.1016/j.esr.2025.101756 | - |
| dc.identifier.scopusid | 2-s2.0-105005216303 | - |
| dc.identifier.url | https://www.sciencedirect.com/science/journal/2211467X | - |
| dc.subject.keyword | Electric vehicle | - |
| dc.subject.keyword | Gini coefficient | - |
| dc.subject.keyword | High-resolution integrated assessment model | - |
| dc.subject.keyword | NetZero | - |
| dc.subject.keyword | Power grid | - |
| dc.type.other | Article | - |
| dc.identifier.pissn | 2211467X | - |
| dc.subject.subarea | Energy (miscellaneous) | - |
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