Coverage evaluation of public electric vehicle charging stations in Bangkok, Thailand using location-allocation model

• The distribution of public charging stations was evaluated by analyzing spatial accessibility and service capabilities. • Location-allocation analysis is employed to assesses the coverage of existing charging stations relative to estimated charging demands. • The sensitivity analysis highlights the impact of operating hours and SoC regain levels on demand coverage and station selection. • Charging stations in specific sub-districts are needed to meet the growing demand, and coverage decreases under peak hour constraints. Electric vehicles (EVs) have emerged as a promising solution to address environmental concerns. With the global rise in EV adoption, establishing an efficient and accessible charging infrastructure is crucial. Charging stations play a vital role in facilitating EV adoption by providing convenient locations for vehicle recharging. However, research assessing the effectiveness of charging stations in meeting EV users’ demands and ensuring their coverage in Thailand is limited. This study evaluates the distribution of public charging stations in Bangkok, Thailand, by analyzing spatial accessibility and considering access limitations and service capabilities. Location-allocation analysis in ArcGIS Pro is employed to assesses the coverage of existing charging stations relative to estimated charging demands. Questionnaire survey results, including EV model and charging behavior information, are used to determine capacity constraints of each charging station. The sensitivity analysis was also performed to highlight the impact of operating hours and SoC regain levels on demand coverage and station selection. Findings reveal that existing public charging stations generally meet the charging demand, but capacity and distribution need attention. Additional charging stations are necessary in specific sub-districts to effectively meet the growing demand, and coverage decreases when considering peak hour constraints, emphasizing the need for strategic expansion. The sensitivity analysis results imply that flexible service strategies and demand-responsive planning are essential to optimize the efficiency and accessibility of charging infrastructure.