Optimal Location Selection for Electric Vehicle Charging Stations in Erzincan City Center: A GIS-Based Multi-Criteria Decision Analysis

The global energy transition and sustainable transportation policies are rapidly accelerating the adoption of electric vehicles (EVs), necessitating integrated planning of charging infrastructure. Supply instability in global energy markets and rising costs have made reducing fossil fuel dependence in the transportation sector a strategic necessity.This study presents a model integrating Geographic Information Systems and Multi-Criteria Decision Analysis to identify optimal locations for EV charging stations in Erzincan city center, situated at the intersection of Turkey’s critical transportation corridors. The analysis is structured around six core criteria: energy demand scores derived from building morphology, proximity to transformer substations, primary transportation networks, existing gas stations, current charging units, and urban green spaces. Kernel Density analysis was utilized to model building-based energy demand, while Euclidean Distance was employed for accessibility parameters. Spatial datasets were synthesized using the Weighted Overlay method. The findings reveal that the highest suitability scores are concentrated around the "Dörtyol" junction and its commercial surroundings, which serve as the city's commercial and transportation hub. Furthermore, the study identifies a unique local characteristic: 93.47% of the electric vehicle fleet in Erzincan consists of motorcycles, highlighting the need for local planning strategies to incorporate electric motorcycle-oriented charging solutions.