Sustainable planning of EV charging infrastructure in urban regions: A hybrid GIS-MCDM approach for West Java, Indonesia

Abstract

Rapid urbanization and increasing energy demand have intensified environmental pressures, particularly in the transportation sector, which remains one of the largest contributors to greenhouse gas emissions. Although electric vehicles (EVs) represent a cleaner alternative, their widespread adoption in developing countries is constrained by insufficient and poorly planned charging infrastructure. This study introduces a hybrid Geographic Information System (GIS) and Fuzzy Analytical Hierarchy Process (F-AHP) framework for optimizing Electric Vehicle Charging Station (EVCS) site selection in West Java, Indonesia, a densely populated and hazard-prone region. Eighteen technical, environmental, social, and disaster-related criteria were evaluated through expert weighting and spatial overlay analysis to develop a disaster-integrated suitability map. The results show that only 5.02% (≈2079 km2) of the province is suitable for EVCS deployment, primarily concentrated in lowland urban areas such as Bogor, Bekasi, and Bandung, while 94.98% is unsuitable due to steep topography, active faults, and flood-prone zones. The integration of AHP and F-AHP enhances analytical precision by addressing uncertainty and expert subjectivity in complex decision-making environments. Theoretically, this research bridges a critical gap between sustainable mobility planning and disaster risk science by demonstrating the adaptability of fuzzy-based MCDM in resilient infrastructure development. Practically, the proposed model serves as a decision-support tool for policymakers, the national electric utility company, and the Ministry of Energy and Mineral Resources to guide spatially equitable and disaster-resilient EVCS deployment aligned with Indonesia’s net-zero emission targets.

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