Geospatial Analysis for Electric Vehicle Charging Infrastructure Development in Mindanao
Keywords:
Electric Vehicle (EV), EV Charging Station, Geospatial analysis, Geographic Information System (GIS), MindanaoAbstract
This study presents a geospatial methodology for the optimal siting of Electric Vehicle Charging Stations (EVCS) across the island of Mindanao, Philippines. With limited existing infrastructure and vast intercity distances, the research aims to support the country’s transition to sustainable mobility by identifying technically viable and strategically located EVCS sites. Using a sequential site refinement approach, the analysis integrates shortest-path routing, elevation profiling, grid accessibility, and solar irradiance potential to evaluate candidate locations along long-haul transport corridors. Eleven strategic city pairs were selected based on criteria including corridor length, economic significance, terrain challenges, and infrastructure gaps. Initial EVCS placements were determined using midpoint and anchor-site strategies on validated road networks. These placements were then refined through a stepwise GIS-based filtering process. Of the nine initial candidate sites, four were identified as anchor sites and five as midpoint sites. Elevation constraints did not eliminate any candidate locations, indicating full topographic feasibility. Solar resource analysis confirmed suitability for the majority of the proposed network. In addition, thirteen assumed urban electric vehicle charging station (EVCS) locations were incorporated into the network assessment. Elevation data from SRTM DEMs informed terrain-sensitive adjustments, while the lack of substation-level grid proximity data necessitated prioritizing solar-hybrid solutions. GHI values from the Global Solar Atlas confirmed the suitability of off-grid solar deployment in most proposed sites. The final EVCS network consists of midpoint and anchor stations supported by solar or hybrid energy systems, complemented by assumed urban charging infrastructure in major city terminals. This research provides a replicable, data driven framework for EVCS planning in emerging regions. It serves as a decision-support tool for policymakers, energy planners, and private-sector stakeholders seeking to accelerate electric vehicle adoption in the Philippines.
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Alrubaie, A.J., Salem, M., Yahya, K., Mohamed, M., & Kamarol, M. (2023). A comprehensive review of electric vehicle charging stations with solar photovoltaic system considering market, technical requirements, network implications, and future challenges. Sustainability, 15(10), 8122. https://doi.org/10.3390/su15108122
Asian Development Bank. (ADB). (2021). Electric vehicle infrastructure development in Asia and the Pacific. https://www.adb.org/publications
Banegas, M., & Mamkhezri, J. (2023). Terrain-sensitive planning for EV infrastructure in mountainous regions. Transportation Research Part D: Transport and Environment, 117, 103690. https://doi.org/10.1007/s11356-023-27383-6
Bhat, M.Y., Sofi, A.A., & Ganie, J.A. (2025). Green wheels in motion: Electric vehicle sales in the path to decarbonization. Transportation Research Part D: Transport and Environment, 142, 104704. https://doi.org/10.1016/j.trd.2025.104704
Bjerkan, K.Y., Nørbech, T.E., & Nordtømme, M.E. (2016). Incentives for promoting battery electric vehicle (BEV) adoption in Norway. Transportation Research Part D: Transport and Environment, 43, 169–180. https://doi.org/10.1016/j.trd.2015.12.002
Calvo-Jurado, C., Ceballos-Martínez, J.M., García-Merino, J.C., Muñoz-Solano, M., & Sánchez-Herrera, F.J. (2024). Optimal location of electric vehicle charging stations using proximity diagrams. Sustainable Cities and Society, 113, 105719. https://doi.org/10.1016/j.scs.2024.105719
Charly, A., Thomas, N.J., Foley, A., & Caulfield, B. (2023). Identifying optimal locations for community electric vehicle charging. Sustainable Cities and Society, 94, 104573. https://doi.org/10.1016/j.scs.2023.104573
Csiszár, C., Csonka, B., Földes, D., Wirth, E., & Lovas, T. (2020). Location optimisation method for fast-charging stations along national roads. Journal of Transport Geography, 88, 102833. https://doi.org/10.1016/j.jtrangeo.2020.102833
Dávila-Sacoto, M., Toledo, M., Hernández-Callejo, L., González, L.G., Alvarez Bel, C., & Zorita-Lamadrid, Á. (2023). Location of electric vehicle charging stations in Inter-Andean corridors considering road altitude and nearby infrastructure. Sustainability, 15(24), 16582. https://doi.org/10.3390/su152416582
Department of Energy. (2022). Power Situation Report 2022 (p. 16).
Department of Energy. (2023). DOE Key Energy Statistics 2023 (p. 6).
Department of Energy. (2024). Comprehensive Roadmap for the Electric Vehicle Industry. https://tinyurl.com/2u6ceeah
Department of Energy. (2023). Philippine Renewable Energy Resource Map. https://tinyurl.com/46epwp2u
Global Solar Atlas (World Bank Group & Solargis). (2024). Global horizontal irradiance database. https://globalsolaratlas.info
Google Earth Engine. (2024). Digital elevation model resources. https://earthengine.google.com
Gota, S., Huizenga, C., Peet, K., Medimorec, N., & Bakker, S. (2019). Decarbonizing transport to achieve Paris Agreement targets. Energy Efficiency, 12, 363–386. https://doi.org/10.1007/s12053-018-9671-3
Hisoğlu, S., Çömert, R., Antila, M., Åman, R., & Huovila, A. (2025). Towards solar-energy-assisted electric vehicle charging stations: A literature review on site selection with GIS and MCDM methods. Sustainable Energy Technologies and Assessments, 75, 104193. https://doi.org/10.1016/j.seta.2025.104193
International Energy Agency. (2023). Global EV Outlook 2023: Catching up with climate ambitions. https://www.iea.org/reports/global-ev-outlook-2023
Kazempour, M., Sabboubeh, H., Moftakhari, K.P., Najafi, R., & Fusco, G. (2025). GIS-based geospatial analysis for identifying optimal locations of residential on-street electric vehicle charging points in Birmingham, UK. Sustainable Cities and Society, 120, 105988. https://doi.org/10.1016/j.scs.2024.105988
Kłos, M.J., & Sierpiński, G. (2023). Siting of electric vehicle charging stations: Method addressing area potential and increasing their accessibility. Journal of Transport Geography, 109, 103601. https://doi.org/10.1016/j.jtrangeo.2023.103601
Minh, P.V., Le Quang, S., & Pham, M.-H. (2021). Technical economic analysis of photovoltaic-powered electric vehicle charging stations under different solar irradiation conditions in Vietnam. Sustainability, 13(6), 3528. https://doi.org/10.3390/su13063528
NASA POWER Project. (2024). Prediction of Worldwide Energy Resource. https://power.larc.nasa.gov
NASA SRTM. (2023). Shuttle Radar Topography Mission digital elevation data. https://tinyurl.com/2c98sdbc
Observatory Philippines. (2025). Changing forward: The shape of the Philippines electric vehicle market.
OpenStreetMap Contributors. (2024). OpenStreetMap data extracts. https://www.openstreetmap.org
Skaloumpakas, P., Kafouros, A., Spiliotis, E., Sarmas, E., & Marinakis, V. (2025). Optimizing electric vehicle charging station placement in Greek municipalities through multi-criteria decision analysis. Sustainable Energy, Grids and Networks, 41, 101589. https://doi.org/10.1016/j.segan.2024.101589
Stringer, T., Gaspay, S.M., Sunio, V., & Burelo, M. (2025). Charging ahead: Prioritizing renewable energy for electric minibuses in the Philippines. Sustainability Analytics and Modeling, 5, 100038. https://doi.org/10.1016/j.samod.2025.100038
Zhang, M., Zhu, X., Mather, B., Kulkarni, P., & Meintz, A. (2021). Location selection of fast-charging stations for heavy-duty EVs using GIS and grid analysis. 2021 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 1–5. https://doi.org/10.1109/ISGT49243.2021.9372170
Zhang, R., & Fujimori, S. (2020). Long-term strategies for electric vehicle deployment considering regional infrastructure and terrain. Energy Policy, 145, 111751. https://doi.org/10.1088/1748-9326/ab6658
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