Abstract
Energy planning and solar plant site selections are vital strategic decisions and one of the most complex executive challenges in the interconnected procedures. It is essential to study the potential renewable energy sources in Afghanistan to select the most sustainable sites for solar power production in populated cities. This study is based on the combination of a Geographic Information System, Remote sensing, and multi-criteria decision-making technique to evaluate the optimal placement of photovoltaic solar power plants in the Kabul province, capital of Afghanistan. Two models, Analytical Hierarchy Process (AHP) and Analytical Network Process (ANP), were used to select suitable areas for establishing a solar power plant. The application of the proposed model has been made possible by integrating four constraints such as climate, environmental, topography, and economical which comprised twelve criteria: solar radiation, yearly average rainfall, land slope, aspect, land use, dust, geology and proximity to faults, main roads, Normalized difference vegetation index, urban areas river and water bodies. The findings indicate that there is no considerable difference between the results of both models since both models identified more than 20% of the total area of Kabul province in suitable classes. Outputs maps conclude that northern and southern parts of Kabul city and the eastern part of Kabul province came to the range of suitable areas. It can be concluded that Kabul province is a source of sufficient potential for producing solar electricity. The results of this study can support the plans of the Afghanistan government in solar energy production and the implementation of photovoltaic power plants.
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The financial support provided by the Ministry of Higher Education of Afghanistan is highly acknowledged. We appreciate also the invaluable comments and suggestions of two anonymous reviewers.
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Naseri, M., Hussaini, M.S., Iqbal, M.W. et al. Spatial modeling of solar photovoltaic power plant in Kabul, Afghanistan. J. Mt. Sci. 18, 3291–3305 (2021). https://doi.org/10.1007/s11629-021-7035-5
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DOI: https://doi.org/10.1007/s11629-021-7035-5