Optimizing Utility-Scale Solar PV Site Selection Using GIS and MCDM Approaches: A Case Study in Bhutan

Solar PV, GIS, MCDM, FAHP, MOORA, TOPSIS, Site suitability, Bhutan

Abstract

Solar energy is widely regarded as the cleanest renewable energy source, with an increasing global adoption in the environment and the depletion of fossil fuels. Bhutan, despite its dependence on hydropower, has set ambitious targets in its 2013 alternative
renewable energy policy and the 13th Five-Year Plan to expand solar energy capacity to 500 MW by 2025 and 1000 MW by 2030 through utility-scale solar projects. However, identifying optimal locations for solar photovoltaic (PV) farms requires a systematic approach that considers climatological, environmental, and economic factors. Therefore, this study employs Geographic Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) techniques, including Fuzzy Analytic Hierarchy Process (FAHP), Multi-Objective Optimization by Ratio Analysis (MOORA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), to evaluate and rank potential solar PV sites across Bhutan. Key factors such as solar radiation, temperature, rainfall, slope, aspect, elevation, land use/land cover (LULC), and proximity to roads and settlements were used during the analysis. The data presents the distribution of solar PV suitability with 1304.33 km2 (3.39%) as highly suitable and 22463.95 km2 (38.01%) as suitable for solar PV in Bhutan. Furthermore, the result highlights that Haa, Samtse, Bumthang, Paro, Chhukha, Thimphu, Trashigang, and Dagana as the most suitable districts for solar PV deployment in the country. The result shows a strong alignment with existing solar plants deployed, such as Shangsa, Dechencholing, Sephu, and Rubesa, validated through sensitivity analysis. The study demonstrates the effectiveness
of hybrid GIS-MCDM models in optimizing renewable energy planning and provides actionable insights for policymakers to achieve Bhutans solar energy goals.