Paradise
Paradise | Life Science Engineering Business Natural Science | Online ISSN 3070-1643
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Volume 2 Number 1 2026
RESEARCH ARTICLE (Open Access)
A Hybrid GIS–MCDM Framework for Regional Renewable Energy Prioritization under Energy Security Constraints in the United States
Shipon Chandra Barman1*, Ashok Kumar Chowdhury2, Atiqur Rahman 3
Paradise 2 (1) 1-8 https://doi.org/10.25163/paradise.2110688
Submitted: 03 November 2026 Revised: 14 January 2026 Accepted: 20 January 2026 Published: 22 January 2026
Abstract
The transition toward renewable energy has increasingly been framed not only as an environmental necessity but also as a strategic response to growing concerns over energy security and system resilience. Yet, determining which renewable technologies should be prioritized—and where—remains a complex, multi-dimensional challenge, particularly in geographically diverse countries such as the United States. This study develops a hybrid geospatial multi-criteria decision-making (GIS–MCDM) framework to evaluate and prioritize renewable energy alternatives while explicitly incorporating energy security considerations. Spatial datasets describing solar irradiance, wind speed, biomass availability, hydropower potential, infrastructure access, demographic distribution, and environmental risk were integrated and standardized. A hybrid weighting approach combining the Analytic Hierarchy Process (AHP) and entropy methods was applied to balance expert judgment and data-driven variability. Renewable energy alternatives were then ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), followed by regional prioritization and sensitivity analysis under varying energy security weights. The results indicate that solar photovoltaic (PV) and wind energy are the most suitable technologies at the national level, with closeness coefficients of 0.850 and 0.822, respectively. However, regional analysis reveals distinct spatial patterns: solar dominates in the Southwest, wind in the Great Plains, biomass–wind combinations in the Midwest, and hydropower in the Pacific Northwest. Sensitivity analysis demonstrates that rankings remain stable under most conditions, although wind energy becomes the top-ranked option when energy security is strongly emphasized. Renewable deployment is associated with substantial reductions in fuel import dependency (28%) and price volatility (24%). Overall, the findings suggest that effective renewable energy planning requires a balance between national prioritization and region-specific strategies, with energy security acting as a critical, though often underrepresented, decision factor.
Keywords: Renewable energy prioritization; GIS–MCDM; AHP–Entropy weighting; TOPSIS; energy security risk
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