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A strategic multi-criteria decision-making framework for renewable energy source selection in Saudi Arabia using AHP-TOPSIS

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  • Amiri, Ali Ahmad
  • Wahid, Muhammad Nurdin
  • Al-Buraiki, Abdulrahman S.
  • Al-Sharafi, Abdullah

Abstract

The Kingdom of Saudi Arabia (KSA) is targeting 50 % of its energy generation from renewable energy sources (RES) by 2030. However, a comprehensive approach is needed to prioritize the available RES in the kingdom. This study employs a survey-based approach which gathered insights from several academic and industrial experts and then utilizes analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods to determine the optimal RES. In this case, hybrid RES (solar-wind, solar-geothermal, solar-biomass) is evaluated against single-source alternatives based on different criteria including cost-effectiveness, land conservation, low intermittency, resource potential, design simplicity, and social acceptance. The results showed that cost-effectiveness emerged as the predominant criterion with importance of 31 % followed by low intermittency and resource potential contributing with 24 % and 22 % in importance, respectively. Based on these findings, solar energy is recognized as the best RES, with a priority level of 23 % followed by the hybrid solar-wind and hybrid solar-geothermal, which attained priority levels of 20 and 16 %, respectively. Subsequently, a sensitivity analysis was carried out to assess the impact of varying criteria weights. The findings offer the decision maker useful insights into the priority of different RES in KSA.

Suggested Citation

  • Amiri, Ali Ahmad & Wahid, Muhammad Nurdin & Al-Buraiki, Abdulrahman S. & Al-Sharafi, Abdullah, 2024. "A strategic multi-criteria decision-making framework for renewable energy source selection in Saudi Arabia using AHP-TOPSIS," Renewable Energy, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:renene:v:236:y:2024:i:c:s096014812401591x
    DOI: 10.1016/j.renene.2024.121523
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