Document Type : Research Article
Authors
1
Associate Professor, Department of Management and Accounting, College of Farabi, University of Tehran, Iran
2
PhD Candidate of Business Policy Making at SR.C.(Islamic Azad University, Science and Research Branch)
3
M.Sc. Student in Accounting, Daneshestan Institute of Higher Education, Saveh, Iran
4
Ph.D. Student in Industrial Management, Semnan University, Semnan, Iran
10.22091/jaem.2026.17276.1062
Abstract
The rapid expansion of artificial intelligence (AI) has significantly increased the energy, cooling, and water demands of data centers, creating critical sustainability challenges in water-stressed regions. This study evaluates sustainable energy architectures for AI data centers in Iran, where electricity constraints, water scarcity, climatic pressures, and digital infrastructure growth interact simultaneously. A crisp multi-criteria decision-making framework integrating CRISUS and ARIE was developed. CRISUS was applied to determine the importance of ten technical, economic, environmental, and operational criteria, while ARIE was used to rank five integrated architectures incorporating renewable energy, storage systems, advanced cooling, demand response, and heat recovery technologies. The results identified Water Usage Effectiveness (WUE) as the most influential criterion (0.3379), followed by renewable-energy share (0.1849), carbon intensity (0.1453), and grid dependency (0.1009), which collectively represented 76.9% of total importance. The ARIE analysis ranked the solar–wind hybrid architecture with grid integration, hybrid battery/supercapacitor storage, direct-to-chip liquid cooling, demand response, and waste-heat recovery (A5) as the most sustainable option (RC=0.6015). The dry-cooling solar–wind architecture (A3) achieved the second position, emphasizing the importance of reducing freshwater consumption in highly water-stressed environments. Sensitivity analysis confirmed the robustness of the rankings. The findings highlight that sustainable AI data-center development requires integrated energy–water planning, renewable-energy diversification, efficient cooling strategies, flexible storage, reduced grid dependency, and enhanced operational resilience, particularly for future AI infrastructure in Iran.
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