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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Bahman Zohuri1, Farhang Mossavar-Rahmani2 and Mehdi Abedi-Varaki3
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DOI:10.17265/1934-8975/2025.03.002
1. Ageno School of Business, Golden Gate University, San Francisco 94105, California, USA
2. Finance School of Business Technology and Engineering, National University, San Diego 92110, California, USA
3. FTMC-Center for Physical Sciences and Technology, Savanoriu Ave. 231, LT-02300 Vilnius, Lithuania
AI, smart grid, energy demand, data centers, load balancing, renewable integration, grid modernization, deep learning power consumption, real-time monitoring, AI in energy systems.