Investigating the Impact of Artificial Intelligence on the Efficiency of Renewable Energy Systems in Iran

Document Type : Original Article

Author
Hossein Aliabadi
PhD student, Entrepreneurship Department, Sari Branch, Islamic Azad University, Sari, Iran
10.22034/jmek.2025.500830.1167
Abstract
Artificial intelligence (AI), as an emerging and general-purpose technology, has the potential to create fundamental transformations in the global economy and energy systems. The purpose of this study is to investigate the impact of artificial intelligence on the efficiency of renewable energy systems in Iran. The research method is descriptive-analytical and based on a systematic review of the literature and previous studies. The findings indicate that AI, utilizing techniques such as deep learning, reinforcement learning, and big data analytics, plays an effective role in energy production forecasting, equipment layout optimization, intelligent storage management, and maintenance cost reduction in solar, wind, hydro, geothermal, and biomass energy systems. Furthermore, the integration of AI with technologies such as the Internet of Things (IoT) and blockchain enables the creation of smart and transparent energy networks. The research results indicate that Iran, despite having abundant natural resources, needs to develop data infrastructure, invest in research and development, train specialized workforce, and develop smart grids to optimally exploit these capacities. This study contributes to understanding how AI can serve as a catalyst for Iran''s energy transition. Finally, the future of AI in energy management outlines a clear path for transitioning to more sustainable consumption and reducing dependence on fossil fuels.
Keywords
Artificial Intelligence
System Efficiency
Renewable Energy
Energy
Machine Learning
Subjects
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Management, Economics and Entrepreneurship Studies
Volume 6, Issue 3
Autumn 2025
Pages 56-69

  • Receive Date 19 January 2025
  • Revise Date 16 February 2025
  • Accept Date 19 August 2025