Power, Control, and Data Processing Systems

Power, Control, and Data Processing Systems

Integration of Artificial Intelligence and Blockchain: Combining Two Transformative Technologies in Iran's Power Sector

Document Type : Review paper

Author
Master of Science in Electrical Power Engineering, Faculty of Electrical Engineering, University of Guilan, Guilan, Iran
10.30511/pcdp.2025.2072324.1043
Abstract
The aim of this study is to examine how the integration of two innovative technologies Artificial Intelligence (AI) and Blockchain can transform and enhance the efficiency, security, and transparency of Iran’s electricity sector. Accordingly, this research adopts a descriptive–analytical approach based on a systematic review of national and international academic sources to identify the capacities, challenges, and strategies for integrating these technologies into the country’s energy system. The findings indicate that AI, through predictive analytics, adaptive learning, and process optimization, can make electricity network management smarter and more efficient. Conversely, blockchain technology provides a transparent, secure, and decentralized platform for energy data exchange. The synergy between these two technologies can lead to reduced energy losses, facilitation of peer-to-peer energy trading, enhanced data security, and improved grid sustainability. However, several barriers hinder this integration, including scalability limitations, high implementation costs, incompatibility with legacy infrastructure, legal and regulatory challenges, and a shortage of skilled professionals. Finally, the study proposes strategic measures such as developing supportive policies, employing deep learning–based smart contracts, adopting low-energy blockchain solutions, and expanding IoT-based energy management systems. These actions can pave the way for the establishment of an intelligent, efficient, and sustainable electricity infrastructure in Iran.
Keywords

Subjects


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Volume 3, Issue 1
Winter 2026
Pages 13-27

  • Receive Date 21 September 2025
  • Revise Date 18 October 2025
  • Accept Date 03 November 2025
  • First Publish Date 03 November 2025
  • Publish Date 01 March 2026