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February 19, 20260 citations

Deep Learning and Blockchain for Smart Grids: Integration, Challenges, and Future Directions

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IAIlham Husam Hasan AlbakryHAHaider TH. Salim ALRikabiFAFaisal Theyab Abed

Key Points

  • This review aims to explore the integration of deep learning and blockchain technologies within smart grids, highlighting current challenges and future possibilities.
  • Survey of recent literature on smart grids, deep learning, and blockchain.
  • Analysis of the potential research areas within these technologies.
  • Proposition of a systems-based architecture for improved integration.
  • Identified key issues such as cyber vulnerabilities and big-data management in current smart grids.
  • Discussed the advantages of AI-empowered blockchain for data integrity and decentralization.
  • Highlighted limitations in existing research and proposed future directions for integration.

Abstract

The transition in the direction of sustainable power systems is limited by the rapid growth of global energy demand driven by population growth and urbanization. Recent market forecasts demonstrate high economic growth based on an increasing reliance on smart grid infrastructures. Despite the potential benefits, Smart Grids remain characterized by several consequential problems such as cyber vulnerabilities, complexities of big-data management issues, security considerations, and issues arising from centralized control architectures. The field of combining blockchain technology with AI and other emerging technologies is gaining high relevance. AI-empowered blockchain technologies offer blockchain-based solutions to data integrity, decentralization, and automation. This review paper surveys current developments in the integration of Smart Grids, Deep Learning, and Blockchain. The contributions of this paper are: Firstly, identifying and analysing recent literature from different perspectives. Then, examining the potential research areas along with their existing limitations. In addition, introduce a new systems-based architecture that provides a novel approach to the collaboration among key techniques smart grid, deep learning, and blockchain.

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Cite This Study

Albakry et al. (2026) studied this question.

synapsesocial.com/papers/6996a8c7ecb39a600b3efd8fhttps://doi.org/10.1051/e3sconf/202669403002/pdf
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