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

Year: 2026

Type: article

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.

Source: Springer Link (Chiba Institute of Technology)

DOI: 10.1051/e3sconf/202669403002/pdf

Authors: Ilham Husam Hasan Albakry, Haider TH. Salim ALRikabi, Faisal T. Abed, Hawraa Hussain Jabor

Institution: University of Wasit

Language: English

Topic: Blockchain Technology Applications and Security

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy, Climate action

Open Access status: green

OpenAlex ID: W7129611308

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