AI and Blockchain for Smart Grids: Secure Intelligence, Trusted Data, and Resilient Energy Systems

Submission Deadline: 30 July 2026 View: 93 Submit to Special Issue

Guest Editors

Prof. Hamed Taherdoost

Email: hamed.taherdoost@gmail.com

Affiliation: Arts, Communications & Social Sciences, University Canada West, Vancouver, Canada

Homepage:

Research Interests: smart grids, blockchain, cybersecurity, AI

Assoc. Prof. Tuan-Vinh Le

Email: tvle@mail.fju.edu.tw

Affiliation: Bachelor's Program of Artificial Intelligence and Information Security, Fu Jen Catholic University, New Taipei City, Taiwan

Homepage:

Research Interests: smart grids, information security, cryptography, blockchain

Summary

Smart grids are evolving into intelligent, data-intensive cyber-physical systems where artificial intelligence (AI) enables predictive analytics and operational optimization, while blockchain provides trusted data provenance, decentralized coordination, transparency, and auditability. This Special Issue aims to highlight research and applied innovations that integrate AI and blockchain to strengthen smart grid security, resilience, efficiency, and governance while also considering leadership, business, and regulatory implications of real-world adoption.

Potential topics aim at covering themes including, but not limited to:
- AI- and blockchain-enabled smart grid architectures and digital infrastructure
- Blockchain-based trusted data provenance for smart grid monitoring and analytics
- Smart contracts for automated settlement, demand response, and energy transactions
- Decentralized coordination of DERs, microgrids, and virtual power plants (VPPs)
- Peer-to-peer (P2P) energy trading and AI-driven pricing/forecasting
- AI and blockchain for cybersecurity monitoring, intrusion detection, and incident response
- Governance, compliance, auditability, and privacy in smart-grid blockchain deployments
- Risk management, resilience, and trust mechanisms in decentralized energy systems
- Leadership and organizational strategies for scaling AI/blockchain adoption in smart grids
- Practical case studies, pilot implementations, and industry-led contributions

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