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<p>The integration of intermittent renewable energy into smart grids introduces critical vulnerabilities in security, transparency, and real-time resilience. This paper presents a novel blockchain-secured 6G Smart grid framework that synergistically integrates sixth generation (6G) ultra-reliable low-latency communication (URLLC), distributed ledger technology, and ensemble machine learning to establish a secure, scalable, and intelligent energy ecosystem. The proposed architecture leverages adaptive 6G network slicing to support differentiated services-including peer-to-peer energy trading, grid control, and cybersecurity monitoring-while ensuring sub-30 ms latency and robust connectivity. A permission blockchain layer provides decentralized trust, immutability, and automated transaction validation via formally verified smart contracts. An ensemble learning model combining XGBoost, Random Forest, and LightGBM enables real-time multi-dimensional anomaly detection across energy, network, and transaction layers. The framework is evaluated using a synthetically generated dataset of 5000 hourly records encompassing energy generation, consumption, 6G network performance, and blockchain transactions. Experimental results demonstrate a blockchain transaction success rate of 95.16% and sustained network latency below 30 ms across all slices, even under cyberattack conditions. Reported using class-based anomaly-detection metrics, the model achieves a Recall of 0.93 and F1-score of 0.97 for the anomaly class, and a Recall of 1.00 and F1-score of 0.99 for the normal class, with an overall accuracy of 0.98. The proposed system provides a foundational architecture for resilient, autonomous, and secure renewable energy management in next generation decentralized smart grids.</p>

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A blockchain-secured 6G smartgrid framework for resilient renewable energy integration and intelligent anomaly detection

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月18日

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  • Ismail Hossain,
  • Abu Shufian,
  • Morium Akter Munny,
  • Nowshad Amin,
  • Rayan Hamza Alsisi

摘要

The integration of intermittent renewable energy into smart grids introduces critical vulnerabilities in security, transparency, and real-time resilience. This paper presents a novel blockchain-secured 6G Smart grid framework that synergistically integrates sixth generation (6G) ultra-reliable low-latency communication (URLLC), distributed ledger technology, and ensemble machine learning to establish a secure, scalable, and intelligent energy ecosystem. The proposed architecture leverages adaptive 6G network slicing to support differentiated services-including peer-to-peer energy trading, grid control, and cybersecurity monitoring-while ensuring sub-30 ms latency and robust connectivity. A permission blockchain layer provides decentralized trust, immutability, and automated transaction validation via formally verified smart contracts. An ensemble learning model combining XGBoost, Random Forest, and LightGBM enables real-time multi-dimensional anomaly detection across energy, network, and transaction layers. The framework is evaluated using a synthetically generated dataset of 5000 hourly records encompassing energy generation, consumption, 6G network performance, and blockchain transactions. Experimental results demonstrate a blockchain transaction success rate of 95.16% and sustained network latency below 30 ms across all slices, even under cyberattack conditions. Reported using class-based anomaly-detection metrics, the model achieves a Recall of 0.93 and F1-score of 0.97 for the anomaly class, and a Recall of 1.00 and F1-score of 0.99 for the normal class, with an overall accuracy of 0.98. The proposed system provides a foundational architecture for resilient, autonomous, and secure renewable energy management in next generation decentralized smart grids.