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

Abstract

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.