Synergistic Smart Grid: Instability and Fault Detection using Blockchain and Federated Learning

초록

Smart grids have revolutionized energy management by integrating IoT, allowing real-time monitoring and optimization. However, this connectivity also increases vulnerability to cyber threats. We propose an innovative solution that combines federated learning with a customized IoT-PureChain network to enhance fault detection and grid stability. Utilizing a hybrid model with LSTM and dense layers tailored for decentralized IoT data, our approach leverages two key datasets for fault simulation and stability analysis. We address non-IID data challenges by employing a trimmed mean aggregation, enhancing robustness and accuracy. Our blockchain, designed for IoT, uses a Proof-of-Authority with Association consensus and adaptive mining for high-efficiency, gas-free transactions. This research demonstrates a scalable, secure, privacy-focused system and paves the way for further exploration in IoT blockchain synergy and advanced federated learning.