Federated Learning and Blockchain Integrated Frame-work for Energy Management

Abstract

Energy saving is need of hour and effective energy management for Smart grids is no exception. Efficient management of Smart grids is complex task and thus needs state-of-the-art technologies for efficient management and ensuring data privacy. For secured and efficient management the emerging technologies like Federated Learning and Blockchains can be deployed. The integration of Federated learning and Blockchain offers a promising solution for these advanced and decentralized energy management systems. Federated Learning is distributed machine learning approach where the model is trained over multiple decentralized devices. data centralization. Blockchain technology offers, immutable,secured distributed ledger system that complement the Federated Learning framework. The integration of Federated learning and Blockchain facilitates secure tamper proof data analytics, which can transform energy management systems. The present research paper proposes a model for Smart grids which is based on integration of FL and BC technologies. The study discusses System Architecture for FL-BC framework. Study also proposes the possible simulation for real-world smart grid scenario consisting of smart energy devices like smart meters, solar panels, industrial IoT sensors, and Home Energy Management Systems (HEMS). It can be simulated using Python with the help of machine learning libraries like TensorFlow, PyTorch.