Blockchain‐Enabled Secure IoT‐Based Smart Grid for Distributed Energy Resource Systems Using Federated Learning

ABSTRACT Distributed energy resources (DERs) are increasingly proliferating worldwide, driven by their benefits in promoting energy sustainability, efficiency, and resiliency. Coordinated approaches are crucial for aggregating diverse DERs across large areas, yet the increasing reliance on information technology exposes power systems to cyberattacks. Integrating DERs into the power system increases exposure to cyber threats due to their distributed nature and often insufficient security measures. A layered, defence‐in‐depth strategy is crucial for protecting these resources. It should incorporate robust technical safeguards and continuous monitoring to ensure secure and reliable operation of DERs in modern power grids. Unfortunately, the increased information flow will increase the potential attack surface and introduce new vulnerabilities. In this paper, we proposed blockchain‐enabled secure IoT‐based smart grid for distributed energy resource systems using federated learning. The simulation results clearly demonstrate the robustness and effectiveness of the proposed blockchain‐enabled secure smart grid for distributed energy resource systems using federated learning in detecting and classifying cyberattacks across multiple benchmark datasets. The model achieves consistently high detection accuracy, reaching 99.12% on CICIDS2017, 98.75% on UNSW‐NB15, and 99.3% on CICDDoS2019, indicating strong generalisation capability across diverse network traffic patterns and attack scenarios. The results confirm that the proposed system achieves enhanced scalability, reduced computational complexity, faster processing, and improved real‐time responsiveness for secure smart grid and distributed energy resource management applications.