Smart Grid Meets URLLC: A Federated Orchestration With Improved Communication for Efficient Energy Resources Management

Efficient data communication and machine learning aspects are crucial for orchestrating the distributed resources of smart grid (SG) networks. 5G telecom technologies have enabled ultrareliable low-latency communication (URLLC) to provide low-latency data communication and accelerate distributed machine learning [such as federated learning (FL)] with high reliability. For critical SG operations, such as islanding detection and instability of frequency regulation, the adoption of URLLC and FL appears paramount to enable near real-time communication and collaborative decision making for resource management. However, SG with URLLC and/or FL has been poorly studied in the literature. We develop a novel framework and demonstrate our findings on the importance of URLLC and FL for efficient energy trading between distributed energy sources and to minimize energy loss by enhancing the resilience of critical SG operations. Extensive experiments using real-time data sets validate our design assumptions and ideas.