Integrating artificial intelligence (AI) and virtualization technology into power systems applications can facilitate the transition from conventional grids to smarter grids. Virtualization of grid application, including AI-based applications, near the edge of the grid reduces communication latency and promotes centralized or decentralized decision-making. The infrastructure of edge or cloud datacenters serves as a robust platform for deploying intelligent virtual applications within smart grids. In this paper, we propose a concept of intelligent virtualized relaying using 5G communication. The concept is demonstrated through a hardware-in-loop setup consisting of an MLP algorithm deployed on the edge server, a grid model in OPAl-RT, and UDP protocol communication of voltage and current information over the 5G network. In 5G communication, latency poses a challenge when a fault occurs in the power system and immediate decision-making is required. In this paper, we attempt to predict faults, which are followed by precursor events or pre-fault signatures, to overcome the latency barrier of 5G communication. Our MLP algorithm achieved an accuracy of 99.9%, enabling it to predict faults based on pre-fault signatures, isolate the fault, and island the load with backup distributed generation (DG). Based on the results obtained from Test-1 and Test-2, the fault was predicted within 90ms and 200ms.
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Saleh et al. (2024) studied this question.
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