Design of Fog-based Computing Architecture for Enhancing Secondary Distribution Grid Services Management

Power utility providers have faced an increasing need for the deployment of intelligent solutions consisting of affordable sensing and data-driven technologies to monitor the health of secondary distribution network (SDN). Existing manual-based approaches are not capable of collecting large volumes of real-time operational data to achieving significant monitoring of the SDN network for reliable power distribution. Effective monitoring would require real-time sensing, scalable high-performance computing and appropriate grid-based application for data processing. This paper presents a computing architecture for grid services monitoring to enhance real-time fault management in electrical secondary distribution networks. The platform leverages wireless sensor networks, a hybrid cloud-fog computing architecture, and a heuristic-based application coordination mechanism to efficiently manage grid applications. Experimental results indicate that coordination mechanism improved application workload distribution of up to 70% in fog nodes and 40% to the cloud. A fog-based architecture provided improvements for low latency by 70% compared to cloud-only architectures. This signifies that most of the data processing was pushed to the local fog nodes, which is crucial for fault management applications. compared to a traditional cloud-only approach.