Edge Computing Terminal Equipment Planning Method for Real-time Online Monitoring Service of Power Grid

The safety of the transmission line plays a vital role in the stable operation of the entire power grid. In order to ensure the normal operation of the power grid system, it is necessary to increase the monitoring strength of the cable by real-time online monitoring of the cable. The real-time online monitoring service increases the monitoring frequency and has a high latency requirement. It is difficult for existing cloud computing centers to process high-volume massive data. Therefore, it is necessary to use edge computing technology to set an edge computing node on the side close to the service terminal to reduce the transmission delay and alleviate the pressure on the cloud. In this paper, based on the research of edge computing node planning strategy, with the goal of minimizing economic cost and minimum average delay, and taking the business delay requirement as the constraint, an edge computing node planning model for cable real-time online monitoring is established. In order to solve the problem that the classical genetic algorithm converges too fast and the local search ability is poor, an improved genetic algorithm based on predator search strategy is proposed to solve the node planning problem model, and the number of edge computing nodes and the deployment plan are obtained. Simulation experiments show that the algorithm can effectively implement the planning of edge nodes, which not only meets the business requirements, but also ensures the cost optimization.