Abstract:

Systematic power quality analysis requires the deployment of a large number of monitoring stations on the low voltage side,and there are certain requirements for the data transmission and computing capabilities of communication channels and computing equipment.To this end,this paper proposed a power quality analysis method that takes into account the optimization of edge computing task allocation.First,it builds a power quality analysis system framework under the cloud-side collaboration mode,deploys the power quality analysis algorithm Hilbert-Huang Transform (HHT) at the edge layer,thereby building a power quality analysis model based on edge computing.Then the task allocation problem of power quality monitor is analyzed,the genetic algorithm is used to solve it,and to generate the optimal task allocation strategy.Taking the electric energy data under a certain area as an example,the reliability and accuracy of the analysis method in this paper are verified.At the same time,the results of task allocation optimization are compared with the existing methods.The optimization method in this paper has a lower energy efficiency cost and can be widely used in actual engineering.

Key words: edge computing, task allocation strategy, power quality, Hilbert-Huang transform, genetic algorithm