Ant Colony Optimization Algorithm for Power Quality Data Acquisition

WANG Jiayi; FANG Jun; GAO Peng

doi:10.3969/j.issn.1672-9722.2019.03.008

Abstract：The data existing collection of the power grid adopts centralized or single-node mode. The acquisition efficiency of these two methods is low,which is difficult to meet the acquisition requirement of massive power quality data. Based on the charac?teristics of power quality data,this paper extends data reception processing node and proposes a task scheduling optimization based on ant colony algorithm for grid power quality data acquisition,and realizes server load balancing to improve data collection efficien?cy. The experimental results show that the scheduling speed of the ant colony optimization algorithm is about 2.65 times of that of the existing data scheduling method,and the data distribution ratio of each receiving server is basically maintained at 0.3~0.4. The ant colony optimization algorithm reduces the randomness of the task allocation when the server load difference is small. The allocation ratio is close to 1:1:1. When the server load difference is large,the probability of allocating a single node in the task is reduced. The optimal range of the combination of the relevant parameters of the ant colony optimization algorithm is found,and the average time of the task is reduced about 3.7. The feasibility and validity of the ant colony optimization algorithm are verified by experiments.