电力计量装置运行数据自适应整合算法设计

Design of Adaptive Integration Algorithm for Operation Data of Power Metering Devices

以往的电力计量装置运行数据自适应整合算法未考虑数据的特征加权值,导致整合精度不高。因此,本文设计了电力计量装置运行数据自适应整合算法,将电力计量装置在运行过程中产生的数据进行聚类。在此基础上,依据概率分布密度的方法,对聚类中心的数据进行特征重组。随后,以特征重组过的数据为基础,计算数据的特征加权值,生成自适应整合算法,完成对电力装置运行数据自适应整合算法的设计。在仿真实验中,与以往的电力计量装置运行数据自适应整合算法相比,设计的电力计量装置运行数据自适应整合算法具有更高的整合精度。

Previous adaptive integration algorithms for operation data of power metering devices did not take into account the characteristic weighting values of the data,resulting in low integration accuracy.Therefore,an adaptive integration algorithm for operation data of power metering devices is designed.Clustering the data generated during the operation of power metering devices,and based on this,using the method of probability distribution density,restructuring the data in the clustering center.Subsequently,based on the restructured data,calculating the feature weighting values of the data,generating an adaptive integration algorithm,and completing the design of an adaptive integration algorithm for power device operation data.In simulation experiments,compared with previous adaptive integration algorithms for power metering device operation data,the designed adaptive integration algorithm for power metering device operation data has higher integration accuracy.