基于蜂群算法的低压电力线高频RLCG 模型参数辨识

电力线是通用的电力网络间的连接载体,同时也是传导电磁干扰和载波通信信号的主要传播介质.建立准确的电力线电参数模型是研究传导电磁干扰和载波信号传输特性的基础.采用一种考虑集肤效应和介质损耗的高频信号传输的RLCG模型对普通的三线低压电力线进行建模,并利用人工蜂群算法对模型参数进行辨识,该模型考虑了高频条件下电力线的趋肤效应以及电介损耗对信号传输特性的影响.利用网络分析仪测量实际电力线的阻抗特性作为标准数据,与传统的基于遗传算法的辨识方法的仿真结果进行对比,证明了所提出的电力线高频RLCG模型可以准确地反映电力线的高频传输特性,为低压电力线载波通信和电磁兼容分析奠定基础.

Parameter identification of power line high frequency RLCG model based on artificial bee colony algorithm

Power line is an important carrier in general electric network and the major propagation path of conducted electromagnetic interference.An accurate electrical parameter model of the power line will improve the reliability of the simulation of electromagnetic interference.This paper proposes a new type of high-frequency RLCG model for power line, with the use of artificial bee colony algorithm as a parameter identification method.Further, the influence of skin effect and dielectric loss under the high frequency are taken into account.The actual power line impedance characteristics given by the network analyzer is treated as reference data, and the simulation results of the traditional recognition method based on genetic algorithm and the proposed method are compared.It is demonstrated that the high frequency transmission characteristics of power line is accurately reflected by the proposed model, which provides theoretical basis for the following power line electromagnetic compatibility simulation.