Phase estimation method for power system based on complex adaptive neural network

被引：0

作者：

Li Y.-L. ^{[1
]}

Wang D.-Z. ^{[1
]}

Ning Y. ^{[1
]}

Hui N.-M. ^{[1
]}

机构：

[1] School of Information Science & Engineering, Northeastern University, Shenyang

来源：

Dongbei Daxue Xuebao/Journal of Northeastern University | 2017年 / 38卷 / 01期

关键词：

Frequency tracing; Grid phase; Neural network; Phase estimation; Unbalanced voltage;

D O I：

10.3969/j.issn.1005-3026.2017.01.002

中图分类号：

学科分类号：

摘要：

Aiming at the difficulty of grid phase detection under non-ideal voltage caused by unbalanced voltage and frequency fluctuation, a phase estimation method was proposed for power system based on complex adaptive neural network. On the basis of neural network model of non-ideal grid voltage, the weight update method of complex least mean squares to the process of weight update procedure of neural network was introduced. Then the weights of neural network were used to calculate the phase. To trace the frequency of grid, a frequency tracing unit was designed and it was proved to be convergent. The simulation and experiment results demonstrate that the proposed method is able to estimate the phase rapidly and precisely under non-ideal voltage conditions. © 2017, Editorial Department of Journal of Northeastern University. All right reserved.

引用

页码：6 / 10

页数：4

共 16 条

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