基于5次谐波能量和LM—Elman的配电网单相故障选线

基金项目:

“十二五”国家科技支撑项目（2012BAB13B04）

详细信息

Research of single-phase fault line selection of power distribution network based on fifth harmonics energy and LM-Elman neural network

1.
College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China
2.
State Grid Shandong Weifang Hanting Power Corporation, Weifang 261100, China

摘要: 针对传统的基于5次谐波的幅值比较选线法准确率低的问题，提出了基于5次谐波能量和LM-Elman的配电网单相故障选线方法。首先利用小波包对配电线路零序电流中的5次谐波进行3层分解和重构，求出第3层重构的小波系数的总能量；然后将归一化处理后的能量值作为Elman神经网络的输入，采用LM算法进行训练和测试。仿真结果表明，该方法能够准确地判断配电网的故障线路。
- 故障选线 /
- 5次谐波能量 /
- Elman神经网络 /
- LM算法
Abstract: In view of the problem of low accuracy of amplitude comparing line selection method based on traditional fifth harmonic, a single-phase fault line selection method of power distribution network based on fifth harmonics energy and LM-Elman neural network was proposed. Firstly, wavelet packet was used for three-layer decomposition and reconstruction of fifth harmonics in zero-sequence current, and the total energy of the third layer reconstructed wavelet coefficients was obtained; then normalized energy values were used as input of Elman neural network, LM algorithm was used for training and testing. The simulation results show that the method can accurately select fault line in distribution network.
- fault line selection /
- fifth harmonics energy /
- Elman neural network /
- LM algorithm