摘要
在配电网中广泛采用小电流接地方式,传统的单一单相接地故障选线方法适用范围有限。针对单一故障选线方法的不足,提出利用模糊神经网络对多种选线方法进行融合。采用基于小波包从零序电流中提取暂态能量分量和暂态方向分量,和基于FFT从零序电流中提取稳态基波分量和五次谐波分量作为故障选线的特征分量。设计模糊神经网络的结构并进行改进,采用BP学习算法。在Matlab 7.1环境下搭建10kV配电网模型,分别仿真不同的故障位置、故障合闸角、故障接地类型和故障线路的故障以验证理论的有效性。
In the distribution network, neutral ineffectively grounding system is widely used. The applicable scope of traditional single phase fault ground line selection is limited. Various methods of earth fault line selection are combined using fuzzy neural networks （FNN） against the shortcoming of single fault line selection method. Steady-state fundamental component, steady-state fifth harmonic component, transient energy component and transient direction component extracted from zero-sequence current separately by means of FFT and wavelet packet are used as fault features to perform fault line selection. The structure of fuzzy neural networks （FNN） is designed and improved. Back-propagation （BP） algorithm is adopted as training algorithm. At last, a 10 kV distribution networks simulation model is set up by Matlab7.1. Fault ground types, fault location, fault close initial angles, and fault lines are simulated to demonstrate the feasibility of the theory.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2010年第22期120-125,共6页
Power System Protection and Control
关键词
故障选线
稳态基波分量
五次谐波分量
暂态方向分量
暂态能量分量
小波包
模糊神经网络
earth fault line detection
state fundamental signal component
the fifth harmonic signal component
transient current direction component
transient current power component
wavelet packet
fuzzy neural networks
