基于模糊逻辑的可控串补线路故障分类

Fuzzy-logic-based fault classification in a series compensated transmission line

提出一种基于模糊逻辑的可控串补线路故障分类方法。采集故障后半个周期的三相电流数据,选取db4小波作为小波基,使用离散小波变换(DWT)分解电流暂态信号,将小波分解系数划分为三个频带,计算每个频带的小波奇异熵,获得能反映不同故障的故障特征量。将特征量作为模糊逻辑的输入,构建模糊故障分类系统。在Matlab环境下建立电力系统模型,选择500 k V、300 km超高压输电线路进行故障仿真。仿真结果表明,不同的TCSC触发角下,该算法不受故障阻抗、故障初始角、故障类型、故障位置的影响,可以准确检测故障,完成故障分类。

This paper presents a fuzzy-logic technique for fault classification in a series compensated transmission line. The proposed method uses the samples of three line currents for half cycle duration to accomplish this task. Daubechies wavelet ＂d B4＂ is used with single level decomposition. The features of the line currents are extracted using discrete wavelet transform. The wavelet decomposition coefficient are divided into three bands to calculate the wavelet singular entropy of every frequency band to obtain the characteristics of the different failure. The extracted features are applied as inputs to the fuzzy logic for fault classification. To evaluate the feasibility of the proposed technique, it is tested on a 500 k V, 300 km transmission line for all the ten types of fault using Matlab. Simulation result indicates that the proposed approach has a good performance and it won＇t be affected by fault resistances, fault inception angle, faulty types and fault distances at different TCSC firing angles.