A discrete wavelet transform approach to discriminating among inrush current,external fault,and internal fault in power transformer using low‐frequency components differential current only

This paper proposes an algorithm based on discrete wavelet transform (DWT) for discriminating among inrush current, internal fault, and external fault in power transformers. Fault conditions are simulated using the Alternative Transients Program/Electromagnetic Transients Program (ATP/EMTP). Daubechies4 (db4) is employed as the mother wavelet to decompose low‐frequency components from fault signals. The ratio between per unit (p.u.) differential current and p.u. time is suggested as an index. The numerator of the ratio is the difference between the maximum differential current and the minimum differential current in terms of p.u. with a base value selected at the transformer‐rated current. The ratio is calculated for all three phases, and from a trial and error process the indices for the separation among the internal fault condition, the external fault condition, and inrush condition are defined. The results obtained from the proposed technique show good accuracy for discriminating faults in the considered system. In addition, the proposed algorithm uses data of the differential current with a time of quarter cycle under the analysis. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

利用暂态电流的输电线路单端量保护新原理探讨

对超高压输电线路的暂态电流波形奇异点（突变点）处的奇异性进行了大量的分析,发现区内,外故障时的暂态电流波形在突变点的奇异性由于母线杂散电容、结合以及阻波器等的影响而有所不同,利用小波多尺度边缘分析来检测并放大这一区内,外波形奇异度的差异,并提出利用单端故障暂态电流构成具有绝对选择性的超高速保护新原理,ＥＭＴＰ仿真证明了该原理和方法的正确性。     

小波变换在励磁涌流和短路电流识别中的应用

为了识别励磁涌流电流和内部故障电流,根据小波变换后励磁涌流在高频率段处呈现出明显的奇异性的特点,利用小波变换对变压器的励磁涌流模型和内部故障模型进行仿真分析,确定了基于一尺度下奇异值的小波判据,比较其高频段上能量的变化情况来识别励磁涌流和内部故障电流。结果表明,此方法可以对励磁涌流和内部故障电流进行良好识别。     

基于奇异性检测的高压输电线路暂态保护判据仿真研究

根据小波分析及奇异性检测的基本理论,利用小波多尺度分析方法对高压输电线路的暂态电流波形奇异点处的奇异性进行了分析与仿真,并给出了一种适合于暂态保护的新型判据。此判据通过比较不同时间窗口、不同频率段内暂态信号的小波变换谱能量比值及模分量极大量比值来实现区内外故障的准确识别。以M文件的形式用Matlab语言编程完成了奇异点检测算法程序并根据500kV输电线路模型对暂态保护新型判据进行了大量仿真。仿真结果证明此判据对不同的故障情况均能正确判断。     

基于小波分析的时差法研究

文章利用小波分析能准确检测信号奇异点的特征提出了基于小波分析的时差法。该方法能准确检测出故障时刻与差流产生时刻之间的差异,正确判断变压器区内外故障,有效防止了变压器区外短路时因电流互感器饱和而造成的差动保护误动。并以某一系统为例,在PSCAD中进行了仿真,验证了此方法的有效性。     

基于小波变换的选择性发电机100%定子单相接地保护方案

提出了基于小波变换的选择性发电机100％定子单相接地保护方案。通过直接对机端、中性点两侧的零序测量电压以及零序电流进行小波分析，利用模极大值的极性比较，能可靠地识别出发电机内、外部的定子接地故障，并对内部故障有100％的保护范围。仿真结果表明，新方案在各种运行方式下均能取得很高的保护灵敏度和可靠性，是一种较佳的具有选择性的发电机定子接地保护新方案。     

利用小波包能量区分变压器内外部故障

TA饱和是变压器差动保护中待解决的关键问题之一。通过对变压器TA饱和的深入分析及仿真研究,得出结论:TA饱和时,区外故障电流含有大量明显的突变点,而区内故障电流连续。据此结论,文章提出了一种利用小波包变换区分变压器内外部故障的新方法。首先小波包变换分别对TA饱和情况下的内外部故障电流进行分解,然后对分解后的信号进行能量计算,将问题量化,可以直观地观察信号的差异,最后提出判据。仿真验证证明,该方法能够正确区分TA饱和情况下的内外部故障电流,能及时阻止可能造成的损害,并可防止变压器保护误动。     

利用线路暂态行波功率方向的分布式母线保护

为避免电流互感器(TA)暂态饱和问题，提出了一种新型的分布式母线保护：基于小波变换识别各线路的暂态行波功率方向，然后比较所有线路的暂态行波功率方向来判别母线区内外故障。该母线保护可以利用已有的输电线行波方向保护而不需专用的母线保护设备，可以利用小波算法解决分布式结构中的同步问题，因而比常规分布式母线保护更易于实现和节省投资。理论分析和EMTP仿真试验表明：该母线保护动作快速可靠，基本不受故障类型、故障过渡电阻、故障距离和故障初始角的影响。     

A novel digital directional transformer protection technique based on wavelet packet

This paper presents a novel digital technique for transformer protection. The technique is based on deriving a directional quantity proportional to the fault current signal and the prefault voltage signal. Standard fast wavelet transform (FWT) schemes may not be as effective for data that has chiefly oscillatory features. An effective solution to discrimination involves examining the signal in both the time and frequency domains simultaneously. The wavelet packet transform is an extension of the FWT that allows for finer characterization of signal content for both time and frequency together. A 11/132-kV transformer connected to a 132-kV power system was simulated using Alternative Transient Program/Electromagnetic Transient Program (ATP/EMTP). Results indicate that the proposed technique is stable, reliable, and fast during the discrimination between internal and external faults, magnetizing inrush currents, and internal faults, ratio-mismatch, and saturation of current transformers (CTs).     

Applying wavelet entropy principle in fault classification

The ability to detect and classify the type of fault plays a great role in the protection of power system. This procedure is required to be precise with no time consumption. In this paper detection of fault type has been implemented using wavelet analysis together with wavelet entropy principle. The simulation of power system is carried out using PSCAD/EMTDC. Different types of faults were studied obtaining various current waveforms. These current waveforms were decomposed using wavelet analysis into different approximation and details. The wavelet entropies of such decompositions are analyzed reaching a successful methodology for fault classification. The suggested approach is tested using different fault types and proven successful identification for the type of fault.     

Transmission Line Boundary Protection Using Wavelet Transform and Neural Network

Two of the most expected objectives of transmission line protection are: 1) differentiating precisely the internal faults from external and 2) indicating exactly the fault type using one end data only. This paper proposes an improved solution based on wavelet transform and self-organized neural network. The measured voltage and current signals are preprocessed first and then decomposed using wavelet multiresolution analysis to obtain the high frequency details and low frequency approximations. The patterns formed based on high frequency signal components are arranged as inputs of neural network #1, whose task is to indicate whether the fault is internal or external. The patterns formed using low frequency approximations are arranged as inputs of neural network #2, whose task is to indicate the exact fault type. The new method uses both low and high frequency information of the fault signal to achieve an advanced line protection scheme. The proposed approach is verified using frequency-dependent transmission line model and the test results prove its enhanced performance. A discussion of the application issues for the proposed approach is provided at the end where the generality of the proposed approach and guidance for future study are pointed out     

基于小波分析的变压器转换性故障快速识别方法

当变压器发生区外故障时,会出现因电流传感器饱和而导致差动保护误动的问题。为解决这一问题,文中提出了基于小波分析的时差法,作为变压器差动保护判断区内、外故障的判据。首先,分析了电流互感器的饱和对变压器差动保护产生的影响;其次,利用模极大值原理研究了小波用于信号奇异性检测的方法,并选取合适的阈值规则对含噪声信号进行了消噪处理;然后,利用小波模极大值原理确定故障开始和差流出现的时刻;最后,提出了一种基于综合负序分量的变压器区外转区内故障时解除差动保护闭锁的新判据,并仿真验证了该方法的有效性。     

A Random Forest Classifier-based Digital Protection Scheme for Busbar

This paper presents a random forest (RF) classifier-based digital protection scheme which provides an effective discrimination between internal and external faults on a busbar. The measured current signals of all the bays (lines) connected to a busbar have been used as feature vectors. The system and fault parameters have been varied to generate a wide variety of simulation cases (33,600) consisting of both internal and external faults. By giving post-fault data of one cycle duration of all the bay currents as an input to the RF classifier, and taking only 30% of the total data (33,600) for training and remaining 70% of the total data for testing, an accuracy higher than 98% has been obtained. The PSCAD/EMTDC software package is used to model a prevailing 400-kV Indian busbar system for the purpose of authentication of the presented technique. The presented technique successfully differentiates between internal faults and external faults and remains unaffected against the change in system and fault parameters. In addition, the proposed scheme maintains stability under the Current Transformer saturation phenomena particularly during a heavy-through fault. A comparative analysis of the proposed scheme with the recently proposed scheme using support vector machine classifier clearly shows its superiority.     

利用电压相关性的±800kV直流输电线路区内外故障判断方法

对--800-kV直流输电线路区内及区外故障分量附加网络的理论分析表明,当直流输电线路发生区内故障时,于故障启动元件响应之后的短数据窗内,线路两侧电压电流故障分量均满足平波电感元件性能方程(voltage current relation,VCR);当发生区外故障时,故障侧的电压电流故障分量则不满足平波电感元件的VCR。为此,提出了基于实测电压与计算电压相关性的区内外故障判断方法:直流线路发生区内故障时,运用线路两侧实测电流由平波电感元件VCR分别计算两侧的电压,计算所得的电压波形与实测电压波形正相关,且数值很大;发生区外故障时,则故障侧计算所得的电压波形与实测电压波形负相关。据此,利用线路两侧计算的电压波形与实测电压波形的相关系数构造区内外故障识别判据。仿真结果表明,该识别算法可灵敏区识别内故障并可靠识别区外故障,可用于加速直流输电线路的后备保护动作。     

电流行波差动式母线保护的研究

为避免电流互感器暂态饱和的影响,研究了一种基于暂态电流行波的新型母线保护。在对母线上线路各相电流行波差动量的故障特征进行分析的基础上,为提高判别母线区内外故障的灵敏度,又引入各相电流行波的制动量,提出一种具有比率制动特性的电流行波差动式母线保护,及其基于小波变换的实用比率判据。理论分析和EMTP仿真表明该母线保护快速、灵敏、可靠,基本不受故障类型、故障过渡电阻、故障距离和故障初始角的影响。     

基于小波包和改进BP神经网络的变压器励磁涌流识别方法

根据励磁涌流和内部故障电流的波形特征存在巨大差异,提出一种基于小波包和改进BP网络的识别励磁涌流的新算法。利用小波包对励磁涌流和故障电流信号进行分解和重构,提取小波包重构系数,计算各频段的能量并进行归一化处理,构造能量特征向量,作为BP网络的输入样本,进行训练和测试,提出保护判据。经过PSCAD/EMTDC和MATLAB软件对大量样本进行仿真验证,证明该方案能够快速准确地识别励磁涌流和内部故障电流。     

基于R/S分析和小波变换的同步发电机定子绕组匝间短路故障分析

同步发电机定子绕组匝间短路故障是一种常见的、破坏性很强的故障,对发电机、电厂乃至电网的安全运行都将带来一系列严重的影响,有效的判断出该故障是否发生具有十分重要的意义.然而同步发电机定子绕组匝间短路故障识别一直是一个难点.本文尝试应用一种新的方法--R/S分析和小波变换对同步发电机定子内部绕组匝间短路故障进行分析.针对定子绕组内谮部匝间短路故障时引起相电压、相电流中谐波分量变化的特点,应用小波变换多分辨分析的特性,分析短路故障采样信号,并采用分形行几何中的重标度级差法分析计算相应尺度下的分形维数,提取匝间短路故障的特征量.该方法为同步发电机定子绕组匝间短路故障诊断提供了新的思路.     

一种快速识别故障发展的变压器差动保护解除闭锁新方法

TA饱和一直是影响变压器差动保护可靠性的重要原因。目前已有的比率制动特性和时差法等方法,在一定程度上提高了保护躲避区外故障的能力,但无法及时处理区外故障转区内故障的情况。通过分析发现:当外部故障且TA饱和时,绝大部分采样点在满足动作条件的情况下,其饱和TA的二次电流变化趋势与差流的变化趋势相反,而在内部故障情况下,上述规律则不满足。由此提出利用饱和二次电流和差流采样值变化轨迹,动态地定是否发生故障发展,有利于进一步提高差动保护的可靠性。仿真结果证实了所提方法的有效性。     

基于信息融合和神经网络的变压器内部故障快速诊断方法

变压器内部故障诊断通常需要利用油中溶解气体进行分析,但这些信息提取、检测分析过程繁琐,实时性较差。因此文章中提出了一种仅需要电气量的变压器内部故障快速诊断方法,采用小波包分析提取短路电流和差动电流的频域故障特征,采用最大值体现零序电流的故障特征,采用信息融合技术将所得到的所有故障特征进行融合,并利用BP神经网络算法对变压器内部电气故障类型进行诊断。在MATLAB/Simulink平台建立来仿真模型并进行了算例分析,结果表明文章中所提出的变压器内部电气故障诊断方法具有高准确性和高可靠性的优点。     

Fault line selection in cooperation with multi-mode grounding control for the floating nuclear power plant grid

The Floating nuclear power plant grid is composed of power generation, in-station power supply and external power delivery. To ensure the safety of the nuclear island, the in-station system adopts a special power supply mode, while the external power supply needs to be adapted to different types of external systems. Because of frequent single phase-ground faults and various fault forms, the fault line selection protection should be accurate, sensitive and adaptive. This paper presents a fault line selection method in cooperation with multi-mode grounding control. Based on the maximum united energy entropy ratio (MUEER), the optimal wavelet basis function and decomposition scale are adaptively chosen, while the fault line is selected by wavelet transform modulus maxima (WTMM). For high-impedance faults (HIFs), to enlarge the fault feature, the system grounding mode can be switched by the multi-mode grounding control. Based on the characteristic of HIFs, the fault line can be selected by comparing phase differences of zero-sequence current mutation and fault phase voltage mutation before and after the fault. Simulation results using MATLAB/Simulink show the effectiveness of the proposed method in solving the protection problems.