电力变压器励磁涌流和内部故障识别新方法

区分励磁涌流和内部故障时的短路电流,是变压器差动保护的难点技术之一,虽然目前已有多种方法,但每种方法都或多或少地存在着一些问题,空载合闸误动或内部故障时拒动(或延时动作)的情况还时有发生.在引入瞬时无功功率理论的基础上,提出了一种依据变压器两侧三相差瞬时有功功率和瞬时无功功率直流分量比值的变化关系来识别变压器励磁涌流和内部故障电流的新方法.该方法不仅简便易行,而且从平均有功和平均无功的关系出发,进一步揭示了变压器励磁涌流与内部故障本质上的不同.RTDS仿真实验结果表明:该方法简单可靠,识别效果显著.     

基于有功无功直流分量比值的变压器涌流新判据

针对变压器差动保护存在的区分励磁涌流和内部故障电流的难题,在引入瞬时无功功率理论的基础上,提出一种依据变压器各侧三相差有功功率和差无功功率直流分量比值的变化关系来识别变压器励磁涌流和内部故障电流的新方法.该方法原理简单,易于实现,具有数据采样方便、计算量小、动作可靠等特点.该方法从能量守恒的角度及有功功率和无功功率的关系出发,揭示了变压器励磁涌流和故障状态的本质不同.对变压器各种运行状态进行了实时数字仿真(RTDS)实验,仿真实验结果表明:该方法简单可靠,识别效果显著.     

基于变压器功率因数对励磁涌流和内部故障电流的识别

针对变压器采用纵差动保护会受到励磁涌流的影响而误动作,以及励磁涌流和内部故障时的短路电流的区分问题,提出一种根据变压器两侧三相瞬时功率因数的变化关系来识别励磁涌流和内部故障的方法.该方法简单、便捷,从能量的角度进一步揭示了变压器励磁涌流与内部故障电流本质不同.     

基于有功与无功相对大小的变压器励磁涌流鉴别新方法

提出了一种基于有功功率和无功功率相对大小特征的变压器励磁涌流鉴别新方法。分析了励磁涌流和内部故障情况下,有功和无功功率不同的变化趋势。当变压器空投于故障时,由于故障支路的存在,有功功率在一段时间内始终大于无功功率,而发生励磁涌流时,即使有功大于无功,持续时间也很短（非饱和阶段的时间3～5 ms）,这两种情况区别非常明显。利用这点不同构成判据,判断是否发生故障。该方法易于实现,计算量小,动作可靠、迅速。利用变压器各种运行状态的动模实验数据进行验证,结果表明该方法不受励磁涌流的影响且能够迅速、可靠地反映变压器内部故障,在性能上明显优于谐波制动判据。     

基于瞬时功率的变压器励磁涌流和内部故障电流识别新方法

在分析瞬时功率频谱特性的基础上，提出了一种基于瞬时功率的变压器励磁涌流和内部故障电流识别新方法。该方法主要依据变压器两侧三相差瞬时功率幅频特性中直流分量和基频分量的相对关系来识别变压器励磁涌流和内部故障电流。该方法具有传统变压器电流差动保护简便易行的特点，并从能量守恒的角度出发，进一步揭示了变压器励磁涌流与内部故障电流本质上的不同。HYBRISIM混合仿真实验结果表明该方法简单可靠、识别效果明显。     

一种鉴别变压器励磁涌流和内部故障的新原理

提出一种利用电流波形特征识别变压器励磁涌流和内部故障的方法,该方法综合利用变压器差电流波形在空投涌流时会呈现出尖顶波特性和间断特征,而故障时差电流波形基本为基频正弦波的差异,先计算差电流与其中所包含基频正弦波的相关度J,再进一步利用励磁涌流尖顶的凹弧特征构造一个系数k,根据J和k进一步构造一个函数J1区分变压器的励磁涌流和内部故障。动模试验结果表明该方法能够正确区分励磁涌流和故障电流,在空投变压器时能够可靠地闭锁励磁涌流;在变压器各种内部故障时能够可靠地开放保护,动作时间一般在20 m s左右,具有较高的灵敏度和可靠性能够满足现代变压器对保护动作可靠性的要求。而且该方法实现方便,计算量小,具有良好的在实际工程中应用的价值。     

一种鉴别变压器励磁涌流和内部故障的新原理

提出一种利用电流波形特征识别变压器励磁涌流和内部故障的方法,该方法综合利用变压器差电流波形在空投涌流时会呈现出尖顶波特性和间断特征,而故障时差电流波形基本为基频正弦波的差异,先计算差电流与其中所包含基频正弦波的相关度J,再进一步利用励磁涌流尖顶的凹弧特征构造一个系数k,根据J和k进一步构造一个函数J1区分变压器的励磁涌流和内部故障.动模试验结果表明该方法能够正确区分励磁涌流和故障电流,在空投变压器时能够可靠地闭锁励磁涌流;在变压器各种内部故障时能够可靠地开放保护,动作时间一般在20 ms左右,具有较高的灵敏度和可靠性能够满足现代变压器对保护动作可靠性的要求.而且该方法实现方便,计算量小,具有良好的在实际工程中应用的价值.     

正序有功功率差作为变压器励磁涌流判据的研究

针对当前变压器保护由于励磁涌流判据存在的某些方面的不足而出现的误动率相对较高的问题,提出应用正序有功功率差作为鉴别励磁涌流和故障电流的方法。推导该方法的动作判别式,并运用电力系统故障分析理论对该方法在励磁涌流和内部故障时的动作特性进行详细的分析,同时用EMPT仿真证明了该方法的有效性。     

基于拟合波形相关性的变压器励磁涌流识别新方法

为了提高变压器差动保护识别励磁涌流与内部故障电流的能力,提出一种基于拟合波形相关性的变压器励磁涌流识别新方法。首先利用正弦拟合法拟合差动电流波形,然后通过相关性分析原理,计算出差动电流原采样信号及其拟合曲线的相关系数,以此来识别励磁涌流与内部故障电流。仿真结果表明:该方法具有原理清晰、识别迅速、区分度高、抗干扰能力强,且易于在微机中实现等优点。     

正序有功功率差作为变压器励磁涌流判据的研究

针对当前变压器保护由于励磁涌流判据存在的某些方面的不足而出现的误动率相对较高的问题，提出应用正序有功功率差作为鉴别励磁涌流和故障电流的方法。推导该方法的动作判别式，并运用电力系统故障分析理论对该方法在励磁涌流和内部故障时的动作特性进行详细的分析，同时用EMPT仿真证明了该方法的有效性。     

A novel algorithm for discrimination between inrush current and internal faults in power transformer differential protection based on discrete wavelet transform

This paper proposes a novel methodology for transformer differential protection, based on wave shape recognition of the discriminating criterion extracted of the instantaneous differential currents. Discrete wavelet transform has been applied to the differential currents due to internal fault and inrush currents. The diagnosis criterion is based on median absolute deviation (MAD) of wavelet coefficients over a specified frequency band. The proposed algorithm is examined using various simulated inrush and internal fault current cases on a power transformer that has been modeled using electromagnetic transients program EMTDC software. Results of evaluation study show that, proposed wavelet based differential protection scheme can discriminate internal faults from inrush currents.     

三相变压器等效瞬时电感的计算分析及CT配置新方案

葛宝明等人以单相变压器模型为基础,提出一种利用等效瞬时电感变化特性判别变压器励磁涌流的算法,具有较好的识别效果。但对于三相变压器不同接线方式,尤其是YΔ/接线方式下等效瞬时电感的计算问题,目前还未见相关文献研究,该文对此问题进行了深入的分析和探讨,研究结果对利用等效瞬时电感变化特性判别变压器励磁涌流算法在工程中的应用,具有一定的指导意义和参考价值。针对变压器Δ侧绕组内部环流对等效瞬时电感计算结果影响大,而又难以通过线电流计算得到的特点,提出了一种新型的变压器差动保护CT配置方案。该方案保证了等效瞬时电感的正确计算,同时又不会使差动保护存在保护死区。     

A correlation based method for discrimination between inrush and short circuit currents in differential protection of power transformer using Discrete Wavelet Transform: Theory,simulation and experimental validation

This paper presents a new method for discrimination between magnetic inrush current and internal fault current in the differential protection of power transformer. The proposed method is based on the Wavelet Transform and correlation coefficient. In this study Discrete Wavelet Transform is used to describe the current signal in terms of different time and frequency components. In the proposed method, the energy signals of these components are employed. In the proposed method, a statistical parameter known as correlation coefficient is used to establish a criterion for the proposed discriminative algorithm. The correlation coefficient is used for express the relationship between wavelet coefficients energy at different scales of the signal resolution. Then pattern of these relations is utilized as a measure to discriminate the inrush current from fault current. For investigation the accuracy of the proposed algorithm different cases of inrush and internal fault currents is simulated by PSCAD/EMTDC software. Also, the proposed method is tested by the gathered data from experimental test at the laboratory. Current signals obtained from the simulation as well as the results obtained from the experimental test are employed by the proposed discriminative algorithm. Analysis of the simulation and experimental results show that the proposed method accurately identifies inrush and fault currents in the distance of the power transformer protection in a time period less than quarter of power frequency cycle. In addition to the sensitivity and high reliability, the proposed method has low computation work and does not required determining the threshold for each new power system.     

Decision Tree based discrimination between inrush currents and internal faults in power transformer

This paper presents a new approach for discriminating inrush currents from internal faults in case of power transformer protection using Decision Tree (DT). Differential current of one cycle inrush and internal faults are taken as inputs to the Decision Tree with corresponding target outputs as ‘0’ for inrush and ‘1’ for internal fault conditions. The DT is trained with inrush currents and internal faults with wide variations in operating parameters of the power network and provides accurate results in distinguishing inrush currents from internal faults. The proposed DT based algorithm is found to be accurate and robust, and thus highly suitable for power transformer protection.     

电力变压器励磁涌流判别的自适应小波神经网络方法

励磁涌流识别一直是电力变压器差动保护中比较关注的问题。文中提出了一种基于自适应小波神经网络实现变压器励磁涌流判别的新方法。结合励磁涌流和内部故障电流的特点，构建了一个四层的自适应小波神经网络模型，并对其具体的实现方法进行了详细的分析；利用ATP—EMTP程序进行仿真计算生成训练样本和测试样本，对所构建的网络进行了训练和测试，结果表明自适应小波神经网络能准确、可靠地识别出变压器的励磁涌流状态。     

用归一化等效瞬时电感分布特性识别励磁涌流的新算法

针对具有Y/△接线方式的三相变压器,提出了一种新的变压器差动保护TA配置方案：该方案是在传统变压器差动保护接线基础上,在变压器△侧接入一相绕组TA,然后与所测得的线电流结合,利用KCL定律可以容易地求解出△侧各相绕组电流.该方案既保证了等效瞬时电感的准确计算,使其不受△侧绕组内部环流的影响,又不会使差动保护存在＂死区＂.在此基础上,文中提出一种基于归一化等效瞬时电感分布特性的励磁涌流识别新算法：对等效瞬时电感进行归一化处理,使判据定值的选取更具有普遍性,与具体变压器参数、类型无关;利用分布特性更好地反映了等效瞬时电感的变化特征和规律.新算法识别灵敏可靠,HYBRISIM（Hybrid Simulator）实验数据也验证了新算法的准确性和有效性,其在超高压大容量变压器保护方面具有较好的工程应用前景.     

Transformer Differential Protection Using Principal Component Analysis

This paper describe a new algorithm for transformer differential protection, based on pattern recognition of the differential current obtained as the phasor sum of the current-transformer secondary currents. The algorithm uses principal component analysis to preprocess data from the power system in order to eliminate redundant information and enhance hidden pattern in differential current to discriminate between internal faults (transformer differential protection zone) from inrush and overexcitation conditions. The algorithm was proven using PSCAD/EMTDC simulations in a three-phase power system considering critical fault cases. The results show the feasibility to implement this algorithm for transformer differential protection.