High impedance fault detection implementation issues

Faults on distribution circuits are normally detected by simple overcurrent relays. Faults through a high impedance such as dry earth or asphalt do not have sufficient current to operate overcurrent relays and must be cleared manually. Such high impedance faults may pose a hazard to the public. Equipment is now commercially available to detect a high percentage of high impedance faults, but use of this equipment introduces operational issues which affect applications. This paper discusses technical as well as nontechnical issues associated with applying high impedance fault detectors. Recognizing all the issues is important to the effective implementation of these new fault detecting techniques     

High impedance fault detection device tester

High impedance or down conductor power system fault detection devices are now commercially available for evaluation. However, security and dependability of these devices can not be tested using conventional relay test apparatus and procedures. This paper presents a test apparatus and procedures for testing high impedance fault detection devices. The apparatus is capable of playing back, in real-time, waveforms selected from a data library, which includes seventy seven field recordings of high-impedance faults and feeder loads. Each recording is approximately five minutes long and stored in the form of digitized data sampled at 20 kHz     

High impedance fault detection in low voltage networks

High impedance faults are those with fault current magnitude similar to load currents. Experimental results were obtained that confirm operating experience that such faults can occur in the low voltage (600 V and below) underground distribution networks typically found in urban power systems. These faults produce current waveforms qualitatively similar to those found on overhead feeders, but quantitatively smaller. Loose connectors can produce similar, but cleaner current characteristics. Noisy loads remain a major impediment to reliable detection. Design and installation of an inexpensive prototype fault detector on the Seattle City Light street network is described     

High impedance fault detection methodology using wavelet transform and artificial neural networks

This paper presents a new technique based on the combination of wavelet transform (WT) and artificial neural networks (ANNs) for addressing the problem of high impedance faults (HIFs) detection in electrical distribution feeders. The change in phase current waveforms caused by faults and normal switching events has been used in this methodology. The discrete wavelet transform (DWT) used decomposes the time domain current signals into different harmonics in time-frequency domain and extracts special features to train ANNs. This preprocessing reduces the number of inputs to ANN and improves the training convergence. The ANN structure and learning algorithm used in this method is the multilayer perceptron network and Levenberg-Marquardt back-propagation algorithm, respectively.The signal data of several HIFs, low impedance faults (LIFs) and normal switching events have been obtained by the simulation of a real distribution network, with five feeders, under these different operations conditions, using SimPowerSystem Blockset of MATLAB. The results obtained have validated the effectiveness of the proposed methodology to detect HIFs and discriminate them from normal transient operations.     

High impedance fault detection based on wavelet transform and statistical pattern recognition

A novel method for high impedance fault (HIF) detection based on pattern recognition systems is presented in this paper. Using this method, HIFs can be discriminated from insulator leakage current (ILC) and transients such as capacitor switching, load switching (high/low voltage), ground fault, inrush current and no load line switching. Wavelet transform is used for the decomposition of signals and feature extraction, feature selection is done by principal component analysis and Bayes classifier is used for classification. HIF and ILC data was acquired from experimental tests and the data for transients was obtained by simulation using EMTP program. Results show that the proposed procedure is efficient in identifying HIFs from other events.     

Algorithm comparison for high impedance fault detection based onstaged fault test

Four high-impedance fault-detection algorithms-proportional relaying, ratio ground relaying, second-order harmonic current relaying, and third-order harmonic current relaying-were simulated by mathematical models. Relaying performances using staged fault data were then compared. Results of the fault data processing were used to distinguish the detection characteristics: fault identification, stability, threshold setting adaptability, transient recovery characteristic, and availability. The operations of a ground overcurrent relay and a ratio ground relay were also checked in the test. The results can be used as a reference for the development of a reliable high-impedance fault detector     

Adaptive Kalman filter and neural network based high impedance fault detection in power distribution networks

This paper presents an intelligent approach for high impedance fault (HIF) detection in power distribution feeders using combined Adaptive Extended Kalman Filter (AEKF) and probabilistic neural network (PNN). The AEKF is used to estimate the different harmonic components in HIF and NF (no-fault) current signals accurately under non-linear loading condition. The estimated harmonic components are used as features to train and test PNN for accurate classification of HIF from NF. Also a performance comparison is made between the results from feed forward neural network (FNN) and PNN for the same features extracted using AEKF. Thus a qualitative comparison is made for HIF detection and classification using the above techniques with FNN and PNN, separately. The testing results in noisy environment ensure the robustness of the proposed technique for HIF detection in distribution network.     

Decision tree-based methodology for high impedance fault detection

This paper presents a high impedance fault (HIF) detection method based on decision trees (DTs). The features of HIF, which are the inputs of DTs, are those well-known ones, including current [in root mean square (rms)], magnitudes of the second, third, and fifth harmonics, and the phase of the third harmonics. The only measurements needed in the proposed method are the current signals sampled at 1920 Hz. It will reduce the cost of hardware compared with methods that use high sampling rates. A new HIF model is also used. The data of current signals are from the simulation of Electromagnetic Transients Program (EMTP). The DT algorithm trained can successfully distinguish the HIFs from most normal operations on simulation data, including switching loads, switching shunt capacitors, and load transformer inrush currents. Testing on experimental data is recommended for future work.     

An adaptive high and low impedance fault detection method

An integrated high impedance fault (HIF) and low impedance fault (LIF) detection method is proposed in his paper. For a HIF detection, the proposed technique is based on a number of characteristics of the HIF current. These characteristics are: fault current magnitude; magnitude of the 3rd harmonic current; magnitude of the 5th harmonic current; the angle of the third harmonic current; the angle difference between the third harmonics current and the fundamental voltage; and the negative sequence current of HIF. These characteristics are identified by modeling the distribution feeders in EMTP. Apart from these characteristics, the above ambient (average) negative sequence current is also considered. An adjustable block out region around the average load current is provided. The average load current is calculated at every 18000 cycles (5 minutes) interval. This adaptive feature will not only make the proposed scheme more sensitive to low fault current, but it will also prevent the relay from tripping during the normal load current. In this paper, the logic circuit required for implementing the proposed HIF detection method is also included. With minimal modifications, the logic developed for the HIF detection can be applied to low impedance fault detection. A complete logic circuit which detects both the HIF and LIF is proposed. Using this combined logic, the need of installing separate devices for HIF and LIF detection can be eliminated     

基于遗传算法的高次谐波治理

电力电子装置的广泛应用以及大功率非线性冲击负荷的不断增加,在电力系统中产生了大量的谐波,引起了电力系统电压和电流的波形严重畸变,导致电力设备过热或损坏。通过装设滤波器和SVC等装置能得到解决。最近随着交-直-交变频传动轧机的出现,产生的35次、37次等高次谐波,影响了轧机生产线的运行,常规的设计及治理方法已很难满足电力系统运行要求。给出一种基于遗传算法的滤波器参数优化设计方法,不但解决了高次谐波问题,而且对无功功率的补偿效果也很好,整个装置的生产时间也比较短,成功的实践经验对于治理类似的工程问题也有较高的参考价值。     

A time-domain three-phase power system impedance modeling approachfor harmonic filter analysis

A time-domain method for impedance modeling of an unbalanced, three-phase power transmission and distribution network using three-phase measurements of bus voltage and injected current waveforms is presented. An impedance model seen at a bus where a harmonic filter is to be installed is calculated for each harmonic frequency, and the effect of placing the filter at the bus is then analyzed at these frequencies. As the configuration or operating condition of the power system varies, the estimated model changes accordingly, provided updated measurements are available. Hence, the effect of the harmonic filter under different system configurations or operating conditions is analyzed, and the information from this analysis is used for online harmonic filter control. Impedance models estimated by the proposed method are applied in filter design and performance analysis with actual recorded data, and the results are presented     

基于Web的多通道谐波监测及故障录波一体化系统

阐述了建立在工业控制计算机技术、网络管理技术、通信技术上的新一代多通道谐波检测及故障录波一体化装置的硬软件原理、主要功能及关键技术。详细介绍了基于Web管理的体系结构及其实现方法。     

基于变分模态分解与图信号指标的配电网高阻接地故障识别算法

为有效检测配电网高阻接地故障(HIF)的发生,本文结合变分模态分解与图信号指标,提出一种全新的HIF识别算法.首先,利用变分模态(VMD)分解得到故障暂态零序电流的多个本征模态分量;其次,根据峭度准则选取对故障暂态突变量最敏感的模态分量,进而计算该模态分量的图信号指标作为故障指标;最后,通过随机森林分类器对故障特征进行...     

Energy variance criterion and threshold tuning scheme for highimpedance fault detection

This paper presents a new approach to the detection of high impedance fault (HIF). The proposed approach (or detector which implements this approach) has four distinct features. First, the detector input signal is the three-phase unbalanced current (or feeder 3I₀), rather than the conventional three individual phase-currents. Secondly, the detector is designed by monitoring the energy variance for the second, fourth and sixth harmonics of 3I₀ individually, and by requiring the increment of randomness of all these harmonics to indicate an HIF. Thirdly, a self-tuning scheme based on the statistical confidence is applied to the automatic setting of threshold level for the energy variances monitored. Fourthly, effective counters are designed to detect both persistent and intermittent arcings. The detector has been tested on 51 stages faults and 8 unfaulted feeders. The test results show that the detector can have 100% faults detection rate so long as the arcing current at fault location is not less then 5 A. As to the dependability tests, no false alarm (or tripping) has happened for all of the unfaulted feeders under test. These feeders either supply special (including arc furnace) load, or have leakage current (referring to the intermittent zero-sequence load due to the feeder location along coast), or are under the normal capacitor or load switchings, and dependability and for the limitation of proposed fault detection method are presented     

Comparison of impedance based fault location methods for power distribution systems

Performance of 10 fault location methods for power distribution systems has been compared. The analyzed methods use only measurements of voltage and current at the substation. Fundamental component during pre-fault and fault are used in these methods to estimate the apparent impedance viewed from the measurement point. Deviation between pre-fault and fault impedance together with the system parameters are used to estimate the distance to the fault point.     

基于ELM的电力系统谐波阻抗估计

提出了一种基于极限学习机(ELM)的电力系统谐波阻抗估计方法,通过测量公共连接点处的谐波电压和谐波电流作为极限学习机的输入矢量,构造回归模型,进而估计出系统侧谐波阻抗。该方法与传统的二元线性回归方法相比,能够准确进行回归拟合。通过建立系统侧和用户侧的等值电路对该方法进行了仿真测试,并将估计结果与其他谐波阻抗估计方法进行了比较分析,验证了该方法的有效性。     

基于小波变换的电力系统谐波分析

电力系统的谐波是影响电能质量的重要因素,本文论述了基于小波变换的谐波检测方法,将含谐波的电信号进行基于多分辨思想的正交小波变换,解决了时频同时局部化的问题,并提出单子带重构算法,改善了Mallat算法中的频率折叠问题。由于小波分析在时、频域内良好的局部性,使之在谐波的跟踪检测、进而抑制谐波对电力系统的不良影响方面具有十分重要的意义。     

High voltage insulation for power cables utilizing high temperaturesuperconductivity

It is worth noting that, with a few exceptions, the efforts to develop dielectric systems, especially for the LTD superconducting cables, are lagging behind the intense efforts to develop more efficient HT superconducting materials, tapes, and conductors. The results presented here and reported in the literature confirm that lifetime is usually greater for cryogenic insulation, and thus the impulse and switching surge breakdown strengths may be a limiting factor in determining the operating stress of such insulation     

Analytical approach to internal fault simulation in power transformers based on fault-related incremental currents

A new method for simulating faulted transformers is presented in this paper. Unlike other methods proposed in the literature, this method uses the data obtained from any sound transformer simulation to obtain the damaged condition by simply adding a set of calculated currents. These currents are obtained from the definition of the fault. The model is fully based on determining the incremental values exhibited by the currents in phases and lines from the prefault to the postfault condition. As a consequence, data obtained from simulation of the sound transformer may be readily used to define the damaged condition. The model is described for light and severe faults, introducing this latter feature as a further add-on feature to the low-level faults simulation. The technique avoids the use of complex routines and procedures devoted to specially simulate the internal fault. Of prompt application to relay testing, the proposed analytical model also gives an insight into the fault nature by means of the investigation of symmetrical components. In contrast with its low complexity, the method has shown to present large accuracy for simulating the fault performance.     

基于Matlab的电力系统谐波电流实时检测方法仿真

讨论了2种基于瞬时无功功率理论的谐波电流检测方法,给出了检测系统的框图,并应用matlab仿真平台进行了仿真研究,给出了仿真波形,验证了该方法的正确性.