基于零序阻抗模型故障特征的含分布式电源配电网故障区间定位方法

电力系统配电网的故障区间定位是故障精确测距的基础,其研究对尽快恢复供电及减少停电经济损失具有重要作用。分布式电源(DG)的引入增加了故障区间定位的难度,为此提出一种基于电源端测量数据的含DG配电网故障区间定位新算法。该方法在含DG配电网零序阻抗模型的基础上,根据故障点的故障特征搜索故障支路关联节点,定位故障区间。算例仿真结果表明所提出方法具有区间定位准确度高、鲁棒性强和计算速度快的优点。     

A Fault Location Scheme for Active Untransposed Distribution Systems Using a Limited Number of Synchronized Measurements

Abstract

This paper presents a fault location scheme for unbalanced and untransposed distribution systems which contain different types of distributed generation (DG). A general formula has been derived for any fault type using a limited number of synchronized measurement points. To avoid having to synchronize all the measurement points, the voltage and current measured locally at the DGs are processed locally to calculate the equivalent impedance of the DG at the non-fundamental frequencies. This is then used in the fault location process. The IEEE 34-bus feeder is simulated using the distributed parameter model for the lines and is used to validate the proposed scheme. Uncertainties associated with fault type, fault location, fault resistance, inception angle, noise in measurements and load profile are considered in the evaluation. The simulation studies demonstrate that the scheme can have a high accuracy and is robust.     

Fault location in active distribution networks using non-synchronized measurements

Fault location is a necessity to realize the self-healing concept of modern distribution networks. This paper presents a novel fault location method for distribution networks with distributed generation (DG) using measurements recorded at the main substation and at the DG terminals. The proposed method is based on an iterative load flow algorithm, which considers the synchronization angle as an unknown variable to be estimated. Therefore, it obviates the need of synchronized measurements. A new fault location equation is also proposed which is valid for all different fault types, hence the fault type information is not required. The developed method can be simply implemented by minor modifications in any distribution load flow algorithm and it is applicable to different distribution network configurations. The accuracy of the method is verified by simulation studies on a practical 98-node test feeder with several DG units.     

基于广义S变换的有源配电网故障定位方法

有源配电网中,DG中性点接地方式的不同选择将对原有故障电气量造成不同影响.从小电流接地系统与DG中性点接地方式安全配合的角度分析可知,DG采用中性点不接地方式最佳,并由此得出了其暂态零序电流不受DG接入影响的结论.在此基础上,针对故障信息利用不充分且单一判据存在定位盲区的问题,提出一种基于广义S变换多维判据的故障定位方法,对暂态零序电流信号进行广义S变换处理,不仅利用其幅值矩阵故障信息提取了主谐振频率和暂态能量特征量,还提出利用常被忽略的相角矩阵构造了统计极性特征量,构建了完备的多维故障区段判据.通过依次比较两检测点任一故障特征量,差异较大则判定为故障区段.理论分析与仿真验证表明该方法能够有效、准确地定位故障区段,且具有较强的适用性.     

A single ended directional fault section identifier and fault locator for double circuit transmission lines using combined wavelet and ANN approach

Fault section identification and determining its location are important aspects to reduce down/repair time, speed up restoration of power supply and to improve the reliability. In this paper combined wavelet and artificial neural network based directional protection scheme is proposed for double circuit transmission lines using single end data to identify the faulty section and its location with reach setting up to 99% of line length. The proposed method requires the three phase currents and voltage to be measured at one end of the double circuit transmission line modelled using distributed parameter line model which also considers the effect of shunt capacitance. Approximate coefficients feature vector of the three phase voltage and current are extracted using discrete wavelet transform to train the ANN with Levenberg Marquardt algorithm. The proposed scheme involves two stages. The first stage identifies the zone/section of the fault and the second stage calculates the fault location from the relaying point. The proposed combined Wavelet and ANN based fault location scheme is also compared with ANFIS based fault location scheme. The test results of the proposed scheme show that the fault section identification and location estimation is very accurate and the average percentage error in fault location estimation is within 0.001%. This method is adaptive to the variation of fault type (both forward and reverse), fault inception angle, fault location and fault resistance. The main advantage of the proposed scheme is that it offers primary protection to 99% of line length using single end data only and also backup protection to the adjacent forward and reverse line sections.     

基于PQMS电压信息的有源配电网故障定位方法

通过建立逆变型分布式电源(Inverter Interfaced Distributed Generation,IIDG)在低电压穿越控制下的(Low Voltage Ride Through,LVRT)故障输出模型,利用电能质量检测装置(PQMS)的电压信息,建立故障定位评估函数,提出了一种含逆变型DG配电网的故障定位新方法。论文首先研究了逆变型DG的低压穿越控制策略,建立逆变型DG的故障特征模型,分析对称及非对称故障条件下输出特性。然后利用含逆变型DG的配电网模型,分析不同故障条件下的故障特征。通过分析故障分量网络,建立节点电压关于故障距离与过渡电阻的方程,通过改进的粒子群算法求解精确故障距离。该方法考虑了故障条件下DG输出特性对于配电网故障定位的影响,利用故障网络的节点电压分布函数,解决了低电压穿越运行下的逆变型DG有源配电网故障定位问题。最后,在DigSilent软件中构建了带有逆变型DG的IEEE 33配电网仿真系统,验证所提方法的有效性与准确性。     

基于DOST能量相似度的有源配电网故障区间定位方法

有源配电网小电流接地系统发生单相接地短路时,通过理论分析得出单个DG接入配电网并不影响零序电流大小的结论,由此提出一种基于离散正交S变换(DOST)暂态零序电流能量相似度的故障定位方法。首先对线路上检测设备上传的暂态零序电流信号进行离散正交S变换,然后利用得到的时频矩阵中的元素计算线路区间两端检测点的能量相似度,能量相似度小于设定的阈值即为故障区间。MATLAB/Simulink仿真结果表明该方法准确有效,适用于有源配电网的故障区间定位。     

基于分层定位模型的含DG配电网故障定位方法研究

针对现有配电网故障定位算法在含DG的故障定位中存在耗时长、准确率低等问题,提出了一种将分层模型与改进免疫算法相结合用于含DG的配电网故障定位方法。简化配电网模型,使用改进的免疫算法定位故障区域,并使用改进的免疫算法对故障区域进行二次定位。通过试验对单点故障和多点故障进行分析,验证了所提方法的优越性。试验结果表明,相比于传统的故障定位方法,所提方法引入了分层理论,有效降低了故障节点的搜索维数,在保证速度的情况下,具有较高的故障定位精度。     

基于雷电记录与行波数据的雷击故障测距结果优化方法

针对雷击故障参考点定位不准确,导致测距结果可能与雷击故障发生的实际距离相差较大的问题,结合雷电记录与行波数据,从雷击故障参考点定位角度着手,进行雷击故障测距结果优化研究。首先获取相关雷电记录和行波数据,然后计算待分析故障特征点,并利用雷击故障历史数据、非雷击故障历史数据、雷电定位系统历史数据,构建(Δx,Δt,ΔP)三维坐标系,划分雷击故障识别域和非雷击故障识别域,判断待分析故障特征点是否落入雷击故障识别域当中,确定雷击故障参考点,最后利用行波测距方法得出雷击故障精确位置。结果表明,与基于雷电记录或基于行波数据的2种单一测距方法相比,该方法测距结果更接近实际值,由此可知,雷击故障测距结果得到优化,提高了测距精度。     

基于电流序分量的多源配电网故障定位方法

为了克服传统配电网故障定位方法对分布式电源(Distribution Generation,DG)接入的适应性较差的问题,且需要在馈线中配置大量测量装置导致成本增加的缺点,提出了一种基于电流序分量相关系数的多源配电网故障区段定位方法。首先利用叠加法分析了多端电源配电网故障点电流特征及定位原理,然后通过电源端口测量装置获取故障前后电源输出电流幅值差,再假设不同位置发生故障并计算此时各电源输出故障电流理论值,最后利用相关分析法计算理论与实测两组数据的相关系数,并提取相关系数最大的两个相邻节点实现区段定位。通过ETAP电力系统仿真平台搭建了改进的IEEE33节点模型模拟测量值,利用MATLAB编程进行相关分析,结果验证了方法的正确性。     

Non-linear representation of voltage sag profiles for fault location in distribution networks

Fault location for distribution networks with multiple laterals would requires additional information such as from fault indicators and protective devices. As SCADA systems to provide such information are limited in 11 kV or lower voltage distribution networks, effective fault location method that only use information from a measurement at primary substation is needed. This paper presents the application of calculated non-linear voltage sag profiles and voltage sag measurement at primary substation to locate a fault in distribution networks. The proposed method firstly identifies the faulted section. From the indentified section, fault distance is calculated. The method has been tested under different fault scenarios that include various fault resistance, loading variation and data measurement errors. The results indicate the possibility of using this method to support automatic fault management system.     

基于神经网络建模的零序直流原理测距研究

针对电力电缆铺设隐蔽,发生故障时不易准确定位故障点的问题,研究了零序直流保护原理和人工神经网络技术在小电流接地系统单相接地故障测距中的应用。利用直流信号不受电网电容影响的特性,建立检测源与接地网电路模型。根据电路模型,建立其数学模型,由于模型中的一些参数复杂,则考虑采用神经网络对其未知量进行辨识,并将辨识好的数学模型应用于故障测距中。根据实验数据,对两种模型进行分析,结果表明利用神经网络辨识参数的方法能够准确、可靠地实现故障测距。     

An alternative approach to fault location on power distribution feeders with embedded remote-end power generation using artificial neural networks

In this paper, the design and implementation of a feed-forward artificial neural network (ANN)-based fault locator to classify and locate shunt faults on primary overhead power distribution lines with load taps and embedded remote-end power generation is presented. In the ANN algorithm, the standard back-propagation technique with a sigmoid activation function is used. The fault locator utilizes fault voltage and current samples obtained at a single location of a typical radial distribution system. The ANNs are trained with data under a wide variety of fault conditions and used for the fault type classification and fault location on the distribution line. A 34.5?kV distribution system is simulated using electro-magnetic transients program and their results are used to train and test the ANNs. The ANN-based fault locator gives high accuracy for the vast majority of the practically encountered systems and fault conditions, including the presence of load taps and the remote-end in-feed source.     

分布式发电条件下的多电源故障区域定位新方法

根据分布式发电条件下的配电网网络结构和故障电流的变化特点,提出了一种新型多电源故障区域定位方法。该方案利用配电网的特定母线节点,进行分支电流综合幅值比较以判定故障搜索的正方向,并最终把故障范围锁定在一个最小的故障关联区域内。这一方案具有集中式保护与分布式处理相结合的特点,首先由智能电子终端(IED)对广域范围内的故障信息进行分布处理,然后由保护装置对相关故障信息进行综合处理并完成故障隔离。文章对故障搜索的电流幅值判据进行了详细论证,并提出了其矩阵算法,该算法对DG投退造成的网络结构的随机变化具有自适应性,对IED故障具备一定的容错能力,满足DG接入对配电网保护提出的要求。分布式处理降低了保护对通信系统的要求,同时,由于仅利用电流量进行故障搜索判定,工程上较容易实现。文章以实例对该故障区域定位方法进行了仿真,证明了方案的正确性。     

基于状态估计残差比较的配电网故障区段定位方法

针对单端量测的阻抗法在多分支辐射状网络中会出现伪故障点的问题,利用网络中分布的智能量测设备提供的监测信息,提出了基于状态估计残差比较的配电网故障区段定位方法。该方法首先遍历所有节点通过添加故障支路建立不同节点故障网络下的状态方程;其次通过求解状态估计方程获得含网络所有节点的总残差检测值序列;然后搜寻最大残差检测值所在节点判断故障节点位置;最后根据节点相邻区间首末端阻抗角相位变化差异判定故障区间。大量仿真表明,该方法在不同故障类型、过渡电阻等工况下均具有良好的故障定位效果。该方法考虑了量测产生的随机变量成分,利用测量数据的互补性和多源性,在一定程度上提高了不同量测数据误差的抗干扰能力,极大地缩小了配电网在有限量测条件下的故障查找范围。     

基于正序电压差的含分布式电源配电网断线接地复合故障定位方法

分布式电源(distributed generation, DG)大量应用给电网故障识别与定位提出了更高要求。配电网断线故障时绝缘虽未遭到破坏,但可能导致DG故障穿越,甚至诱发并网逆变器闭锁,造成电气量越限,威胁电网稳定运行。为此,提出了一种利用正序电压差实现含DG配电网的断线接地复合故障定位方法。通过解析不同故障情况下配电网馈线序电流和DG并网点电压,发现了非故障点两端正序电压差等于线路压降,而断口两端正序电压差恒为正数且多大于非故障区段压差的特征,构造了基于正序电压差的故障定位判据。针对定位判据可能出现的死区问题,引入DG输出电流作为辅助判据提高定位可靠性,进而提出了含DG配电网的断线接地复合故障定位方法。理论分析和仿真结果表明,所提方法能够实现不同DG容量、故障位置下的断线接地复合故障区段准确定位,且具有较强的耐过渡电阻能力。     

Best ANN structures for fault location in single-and double-circuit transmission lines

The great development in computing power has allowed the implementation of artificial neural networks (ANNs) in the most diverse fields of technology. This paper shows how diverse ANN structures can be applied to the processes of fault classification and fault location in overhead two-terminal transmission lines, with single and double circuit. The existence of a large group of valid ANN structures guarantees the applicability of ANNs in the fault classification and location processes. The selection of the best ANN structures for each process has been carried out by means of a software tool called SARENEUR.     

基于模型识别的有源配电网单相接地故障定位方法

分布式电源(distributed generation, DG)大量接入使配电网继电保护面临严峻挑战。单相接地故障发生概率大,但故障信息十分微弱,特别是在DG多样化故障输出特性的影响下,有源配电网单相故障定位的准确性常难以保证。为此,提出了一种基于模型识别的有源配电网单相接地故障定位方法。分析了配电网单相接地故障下DG的输出特性,建立了在不同故障位置下有源配电网的正序增广网络,构建了故障位置关于馈线出口以及DG输出电流的函数,建立了配电网单相接地故障位置模型,利用不同故障位置下短路电流矢量占比系数的差异性构建了新的故障定位判据。通过将单相接地故障定位问题转化为故障位置模型系数的求解问题,提高了故障定位的准确性和实用性。理论和仿真分析表明,在不同故障位置、不同过渡电阻下均能准确定位单相接地故障,具有原理清晰、故障特征量采集便捷、灵敏性和可靠性高的优点。     

计及DG出力相关性的孤岛微电网蒙特卡洛法概率潮流

孤岛微电网缺乏主网的支撑,分布式电源(distributed generator,DG)出力的随机性以及负荷的波动性都将对系统频率及电压造成影响。为准确分析孤岛模式下微电网的运行状态,提出一种计及DG出力相关性的孤岛微电网概率潮流计算方法。首先简化孤岛微电网节点分类,将潮流方程表达成统一形式;其次,在考虑DG出力的相关性下运用蒙特卡洛法进行抽样计算,从而获得概率潮流结果;最终以Benchmark 0.4 kV低压微电网系统作为算例,验证了文中方法的有效性。     

遗传神经网络的瞬变电磁视电阻率求解算法

提出用遗传神经网络求解中心回线装置下瞬变电磁法(TEM)的视电阻率。根据中心回线方式的瞬变电磁响应关系式,设计出神经网络的输入输出关系和单输入单输出的三层网络结构。计算出神经网络的输入输出样本集,并通过尝试法确定隐含层的神经元个数。引入遗传算法优化神经网络结构的连接权值,得到了最优连接权值的GABP神经网络。用该神经网络对瞬变电磁响应的非线性方程进行拟合,得到以实测数据计算的核函数值所一一对应的瞬变场参数值,达到求视电阻率并成像的目的。通过对地下高阻块状异常体模型和电力系统钢制扁钢材料的接地网模型两个实例模型的仿真计算证明,得到视电阻率断面图,达到了求解反问题的效果。理论模型与实际数据计算表明,遗传优化的BP神经网络使得瞬变电磁视电阻率的计算时间大大缩短,是个实用的算法。该方法为瞬变电磁接地网故障实时诊断平台提供必要的技术基础。