Determination of Total Vector Error of the Phasor Measurement Unit (PMU) Using the Phase Angle Error of a Constant Amplitude Voltage Signal

This paper investigates the effect of the Phase Angle Error of a Constant Amplitude Voltage signal in determining the Total Vector Error (TVE) of the Phasor Measurement Unit (PMU) using MATLAB/Simulink. The phase angle error is measured as a function of time in microseconds at four points on the IEEE 14-bus system. When the 1 pps Global Positioning System (GPS) signal to the PMU is lost, sampling of voltage signals on the power grid is done at different rates as it is a function of time. The relationship between the PMU measured signal phase angle and the sampling rate is established by injecting a constant amplitude signal at two different points on the grid. In the simulation, 64 cycles per second is used as the reference while 24 cycles per second is used to represent the fault condition. Results show that a change in the sampling rate from 64 bps to 24 bps in the PMUs resulted in phase angle error in the voltage signals measured by the PMU at four VI Measurement points. The phase angle error measurement that was determined as a time function was used to determine the TVE. Results show that (TVE) was more than 1% in all the cases.

Subsynchronous oscillation monitoring and alarm method based on phasor measurements

Owing to the large-scale grid connection of new energy sources, several installed power electronic devices introduce sub-/supersynchronous inter-harmonics into power signals, resulting in the frequent occurrence of subsynchronous oscillations(SSOs). The SSOs may cause significant harm to generator sets and power systems;thus, online monitoring and accurate alarms for power systems are crucial for their safe and stable operation. Phasor measurement units(PMUs) can realize the dynamic real-time monitoring of power systems. Based on PMU phasor measurements, this study proposes a method for SSO online monitoring and alarm implementation for the main station of a PMU. First, fast Fourier transform frequency spectrum analysis is performed on PMU current phasor amplitude data to obtain subsynchronous frequency components. Second, the support vector machine learning algorithm is trained to obtain the amplitude threshold and subsequently filter out safe components and retain harmful ones. Finally, the adaptive duration threshold is determined according to frequency susceptibility, amplitude attenuation, and energy accumulation to decide whether to transmit an alarm signal. Experiments based on field data verify the effectiveness of the proposed method.

High Impedance Fault Detection of Distribution Network by Phasor Measurement Units

This paper proposes a new algorithm for High Impedance Fault (HIF) detection using Phasor Measurement Unit (PMU). This type of faults is difficult to detect by over current protection relays because of low fault current. In this paper, an index based on phasors change is proposed for HIF detection. The phasors are measured by PMU to obtain the square summation of errors. Two types of data are used for error calculation. The first one is sampled data and the second one is estimated data. But this index is not enough to declare presence of a HIF. Therefore another index introduces in order to distinguish the load switching from HIF. Second index utilizes 3rd harmonic current angle because this number of harmonic has a special behaviour during HIF. The verification of the proposed method is done by different simulation cases in EMTP/MATLAB.

Optimal Placement of Phasor Measurement Units Using a Modified Canonical Genetic Algorithm for Observability Analysis

This paper proposes a method for optimal placement of synchronized PMUs （phasor measurement units） in electrical power systems using a MCGA （modified canonical genetic algorithm）, which the goal is to determine the minimum number of PMUs, as well as the optimal location of these units to ensure the complete topological observability of the system. In case of more than one solution, a strategy of analysis of the design matrix rank is applied to determine the solution with the lower number of critical measurements. In the proposed method of placement, modifications are made in the crossover and mutation genetic operators, as well as in the formation of the subpopulation, and are considered restrictive hypotheses in the search space to improve the performance in solving the optimization problem. Simulations are performed using the IEEE 14-bus, IEEE 30-bus and New England 39-bus test systems. The proposed method is applied on the IEEE 118-bus test system considering the presence of observable zones formed by conventional measurements.

Estimation Method of Center of Inertia Frequency Based on Phasor Measurement Data

In the world, recent increased disturbances, congestion management problems, and increases of complexity in operating power systems have brought the need for integrations and improvements of power systems. Advanced applications in WAMPAC （wide area monitoring, protection, and control） systems provide a cost effective solution to improve system planning, operation, maintenance, and energy trading. Synchronized measurement technology and the application are an important element of WAMPAC. In addition, PMUs （phasor measurement units） are the most accurate and advanced time-synchronized technology available for WAMPAC application. Therefore, the original measurement system of PMUs has been constructed in Japan. This paper describes the estimation method of a center of inertia frequency by applying actual measurement data. The application of this method enables us to extract power system oscillations from measurement data appropriately. Moreover, this proposed method will help to the clarification of power system dynamics and this application will make it possible to realize the monitoring of power system oscillations associated with the power system stability.

Curvature Quantified Douglas-Peucker-based Phasor Measurement Unit Data Compression Method for Power System Situational Awareness

Facing constraints imposed by storage and bandwidth limitations,the vast volume of phasor meas-urement unit(PMU)data collected by the wide-area measurement system(WAMS)for power systems cannot be fully utilized.This limitation significantly hinders the effective deployment of situational awareness technologies for systematic applications.In this work,an effective curvature quantified Douglas-Peucker(CQDP)-based PMU data compression method is proposed for situational awareness of power systems.First,a curvature integrated distance(CID)for measuring the local flection and fluc-tuation of PMU signals is developed.The Doug-las-Peucker(DP)algorithm integrated with a quan-tile-based parameter adaptation scheme is then proposed to extract feature points for profiling the trends within the PMU signals.This allows adaptive adjustment of the al-gorithm parameters,so as to maintain the desired com-pression ratio and reconstruction accuracy as much as possible,irrespective of the power system dynamics.Fi-nally,case studies on the Western Electricity Coordinat-ing Council(WECC)179-bus system and the actual Guangdong power system are performed to verify the effectiveness of the proposed method.The simulation results show that the proposed method achieves stably higher compression ratio and reconstruction accuracy in both steady state and in transients of the power system,and alleviates the compression performance degradation problem faced by existing compression methods.Index Terms—Curvature quantified Douglas-Peucker,data compression,phasor measurement unit,power sys-tem situational awareness.

A Robust Asynchrophasor in PMU Using Second-Order Kalman Filter

Phasor Measurement Units(PMUs)provide Global Positioning System(GPS)time-stamped synchronized measurements of voltage and current with the phase angle of the system at certain points along with the grid system.Those synchronized data measurements are extracted in the form of amplitude and phase from various locations of the power grid to monitor and control the power system condition.A PMU device is a crucial part of the power equipment in terms of the cost and operative point of view.However,such ongoing development and improvement to PMUs’principal work are essential to the network operators to enhance the grid quality and the operating expenses.This paper introduces a proposed method that led to lowcost and less complex techniques to optimize the performance of PMU using Second-Order Kalman Filter.It is based on the Asyncrhophasor technique resulting in a phase error minimization when receiving the signal from an access point or from the main access point.The MATLAB model has been created to implement the proposed method in the presence of Gaussian and non-Gaussian.The results have shown the proposed method which is Second-Order Kalman Filter outperforms the existing model.The results were tested usingMean Square Error(MSE).The proposed Second-Order Kalman Filter method has been replaced with a synchronization unit into thePMUstructure to clarify the significance of the proposed new PMU.

Fault Characterization Based on Synchrophasor Data Using Heuristic Approach

With the advent of phasor measurement unit (PMU) technology, the grid observability has got a new dimension. This facet of technology helps in getting the real-time and dynamic scenario of the grid operations which was a remote possibility some decades before. Achieving this level of observability puts us at an advantage of responding to the system faults with reduced response time, and helps in restoring the grid stability within fraction of second. This paper demonstrates the detailed fault characterization from the PMU inputs, after illustrations from various real-time examples and different faults occurred in India. This paper tries to shed some light on areas where the accurate fault characterization can help the operator in taking the right decision for reliable grid operations.

融合多源量测数据的区间型抗差谐波状态估计

在相量测量单元(PMU)配置数量不足以满足谐波状态估计的可观性条件时,可将电能质量监测装置(PQMD)作为数据补充源。该文针对多源量测数据存在的同步性差异和量测偏差等问题,提出一种融合PMU与PQMD量测数据的区间型抗差谐波状态估计方法。首先,根据PQMD检测起始时刻不同步的特征,提出基于重叠度指标的PMU与PQMD量测数据融合方法;其次,采用量测变换从PQMD功率量测数据得到等效电流相量量测,构建区间型混合量测全集;再次,采用投影统计法和改进Huber权函数计算量测权重,对重叠度低且残差大的量测赋予较小的权重以抑制量测偏差的影响,并根据权重大小优选测点,得到非同步量测偏差最小的量测子集;最后,通过迭代重加权最小二乘法求解状态估计模型,在IEEE 30系统验证了该文所提方法的可行性与有效性。

基于相量测量单元优化配置的配电网谐波状态估计研究

随着大量电力电子设备的接入,配电网谐波问题愈发严重。谐波状态估计的准确性直接影响到后续的谐波治理效果。相量测量单元(phasor measurement unit,PMU)可以实时测量节点电压与支路电流,可借助其实现谐波状态估计。然而目前PMU价格较高,如何进行合理的优化配置保证全网谐波状态可观,同时提高谐波状态估计的准确性,是亟待解决的问题。首先构建以PMU经济配置和谐波状态估计精度最高为目标的PMU优化配置模型,并提出一种改进二进制粒子群-遗传混合算法用于求解。随后在实时仿真器中搭建IEEE14节点模型,选用均值插补法以及Vondrak滤波法进行数据处理并分析了优化所得多种PMU配置场景对谐波状态估计的影响。结果表明:所提算法从减少投资成本及降低谐波状态估计误差角度考虑,能够给出合理的PMU配置方案,有助于支撑工程决策。

基于HT-STWLS的配电网PMU设计

随着分布式能源和可调负荷大量接入配电网,其随机性和间歇性增加了配电网信号量测的难度,同时配电网存在节点分支类型变化多、通信条件受限等不确定因素,使相量量测单元(PMU)在配电网中应用受到限制。针对配电网节点多分支特点和量测估计高精度要求等问题,提出了基于HT-STWLS的新型配电网同步量测单元,并搭建了实验装置。首先,该装置采用多核分布式结构,通过网络路由模式,能够有效解决节点多分支量测问题,增强节点边缘计算能力;然后,对装置采集信号进行希尔伯特变换(HT)处理后,将数据代入到对称泰勒加权最小二乘(STWLS)过程中进行信号参数估计,获取高精度基波参数值;最后,通过算法验证和实际电网信号的测试,表明所提装置的HT-STWLS算法能够实现配电网信号参数的高精度估计。

考虑相量量测单元数据不同步的双端输电线路正序以及零序参数辨识方法

针对相量量测单元(phasormeasurementunit,PMU)数据不同步导致参数辨识结果误差大的问题,提出了考虑PMU数据不同步的输电线路正序以及零序参数辨识方法。首先,分析线路集中参数模型和分布参数模型在一定电压等级下的长度适用范围。基于线路的集中参数模型,利用正常运行情况下PMU装置获取的线路两端功率以及电压信息,构建以正序参数和不同步角度为未知量的非线性方程,并运用Levenberg-Marquardt(L-M)算法求解正序参数以及不同步角度。其次,在辨识出正序参数以及不同步角度的基础上,分析单相接地故障情况下的正序、负序以及零序等效电路图,通过正序和负序网络求解出故障距离。在故障距离已知的情况下,基于零序网络构建以零序参数为未知量的方程,并利用L-M算法求解方程。最后,利用MATLAB软件搭建单回双端输电线路系统,并对所提正序以及零序参数辨识方法进行仿真,验证了所提参数辨识方法的有效性和精确性。

一种基于圆周运动轨迹方程的电力系统基波频率测量方法

随着新能源的大规模接入,系统惯量降低,电力系统的频率波动变得剧烈,增加了频率准确测量的难度,而频率的测量精度直接关系着电力系统各类基于频率控制应用的有效性。因此,该文从圆周运动角度,提出了一种新颖的频率精确测量方法。该方法建立了电力系统电压信号正弦变化的旋转相量圆周运动表征模型,基于匀速圆周运动和变速圆周运动的轨迹运动方程,推导了旋转相量及其导数与系统频率之间的函数关系;利用二次多项式拟合电压信号动态变化的幅值和相角,提出了基于最小二乘法的旋转相量及其导数求解方法,进一步,提出了基于频率网格化的迭代优化方法,消除了频率偏移对算法的影响。仿真和硬件测试表明,所提算法在频率偏移、线性和非线性变化条件下均能准确地测量基波频率。

低压配电网用户相位识别方法研究

配电网由于负荷不均衡,会产生三相不平衡现象。该文提出一种用户相位识别和三相电流相位不平衡检测方法。该方法能够有效辨识同一台区下的用户相位,为用电信息采集和台区治理提供数据基础。考虑到电力信号的动态特性,首先借助泰勒级数来近似表示信号的时变相量;其次联立窗内每个数据点对应的关系方程,并通过最小二乘法求解出泰勒系数,得到精准的相量测量值,然后对用户与变压器处的相位分别进行相移与相位补偿;最后通过比较两者的相位差与所设阈值之间的关系实现用户相位归属关系识别。完成用户的相位识别之后,通过变压器低压侧三相电流的相位差值可判断配电网三相电流相位的不平衡情况,为配电网三相不平衡时的换相、电网重构等措施提供监测分析数据。仿真结果表明,文章所提方法在频率偏移条件下,可以实现台区用户相位的准确识别,而在谐波干扰条件下,识别成功率均高于90%。相比于传统的用户与变压器电压相关性分析方法,所提方法识别精度和鲁棒性均得到较大提升。

考虑PMU数据质量问题的电力系统扰动检测方法

快速准确的电力系统扰动检测能够为后续扰动分析提供有效的指导信息,而广域测量系统(wide area measurement system,WAMS)的广泛应用为扰动检测提供了有力的数据基础。基于PMU量测数据,该文提出一种考虑PMU不良数据的扰动事件检测方法。首先分析PMU异常数据行为特性,揭示扰动事件与不良数据的差异性特征。进一步,提出一种基于差分Teager-Kaiser能量算子与3Sigma准则相结合的PMU异常数据初筛方法,避免了低强度扰动漏检和扰动的重复检测问题。接着,利用动态时间规整和最大互信息系数分别计算不同PMU间的时空相似性,以及同一台PMU内不同量测间的相关性,并以此作为表征扰动事件和不良数据差异的特征。最后,通过局部离群概率算法对得到的综合度量指标进行分析,可实现在含有不良数据场景下的扰动事件准确检测。基于IEEE39系统,实际电网模型以及PMU实测数据,验证所提方法具有较好准确性、实时性以及泛化能力。

Phasor measurement units, WAMS, and their applications in protection and control of power systems

The paper provides a short history of the phasor measurement unit(PMU) concept. The origin of PMU is traced to the work on developing computer based distance relay using symmetrical component theory. PMUs evolved from a portion of this relay architecture. The need for synchronization using global positioning system(GPS) is discussed, and the wide area measurement system(WAMS) utilizing PMU signals is described. A number of applications of this technology are discussed, and an account of WAMS activities in many countries around the world are provided.

Impacts of subsynchronous and supersynchronous frequency components on synchrophasor measurements

Phasor measurement units(PMU) are playing an increasingly important role in power system dynamic security monitoring and control. However, the wide-area deployments of the renewable energy sources and the high voltage direct current(HVDC) transmission bring a large number of inter-harmonics to the power grid, which may result in further power system security problems. The impacts of inter-harmonics on synchrophasor measurements are revealed. This paper derives the phasor expressions of the signal, which contains the fundamental component and the inter-harmonics. It is found that the inter-harmonics will lead to the subsynchronous oscillation of the phasor measurements. The frequency transmutation principle between the harmonic and the phasor oscillation is revealed. Then, the field PMU data recorded during a subsynchronous oscillation, which occurred in an area of China with a high concentration of wind farms and HVDC transmission lines, are studied. A geographical wiring diagram with the subsynchronous oscillation distribution depicts the severe consequences of the inter-harmonics. In addition, the correctness of the theoretical derivation and the possibility of the inter-harmonics monitoring are verified.

基于二阶罚函数自适应变阶拟合的全局电网惯量时空感知

随着传统同步发电机逐步被新能源发电替代,电力系统惯量不断降低,惯量时空评估对保障系统安全稳定运行愈加重要。首先,提出了基于二阶罚函数自适应变阶拟合的全局电网惯量时空感知方法;其次,基于同步相量测量单元(PMU)准确估测系统各空间节点的频率变化率及功率变化,采用二阶罚函数对PMU监测数据进行预处理,并对每段拟合数据的处理过程加以自适应变阶拟合;最后,通过两种方法的结合,可实现对电力系统广义节点惯量的时空感知。通过仿真案例分析,验证了所提方法在大、小扰动工况下对惯量时空评估的准确性及适用性。

基于有限个μPMU和压缩感知理论的主动配电网复故障定位方法

主动配电网(Active distribution network,ADN)动态行为相较传统电网更为复杂,亟需解决其故障检测和定位问题。针对配电网系统中微型同步相量测量装置(Micro phasor measurement unit,μPMU)的运用,提出基于有限个μPMU的复故障定位策略。首先,根据任意线路故障下全网可观的μPMU优化配置方案建立短路、断线故障线路等效模型,通过分析模型将电流故障分量等效至相邻两端节点形成虚拟注入电流向量。其次,利用压缩感知理论求解故障网络节点电压方程,根据重构电流向量中非零元素的位置得到可疑故障节点,并基于可疑故障节点及μPMU配置位置划分动态候选故障域。最后,先分别构建短路、断线区域判据,确定故障区间,再进一步根据区域两端推算电压构造线路判据,精确判断故障线路及类型。基于改进的IEEE 33节点配电网系统进行仿真分析,仿真结果表明,基于有限个μPMU的复故障定位策略是可行的,该策略能够有效判断故障的精确位置。

基于PMU梯度动态偏差的新型电力系统快速稳定性

在能源转型和科技进步双重推动下,高比例可再生能源和高比例电力电子设备正成为电力系统发展重要趋势和关键特征.新型电力系统动态行为随之发生重大变化,传统小干扰稳定性分析方法满足使用需要,在应对运行工况快速变化场合时尚存在亟需解决问题.提出基于同步相量测量装置(PMU)数据梯度动态偏差李雅普诺夫直接分析法对新型电力系统小干扰稳定性进行分析,利用PMU数据矩阵降维得到低维矩阵,代入含双馈异步风力发电机组的电力系统矩阵模型,求解李雅普诺夫方程式得到对角矩阵,通过判定矩阵正定性对系统稳定性作出判断.利用求解后得到的对角矩阵计算相应状态变量动态偏差值,对相应状态变量曲线使用梯度下降法迭代计算该曲线极值点数值,时间加权计算整个振荡过程时间加权动态偏差量,为阻尼稳定控制器配置位置提供指导.利用含风力发电新英格兰10机39节点系统仿真验证方法可以达到改善系统小干扰稳定性以及对新型电力系统快速稳定性分析的有效性.