A novel method for locating the source of sustained oscillation in power system using synchrophasors data

Large interconnected power systems are usually subjected to natural oscillation(NO)and forced oscillation(FO).NO occurs due to system transient response and is characterized by several oscillation modes,while FO occurs due to external perturbations driving generation sources.Compared to NO,FO is considered a more severe threat to the safe and reliable operation of power systems.Therefore,it is important to locate the source of FO so corrective actions can be taken to ensure stable power system operation.In this paper,a novel approach based on two-step signal processing is proposed to characterize FO in terms of its frequency components,duration,nature,and the location of the source.Data recorded by the Phasor Measurement Units(PMUs)in a Wide Area Monitoring System(WAMS)is utilized for analysis.As PMU data usually contains white noise and appears as multi-frequency oscillatory signal,the first step is to de-noise the raw PMU data by decomposing it into a series of intrinsic mode functions(IMF)using Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(ICEEMDAN)technique.The most appropriate IMF containing the vital information is selected using the correlation technique.The second step involves various signal processing and statistical analysis tools such as segmented Power Spectrum Density(PSD),excess kurtosis,cross PSD etc.to achieve the desired objectives.The analysis performed on the simulated two-area four-machine system,reduced WECC-179 bus 29 machine system,and the real-time power system PMU data set from ISO New England,demonstrates the accuracy of the proposed method.The proposed approach is independent of complex network topologies and their characteristics,and is also robust against measurement noise usually contained in PMU data.

Interharmonic Analysis Model of Photovoltaic Grid-connected System with Extended Dynamic Phasors

The interactions between randomly fluctuating power outputs from photovoltaic(PV) at the DC side and background voltage distortions at the AC side could generate interharmonics in the PV grid-connected system(PVGS). There is no universal method that can reveal the transmission mechanism of interharmonics and realize accurate calculation in different scenarios where interharmonics exist in the PVGS. Therefore, extended dynamic phasors(EDPs) and EDP sequence components(EDPSCs) are employed in the interharmonic analysis of the PVGS. First, the dynamic phasors(DPs) and dynamic phasor sequence components(DPSCs) are extended into EDPs and EDPSCs by selecting a suitable fundamental frequency other than the power frequency. Second, an interharmonic analysis model of the PVGS is formulated as a set of state space equations. Third, with the decoupling characteristics of EDPSCs,generation principles and interactions among the interharmonics in the PVGS are presented by the sequence components,and its correctness is verified by simulation and experiment.The presented model can be used to accurately calculate the interharmonics generated in the PVGS both at the AC and DC sides. Because of the decoupling among the EDPSCs, the set of state space equations can effectively describe the principle.

Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.

Multiplexed stimulated emission depletion nanoscopy(mSTED)for 5-color live-cell long-term imaging of organelle interactome

Stimulated emission depletion microscopy(STED)holds great potential in biological science applications,especially in studying nanoscale subcellular structures.However,multi-color STED imaging in live-cell remains challenging due to the limited excitation wavelengths and large amount of laser radiation.Here,we develop a multiplexed live-cell STED method to observe more structures simultaneously with limited photo-bleaching and photo-cytotoxicity.By separating live-cell fluorescent probes with similar spectral properties using phasor analysis,our method enables five-color live-cell STED imaging and reveals long-term interactions between different subcellular structures.The results here provide an avenue for understanding the complex and delicate interactome of subcellular structures in live-cell.

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.

基于改进的遗传–模拟退火算法和误差度分析原理的PMU多目标优化配置

为了进一步优化同步相量测量单元(phasor measurement unit,PMU)配置的合理性和效率,提出了一种新的误差度分析原理,并使用改进的遗传–模拟退火算法对多个IEEE标准测试系统进行了优化配置。该原理同时考虑了测量冗余度和状态估计的精度,并且避免引入雅可比矩阵,还具备可观测性分析的功能。研究结果表明:该算法不仅可以找到满足全网可观测性的所有PMU数目的配置解,而且进一步提升了全网的测量精度,从而证明了其有效性和优越性。

PalmPhasor算法性能的理论分析

模板的安全性和隐私性是掌纹系统实际应用的关键问题,然而生物特征保护的多项指标通常相互冲突并且难以同时满足.作为解决上述冲突的一种可撤销掌纹编码算法,Palm Phasor实现了高效、安全的掌纹认证.建立了系统分析Palm Phasor性能的完整框架.为了便于具体分析,将情景分为4种情况,并且提供了支持相应分析的预备知识,包括辅助定理以及Gabor滤波掌纹图像实部和虚部分布特性.在统计学基础上建立的理论分析和实验结果均表明:即使在用户口令被盗的情况下,多方向分数级融合增强的Palm Phasor算法也可以同时有效地满足可撤销生物特征的4项指标.

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.

基于同步量测信息的输电线路参数在线计算灵敏度分析

基于同步相量测量技术的PMU在电力系统中的应用为获取线路的在线运行参数提供了可能。测量现场复杂的电磁环境以及测量各环节的系统误差使测量数据不可避免地存在一定的偏差。基于π型等值电路,给出了利用线路两端同步电压和电流相量计算输电线路正序等值参数的方法。针对实测计算结果中电抗和电纳参数误差较小,而电阻误差很大的情况,采用灵敏度分析理论量化分析了同步相量测量偏差与参数计算结果误差之间的关系.对最终实现线路的所有参数在线测量以及提高参数精度具有一定的理论价值。

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.

GCN-LSTM spatiotemporal-network-based method for post-disturbance frequency prediction of power systems

Owing to the expansion of the grid interconnection scale,the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly important.These characteristics can provide effective support in coordinated security control.However,traditional model-based frequencyprediction methods cannot satisfactorily meet the requirements of online applications owing to the long calculation time and accurate power-system models.Therefore,this study presents a rolling frequency-prediction model based on a graph convolutional network(GCN)and a long short-term memory(LSTM)spatiotemporal network and named as STGCN-LSTM.In the proposed method,the measurement data from phasor measurement units after the occurrence of disturbances are used to construct the spatiotemporal input.An improved GCN embedded with topology information is used to extract the spatial features,while the LSTM network is used to extract the temporal features.The spatiotemporal-network-regression model is further trained,and asynchronous-frequency-sequence prediction is realized by utilizing the rolling update of measurement information.The proposed spatiotemporal-network-based prediction model can achieve accurate frequency prediction by considering the spatiotemporal distribution characteristics of the frequency response.The noise immunity and robustness of the proposed method are verified on the IEEE 39-bus and IEEE 118-bus systems.

A PAC Based Current Feedforward Control for Three-Phase PWM Voltage-Type Converter

This paper presents a novel current feedforward control strategy for a three-phase pulse-width modulation (PWM) DC voltage-type converter based on phase and amplitude control (PAC). With right-angle triangle relation of phasors and principle of conservation of energy, a phasor adjustment method and the relevant low-frequency mathematical model of the system are analyzed in detail, both in rectification and regeneration modes for the converter, are discussed. For improving the traditional PAC dynamic performance, variable load current is detected indirectly by the change of the DC voltage, which is fed to the control system as an additional control variable to generate modulation index and phase angle. Also, the algorithm is derived and the system principle is introduced. Experimental results from a 3 kw laboratory device are included to demonstrate the effectiveness of the proposed control strategy.

Fault Detection Based on Hierarchical Cluster Analysis in Wide Area Backup Protection System

In wide area backup protection of electric power systems, the prerequisite of protection device's accurate, fast and reliable performance is its corresponding fault type and fault location can be discriminated quickly and defined exactly. In our study, global information will be introduced into the backup protection system. By analyzing and computing real-time PMU measurements, basing on cluster analysis theory, we are using mainly hierarchical cluster analysis to search after the statistical laws of electrical quantities' marked changes. Then we carry out fast and exact detection of fault components and fault sections, and finally accomplish fault isolation. The facts show that the fault detection of fault component (fault section) can be performed successfully by hierarchical cluster analysis and calculation. The results of hierarchical cluster analysis are accurate and reliable, and the dendrograms of hierarchical cluster analysis are in intuition.

GPS Spoofing Attack Detection in Smart Grids Based on Improved CapsNet

This paper analyzes the influence of the global positionong system(GPS)spoofing attack(GSA)on phasor measurement units(PMU)measurements.We propose a detection method based on improved Capsule Neural Network(CapsNet)to handle this attack.In the improved CapsNet,the gated recurrent unit(GRU)is added to the front of the full connection layer of the CapsNet.The improved CapsNet trains and updates the network parameters according to the historical measurements of the smart grid.The detection method uses different structures to extract the temporal and spatial features of the measurements simultaneously,which can accurately distinguish the attacked data from the normal data,to improve the detection accuracy.Finally,simulation experiments are carried out on IEEE 14-,IEEE 118-bus systems.The experimental results show that compared with other detection methods,our method is proved to be more efficient.

A SVM Based Condition Monitoring of Transmission Line Insulators Using PMU for Smart Grid Environment

A new methodology for the detection and identification of insulator arc faults for the smart grid environment based on phasor angle measurements is presented in this study and the real time phase angle data are collected using Phasor Measurement Units (PMU). Detection of insulator arcing faults is based on feature extraction and frequency component analysis. The proposed methodology pertains to the identification of various stages of insulator arcing faults in transmission lines network based on leakage current, frequency characteristics and synchronous phasor measurements of voltage. The methodology is evaluated for IEEE 14 standard bus system by modeling the PMU and insulator arc faults using MATLAB/Simulink. The classification of insulator arcs is done using Support Vector Machine (SVM) technique to avoid empirical risk. The proposed methodology using phasor angle measurements employing PMU is used for fault detection/classification of insulator arcing which further helps in efficient protection of the system and its stable operation. In addition, the methodology is suitable for wide area condition monitoring of smart grid rather than end to end transmission lines.

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.

PMU Based Monitoring and Estimation of Inter-area Power Oscillation for Singapore-Malaysia Interconnection Power System

This paper proposes a PMU （phasor measurement unit） based monitoring and estimation scheme of power system small-signal stability in Singapore-Malaysia interconnection power system through a 50-Hz and 500 kV transmission line. Two PMUs are installed in the power system interconnection network of Singapore-Malaysia. One PMU is located in Singapore and the other one in Malaysia （Penang）. Both PMUs measure the single-phase voltage phasor. The data filtering technique based on FFT （Fast Fourier Transform） is employed to extract oscillation data for single mode. Finally, some analysis results of monitoring and estimation of Singapore-Malaysia interconnected power system based on application practice of the CampusWAMS are presented and analyzed.

直流换相失败对送端电网的影响分析

基于一次直流换相失败的PMU数据进行实例分析,并对故障进行了仿真,将仿真结果与PMU数据进行了对比,分析直流换相失败对送端电网的影响。此外,本文对云南电网异步运行后直流换相失败对送端电网的影响也进行了分析,与同步互联情况下进行了对比,并对异步联网下的稳定问题提出了相关建议。

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.

PHASE DIFFERENCE BETWEEN LOW-FREQUENCY OSCILLATIONS OF CEREBRAL DEOXY-AND OXY-HEMOGLOBIN CONCENTRATIONS DURING A MENTAL TASK

Hemodynamic low-frequency(~0.1 Hz)spontaneous oscillations as detected in the brain by nearinfrared spectroscopy have potential applications in the study of brain activation,cerebral autoregulation,and functional connectivity.In this work,we have investigated the phase lag between oscillations of cerebral deoxy-and oxy-hemoglobin concentrations in the frequency range 0.05-0.10 Hz in a human subject during a mental workload task.We have obtained a measure of such phase lag using two different methods:(1)phase synchronization analysis as used in the theory of chaotic oscillators and(2)a novel cross-correlation phasor approach.The two methods yielded comparable initial results of a larger phase lag between low-frequency oscillations of deoxy-and oxyhemoglobin concentrations during mental workload with respect to a control,rest condition.