Remote monitoring system for real time detection and classification of transmission line faults in a power grid using PMU measurements

Remote monitoring of transmission lines of a power system is significant for improved reliability and stability during fault conditions and protection system breakdowns.This paper proposes a smart backup monitoring system for detecting and classifying the type of transmission line fault occurred in a power grid.In contradiction to conventional methods,transmission line fault occurred at any locality within power grid can be identified and classified using measurements from phasor measurement unit(PMU)at one of the generator buses.This minimal requirement makes the proposed methodology ideal for providing backup protection.Spectral analysis of equivalent power factor angle(EPFA)variation has been adopted for detecting the occurrence of fault that occurred anywhere in the grid.Classification of the type of fault occurred is achieved from the spectral coefficients with the aid of artificial intelligence.The proposed system can considerably assist system protection center(SPC)in fault localization and to restore the line at the earliest.Effectiveness of proposed system has been validated using case studies conducted on standard power system networks.

Data-driven Detection and Identification of Line Parameters with PMU and Unsynchronized SCADA Measurements in Distribution Grids

Line parameters play an important role in the control and management of distribution systems.Currently,phasor measurement unit(PMU)systems and supervisory control and data acquisition(SCADA)systems coexist in distribution systems.Unfortunately,SCADA and PMU measurements usually do not match each other,resulting in inaccurate detection and identification of line parameters based on measurements.To solve this problem,a data-driven method is proposed.SCADA measurements are taken as samples and PMU measurements as the population.A probability parameter identification index(PPII)is derived to detect the whole line parameter based on the probability density function(PDF)parameters of the measurements.For parameter identification,a power-loss PDF with the PMU time stamps and a power-loss chronological PDF are derived via kernel density estimation(KDE)and a conditional PDF.Then,the power-loss samples with the PMU time stamps and chronological correlations are generated by the two PDFs of the power loss via the Metropolis-Hastings(MH)algorithm.Finally,using the power-loss samples and PMU current measurements,the line parameters are identified using the total least squares(TLS)algorithm.Hardware simulations demonstrate the effectiveness of the proposed method for distribution network line parameter detection and identification.

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.

A Value-at-Risk Based Approach for PMU Placement in Distribution Systems

With the application of phasor measurement units(PMU)in the distribution system,it is expected that the performance of the distribution system state estimation can be improved obviously with the PMU measurements into consideration.How to appropriately place the PMUs in the distribution is therefore become an important issue due to the economical consideration.According to the concept of efficient frontier,a value-at-risk based approach is proposed to make optimal placement of PMU taking account of the uncertainty of measure errors,statistical characteristics of the pseudo measurements,and reliability of the measurement instrument.The reasonability and feasibility of the proposed model is illustrated with 12-node system and IEEE-33 node system.Simulation results indicated that uncertainties of measurement error and instrument fault result in more PMU to be installed,and measurement uncertainty is the main affect factor unless the fault rate of PMU is quite high.

Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data

This paper proposes an empirical wavelet transform(EWT)based method for identification and analysis of sub-synchronous oscillation(SSO)modes in the power system using phasor measurement unit(PMU)data.The phasors from PMUs are preprocessed to check for the presence of oscillations.If the presence is established,the signal is decomposed using EWT and the parameters of the mono-components are estimated through Yoshida algorithm.The superiority of the proposed method is tested using test signals with known parameters and simulated using actual SSO signals from the Hami Power Grid in Northwest China.Results show the effectiveness of the proposed EWT-Yoshida method in detecting the SSO and estimating its parameters.

Field PMU Test and Calibration Method——PartⅡ:Test Signal Identification Methods and Field Test Applications

Synchrophasor measurement units(PMUs)provide synchronized measurement data for wide-area applications.To improve the effectiveness of synchrophasor-based applications,field PMUs must be tested to ensure their performance and data quality.In the companion paper(Part I),we proposed a field PMU test and calibration framework consisting of a PMU calibrator and analysis center.Part I presents the development and test of the PMU calibrator.This paper focuses on the analysis center and field test applications.First,the critical component of the analysis center is the signal identification module,for which the step and oscillation signal identification methods are proposed.Here,the performance evaluation criteria of PMU in these two cases are different from others.The methods include a step signal detection method based on singular value decomposition(SVD),which has the capability of weak step detection to account for energy leakage of the signal during the step process,and an oscillation signal identification method based on SVD and fast Fourier transform,which can accurately extract oscillation components that benefit from the adaptive threshold setting method.Second,the analysis center software is implemented based on identification results.By integrating the PMU calibrator in Part I with the analysis center in Part II,we can examine in depth the field PMU test applications in three test scenarios,including standard,playback,and field signal test.Results demonstrate the effectiveness and applicability of the proposed field PMU test methods from both Parts I and II.

Synthetic PMU Data Creation Based on Generative Adversarial Network Under Time-varying Load Conditions

In this study,a machine learning based method is proposed for creating synthetic eventful phasor measurement unit(PMU)data under time-varying load conditions.The proposed method leverages generative adversarial networks to create quasi-steady states for the power system under slowly-varying load conditions and incorporates a framework of neural ordinary differential equations(ODEs)to capture the transient behaviors of the system during voltage oscillation events.A numerical example of a large power grid suggests that this method can create realistic synthetic eventful PMU voltage measurements based on the associated real PMU data without any knowledge of the underlying nonlinear dynamic equations.The results demonstrate that the synthetic voltage measurements have the key characteristics of real system behavior on distinct time scales.

Optimal Micro-PMU Placement for Improving State Estimation Accuracy via Mixed-integer Semidefinite Programming

Micro-phasor measurement units(μPMUs)with a micro-second resolution and milli-degree accuracy capability are expected to play an important role in improving the state estimation accuracy in the distribution network with increasing penetration of distributed generations.Therefore,this paper investigates the problem of how to place a limited number ofμPMUs to improve the state estimation accuracy.Combined with pseudo-measurements and supervisory control and data acquisition(SCADA)measurements,an optimalμPMU placement model is proposed based on a two-step state estimation method.The E-optimal experimental criterion is utilized to measure the state estimation accuracy.The nonlinear optimization problem is transformed into a mixed-integer semidefinite programming(MISDP)problem,whose optimal solution can be obtained by using the improved Benders decomposition method.Simulations on several systems are carried out to evaluate the effective performance of the proposed model.

An Adaptive Data-driven Method Based on Fuzzy Logic for Determining Power System Voltage Status

This paper proposes an adaptive method based on fuzzy logic that utilizes data from phasor measurement units(PMUs) to assess and classify generating-side voltage trajectories. The voltage variable and its associated derivatives are used as the input variables of a fuzzy-logic block. In addition, the voltage trajectory is compared with the pre-selected pilot-bus voltage to make a reliable decision about the voltage operational state. Different types of short-term voltage dynamics are considered in the proposed method. The fuzzy membership functions are determined using a systematic method that considers the current situation of the voltage trajectory. Finally, the voltage status is categorized into four classes to determine appropriate remedial actions. The proposed method is validated on a IEEE 73-bus power system in a MATLAB environment.

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.

Bad Data Detection Algorithm for PMU Based on Spectral Clustering

Phasor measurement units(PMUs) can provide real-time measurement data to construct the ubiquitous electric of the Internet of Things. However, due to complex factors on site, PMU data can be easily compromised by interference or synchronization jitter. It will lead to various levels of PMU data quality issues, which can directly affect the PMU-based application and even threaten the safety of power systems. In order to improve the PMU data quality, a data-driven PMU bad data detection algorithm based on spectral clustering using single PMU data is proposed in this paper. The proposed algorithm does not require the system topology and parameters. Firstly, a data identification method based on a decision tree is proposed to distinguish event data and bad data by using the slope feature of each data. Then, a bad data detection method based on spectral clustering is developed. By analyzing the weighted relationships among all the data, this method can detect the bad data with a small deviation. Simulations and results of field recording data test illustrate that this data-driven method can achieve bad data identification and detection effectively. This technique can improve PMU data quality to guarantee its applications in the power systems.

On-Line PMU-Based Transmission Line Parameter Identification

China Southern Power Grid Company(CSG)recently developed and implemented an online PMU-based transmission line(TL)parameter identification system(TPIS).Traditionally,TL parameters are calculated based on transmission tower geometries,conductor dimension,estimates of line length,conductor sags,etc.These parameters only approximate the effect of conductor sag and ignore the dependence of impedance parameters on temperature variation.Recent development in PMU technology has made it possible to calculate TL parameters accurately.The challenges are that such an application requires highly accurate PMU data while the accuracy of PMU measurements under different working/system conditions can be uncertain.With a large number of PMUs widely installed in its system,CSG plans to improve and update the EMS database using the newly developed TPIS.TPIS provides an innovative yet practical problem formulation and solution for TL parameter identification.In addition,it proposes a new metric that can be used to determine the credibility of the calculated parameters,which is missing in the literature.This paper discusses the methodologies,challenges,as well as implementation issues noticed during the development of TPIS.

High-accuracy and Low-complexity Phasor Estimation Method for PMU Calibration

Due to the increasing development of renewables in power systems,the requirements for phasor measurement units(PMUs)becomes higher.A PMU calibrator is an important tool to test and calibrate PMUs to ensure their measurement performance.This device can provide accurate reference values for error analysis of PMUs.In this paper,a phasor algorithm with low computational complexity and high accuracy is proposed for the PMU calibrator.This method reduces the processor requirements and development costs of the calibrator,thereby facilitating its popularization.At first,an enhanced discrete Fourier transform(DFT)method is put forward:1)the frequency response of the windowed DFT method is analyzed to reveal its large measurement errors under dynamic conditions;2)the parameter requirements of the DFT window that is regarded as a lowpass filter are analyzed,and thus a lowpass filter with better filtering performance is designed as the window coefficients to improve the estimation accuracy.Then,based on the enhanced DFT algorithm,a calibrator algorithm framework consisting of two-stage filters and a signal recognition module is established.This algorithm can consider the anti-interference ability and dynamic measurement accuracy at a low reporting rate.Simulation and experimental test results show that the proposed calibrator algorithm provides high-accuracy measurements of the static and dynamic signals with low computational complexity.

Risk assessment framework for power control systems with PMU-based intrusion response system

Cyber threats are serious concerns for power systems.For example,hackers may attack power control systems via interconnected enterprise networks.This paper proposes a risk assessment framework to enhance the resilience of power systems against cyber attacks.The duality element relative fuzzy evaluation method is employed to evaluate identified security vulnerabilities within cyber systems of power systems quantitatively.The attack graph is used to identify possible intrusion scenarios that exploit multiple vulnerabilities.An intrusion response system(IRS)is developed to monitor the impact of intrusion scenarios on power system dynamics in real time.IRS calculates the conditional Lyapunov exponents(CLEs)on line based on the phasor measurement unit data.Power system stability is predicted through the values of CLEs.Control actions based on CLEs will be suggested if power system instability is likely to happen.A generic wind farm control system is used for case study.The effectiveness of IRS is illustrated with the IEEE 39 bus system model.

Optimal placement of PMUs for the smart grid implementation in Indian power grid A case study

Efficient utilization of energy resources is essential for a developing country like India. The concept of smart grid （SG） can provide a highly reliable power system with optimized utilization of available resources. The present Indian power grid requires revolutionary changes to meet the growing demands and to make the grid smarter and reliable. One of the important requirements for SG is the instantaneous monitoring of the voltage, current and power flows at all buses in the grid. The traditional monitoring system cannot satisfy this requirement since they are based on nonlinear power flow equations. Synchro-phasor-measurement devices like phasor mea- surement units （PMUs） can measure the phasor values of voltages at installed buses. Consequently, the currents passing through all branches connected to that bus can be computed. Since the voltage phasor values at the neighboring buses of a bus containing the PMU can be estimated using Ohm＇s law, it is redundant to install PMUs at all the buses in a power grid for its complete observability. This paper proposes the optimal geographi- cal locations for the PMUs in southern region Indian power grid for the implementation of SG, using Integer Linear Programming. The proposed optimal geographical locations for PMU placement can be a stepping stone for the implementation of SG in India.

Multi-period Power System State Estimation with PMUs Under GPS Spoofing Attacks

This paper introduces a dynamic network model together with a phasor measurement unit(PMU)measurement model suitable for power system state estimation under spoofing attacks on the global positioning system(GPS)receivers of PMUs.The spoofing attacks may introduce time-varying phase offsets in the affected PMU measurements.An algorithm is developed to jointly estimate the state of the network,which amounts to the nodal voltages in rectangular coordinates,as well as the time-varying attacks.The algorithm features closedform updates.The effectiveness of the algorithm is verified on the standard IEEE transmission networks.It is numerically shown that the estimation performance is improved when the dynamic network model is accounted for compared with a previously reported static approach.

Field PMU Test and Calibration Method–Part I:General Framework and Algorithms for PMU Calibrator

Laboratory testing of phasor measurement units(PMUs)guarantees their performance under laboratory conditions.However,many factors may cause PMU measurement problems in actual power systems,resulting in the malfunction of PMU-based applications.Therefore,field PMUs need to be tested and calibrated to ensure their performance and data quality.In this paper(Part I),a general framework for the field PMU test and calibration in different scenarios is proposed.This framework consists of a PMU calibrator and an analysis center,where the PMU calibrator provides the reference values for PMU error analysis.Two steps are implemented to ensure the calibrator accuracy for complex field signals:①by analyzing the frequency-domain probability distribution of random noise,a Fourier-transform-based signal denoising method is proposed to improve the anti-interference capability of the PMU calibrator;and②a general synchrophasor estimation method based on complex bandpass filters is presented for accurate synchrophasor estimations in multiple scenarios.Simulation and experimental test results demonstrate that the PMU calibrator has a higher accuracy than that of other calibrator algorithms and is suitable for field PMU test.The analysis center for evaluating the performance of field PMUs and the applications of the proposed field PMU test system are provided in detail in Part II of the next-step research.

PMU based adaptive zone settings of distance relays for protection of multi-terminal transmission lines

This paper proposes Phasor Measurement Unit(PMU)based adaptive zone settings of distance relays(PAZSD)methodology for protection of multi-terminal transmission lines(MTL).The PAZSD methodology employs current coefficients to adjust the zone settings of the relays during infeed situation.These coefficients are calculated in phasor data concentrator(PDC)at system protection center(SPC)using the current phasors obtained from PMUs.The functioning of the distance relays during infeed condition with and without the proposed methodology has been illustrated through a four-bus model implemented in PSCAD/EMTDC environment.Further,the performance of the proposed methodology has been validated in real-time,on a laboratory prototype of Extra High Voltage multi-terminal transmission lines(EHV MTL).The phasors are estimated in PMUs using NI cRIO-9063 chassis embedded with data acquisition sensors in conjunction with LabVIEW software.The simulation and hardware results prove the efficacy of the proposed methodology in enhancing the performance and reliability of conventional distance protection system in real-time EHV MTLs.

Optimal redundant placement of PMUs in Indian power grid -- northern, eastern and north-eastern regions

Effective utilization of renewable energy sources and efficient management of electric energy are essential for any developing countries like India. This can be envisioned through the implementation of concepts of smart grid （SG）. One of the key requisites for SG implementation is that the grid should be completely observable. Renovation of conventional Indian power grid to a SG necessitates incorporation of the phasor measure- ment units （PMUs） in the present power grid measurement and monitoring system. Since the cost of PMU is high and any bus containing a PMU makes the neighboring connected buses observable, optimal placement of PMUs is very important for complete observability of the grid. This paper proposes optimal redundant geographical locations in the northern, eastern and north-eastern regions of Indian power grid for PMU placement. The PMUs installed in these geographical locations will make the grid completely observable and maintain the observability under the conditions of failure of some PMUs or branch outages. Integer linear programming has been used for finding the optimal PMU locations. The results proposed in this paper can be a stepping stone for revamping the Indian power grid to a SG ensuring complete observability during different contingency conditions.

Optimal Placement of Phasor Measurement Unit in Smart Grids Considering Multiple Constraints

The distribution of measurement noise is usually assumed to be Gaussian in the optimal phasor measurement unit(PMU)placement(OPP)problem.However,this is not always accurate in practice.This paper proposes a new OPP method for smart grids in which the effects of conventional measurements,limited channels of PMUs,zero-injection buses(ZIBs),single PMU loss contingency,state estimation error(SEE),and the maximum SEE variance(MSEEV)are considered.The SEE and MSEEV are both obtained using a robust t-distribution maximum likelihood estimator(MLE)because t-distribution is more flexible for modeling both Gaussian and non-Gaussian noises.The A-and G-optimal experimental criteria are utilized to form the SEE and MSEEV constraints.This allows the optimization problem to be converted into a linear objective function subject to linear matrix inequality observability constraints.The performance of the proposed OPP method is verified by the simulations of the IEEE 14-bus,30-bus,and 118-bus systems as well as the 211-bus practical distribution system in China.