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 wa...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.展开更多
With the increased number of PMUs in the power grid, effective high speed, realtime methods to ascertain relevant data for situational awareness are needed. Several techniques have used data from PMUs in conjunction w...With the increased number of PMUs in the power grid, effective high speed, realtime methods to ascertain relevant data for situational awareness are needed. Several techniques have used data from PMUs in conjunction with state estimation to assess system stability and event detection. However, these techniques require system topology and a large computational time. This paper presents a novel approach that uses real-time PMU data streams without the need of system connectivity or additional state estimation. The new development is based on the approximation of the eigenvalues related to the decoupled discreet-time power flow Jacobian matrix using direct openPDC data in real-time. Results are compared with other methods, such as Prony’s method, which can be too slow to handle big data. The newly developed Discreet-Time Jacobian Eigenvalue Approximation (DDJEA) method not only proves its accuracy, but also shows its effectiveness with minimal computational time: an essential element when considering situational awareness.展开更多
In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incide...In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incident.This paper presents a Hankel dynamic mode decomposition(DMD)method to identify SSR parameters using synchrophasor data.The basic idea is to employ the DMD technique to explore the subspace of Hankel matrices constructed by synchrophasors.It is analytically demonstrated that the subspace of these Hankel matrices is a combination of fundamental and SSR modes.Therefore,the SSR parameters can be calculated once the modal parameter is extracted.Compared with the existing method,the presented work has better dynamic performances as it requires much less data.Thus,it is more suitable for practical cases in which the SSR characteristics are timevarying.The effectiveness and superiority of the proposed method have been verified by both simulations and field data.展开更多
This paper proposes an extension of the algorithm in [1], as well as utilization of the wavelet transform in event detection, including High Impedance Fault (HIF). Techniques to analyze the abundant data of PMUs quick...This paper proposes an extension of the algorithm in [1], as well as utilization of the wavelet transform in event detection, including High Impedance Fault (HIF). Techniques to analyze the abundant data of PMUs quickly and effectively are paramount to increasing response time to events and unstable parameters. With the amount of data PMUs output, unstable parameters, tie line oscillations, and HIFs are often overlooked in the bulk of the data. This paper explores model-free techniques to attain stability information and determine events in real-time. When full system connectivity is unknown, many traditional methods requiring other bus measurements can be impossible or computationally extensive to apply. The traditional method of interest is analyzing the power flow Jacobian for singularities and system weak points, attained by applying singular value decomposition. This paper further develops upon the approach in [1] to expand the Discrete-Time Jacobian Eigenvalue Approximation (DDJEA), giving values to significant off-diagonal terms while establishing a generalized connectivity between correlated buses. Statistical linear models are applied over large data sets to prove significance to each term. Then the off diagonal terms are given time-varying weights to account for changes in topology or sensitivity to events using a reduced system model. The results of this novel method are compared to the present errors of the previous publication in order to quantify the degree of improvement that this novel method imposes. The effective bus eigenvalues are briefly compared to Prony analysis to check similarities. An additional application for biorthogonal wavelets is also introduced to detect event types, including the HIF, for PMU data.展开更多
Synchrophasor devices guarantee situation awareness for real-time monitoring and operational visibility of smart grid. With their widespread implementation,significant challenges have emerged, especially in communicat...Synchrophasor devices guarantee situation awareness for real-time monitoring and operational visibility of smart grid. With their widespread implementation,significant challenges have emerged, especially in communication, data quality and cybersecurity. The existing literature treats these challenges as separate problems,when in reality, they have a complex interplay. This paper conducts a comprehensive review of quality and cybersecurity challenges for synchrophasors, and identifies the interdependencies between them. It also summarizes different methods used to evaluate the dependency and surveys how quality checking methods can be used to detect potential cyberattacks.展开更多
Synchrophasor systems, providing low-latency,high-precision, and time-synchronized measurements to enhance power grid performances, are deployed globally.However, the synchrophasor system as a physical network,involve...Synchrophasor systems, providing low-latency,high-precision, and time-synchronized measurements to enhance power grid performances, are deployed globally.However, the synchrophasor system as a physical network,involves communication constraints and data quality issues, which will impact or even disable certain synchrophasor applications. This work investigates the data quality issue for synchrophasor applications. In Part I, the standards of synchrophasor systems and the classifications and data quality requirements of synchrophasor applications are reviewed. Also, the actual events of synchronization signal accuracy, synchrophasor data loss, and latency are counted and analyzed. The review and statistics are expected to provide an overall picture of data accuracy,loss, and latency issues for synchrophasor applications.展开更多
This work investigates the data quality issue for synchrophasor applications, and pays particular attention to synchronization signal loss and synchrophasor data loss events. First, the historical synchronization sign...This work investigates the data quality issue for synchrophasor applications, and pays particular attention to synchronization signal loss and synchrophasor data loss events. First, the historical synchronization signal loss events are analyzed and the potential reasons and solutions are discussed. Then, the scenario of a small amount of synchrophasor data loss is studied and a Lagrange interpolating polynomial method is used to adaptively estimate the incomplete and missing data. The performance of proposed method is demonstrated with simulation results.Specifically, the proposed method considers the trade-off between the estimation accuracy and the hardware cost,and could be efficiently employed in reality.展开更多
By maliciously manipulating the synchrophasors produced by phasor measurement units in power systems,cyber attackers can mislead the control center into taking wrong actions.From the viewpoint of machine learning,norm...By maliciously manipulating the synchrophasors produced by phasor measurement units in power systems,cyber attackers can mislead the control center into taking wrong actions.From the viewpoint of machine learning,normal and malicious synchrophasors may exhibit different spatial distribution characteristics when mapped into a latent space.Hence,a malicious synchrophasor detector can be acquired by training a classification model with instances derived from historical operational synchrophasor data.However,malicious synchrophasors occur infrequently in practice.It is likely to incur a great deal of effort and may even introduce inevitable experience errors when extracting and labeling a sufficient number of malicious synchrophasors from historical operational data for training.For most existing detectors,if they are directly trained with highly imbalanced datasets,their performances may severely deteriorate.In this paper,a novel type of malicious synchrophasor detector is developed based on a combinatorial use of data rebalancing,Bagging-based ensemble learning,and the widely recognized eXtreme Gradient Boosting(XGBoost)classifier.Experiments show that although fewer malicious instances are provided,the proposed detector is still capable of detecting malicious synchrophasors.展开更多
Synchrophasors are time-synchronized electrical measurements that represent both the magnitude and phase angle of the electrical sinusoids. Synchrophasors are measured by fast time-stamped devices called phasor measur...Synchrophasors are time-synchronized electrical measurements that represent both the magnitude and phase angle of the electrical sinusoids. Synchrophasors are measured by fast time-stamped devices called phasor measurement units(PMUs) to constitute the basis of realtime monitoring and control actions in the electric grid.Due to its enhanced situational awareness capabilities,many applications of PMUs are presented in the literature in the past decades. This paper presents a comprehensive summary of synchrophasor technology, its architecture,optimal placement techniques and its applications in electric power transmission and distribution systems. These applications include wide-area situational awareness and monitoring, state estimation, fault location and protective relaying, islanding detection etc. This review also covers some of the existing challenges in its implementation and its potential applications.展开更多
The subsynchronous oscillations(SSOs)related to renewable generation seriously affect the stability and safety of the power systems.To realize the dynamic monitoring of SSOs by utilizing the high computational efficie...The subsynchronous oscillations(SSOs)related to renewable generation seriously affect the stability and safety of the power systems.To realize the dynamic monitoring of SSOs by utilizing the high computational efficiency and noise-resilient features of the matrix pencil method(MPM),this paper propos es an improved MPM-based parameter identification with syn chrophasors.The MPM is enhanced by the angular frequency fitting equations based on the characteristic polynomial coeffi cients of the matrix pencil to ensure the accuracy of the identi fied parameters,since the existing eigenvalue solution of the MPM ignores the angular frequency conjugation constraints of the two fundamental modes and two oscillation modes.Then,the identification and recovery of bad data are proposed by uti lizing the difference in temporal continuity of the synchropha sors before and after noise reduction.The proposed parameter identification is verified with synthetic,simulated,and actual measured phase measurement unit(PMU)data.Compared with the existing MPM,the improved MPM achieves better accuracy for parameter identification of each component in SSOs,better real-time performance,and significantly reduces the effect of bad data.展开更多
Wide-area monitoring systems(WAMS)are becoming increasingly vital for enhancing power grid operators’situational awareness capabilities.As a pilot WAMS that was initially deployed in 2003,the frequency monitoring net...Wide-area monitoring systems(WAMS)are becoming increasingly vital for enhancing power grid operators’situational awareness capabilities.As a pilot WAMS that was initially deployed in 2003,the frequency monitoring network FNET/GridEye uses GPS-time-synchronized monitors called frequency disturbance recorders(FDRs)to capture dynamic grid behaviors.Over the past ten years,a large number of publications related to FNET/GridEye have been reported.In this paper,the most recent developments of FNET/GridEye sensors,data centers,and data analytics applications are reviewed.These works demonstrate that FNET/GridEye will become a costeffective situational awareness tool for the future smart grid.展开更多
State estimation is a critical functionality of energy management system(EMS) to provide power system states in real-time operations. However, problems such as failure to converge, prone to failure during contingencie...State estimation is a critical functionality of energy management system(EMS) to provide power system states in real-time operations. However, problems such as failure to converge, prone to failure during contingencies,and biased estimates while system is under stressed condition occur so that state estimation results may not be reliable.The unreliable results further impact downstream network and market applications, such as contingency analysis,voltage stability analysis, transient stability analysis, system alarming, and unit commitment. Thus, operators may lose the awareness of system condition in EMS. This paper proposes a fully independent and one-of-a-kind system by integrating linear state estimator into situational awareness applications based on real-time synchrophasor data. With guaranteed and accurate state estimation solution and advanced real-time data analytic and monitoring functionalities, the system is capable of assisting operators to assess and diagnose current system conditions for proactive and necessary corrective actions. The architecture, building components, and implementation of the proposed system are explored in detail. Two case studies with simulated data from the subsystems of Electric Reliability Council of Texas(ERCOT) and Los Angeles Department of Water and Power(LADWP) are presented. The test results show the effectiveness and reliability of the system, and its value for realtime power system operations.展开更多
Increasing power demand,penetration of renew-ables,and limitations of necessary grid expansion are proffering new challenges to existing power system protection and control strategies.However,with the advancement in i...Increasing power demand,penetration of renew-ables,and limitations of necessary grid expansion are proffering new challenges to existing power system protection and control strategies.However,with the advancement in intelligent elec-tronic devices and relaying technology,fast,accurate and reliable protection schemes can be developed for smart power systems.In this paper,a new protection scheme based on admittance and power change has been proposed with dual-use line relays to detect symmetrical/asymmetrical faults in power systems.A large number of fault environments have been simulated by varying fault distances from relay location,fault resistance,and power angle in single machine infinite bus and WSCC 9-bus systems.Some crucial decisive fault scenarios e.g.close in/far end faults,faults in series compensated line,faults during asymmetrical swings,switching ON/OFF large loads,single and multi-modal swings have also been verified for the proposed index.In this paper,for the first time,detection of faults during power swings have been examined and verified in the presence of wind farms.The simulation results show the proficiency of the proposed algorithm for detecting faults in the presence or absence of power swings.展开更多
The present-day power system is a complex network that caters to the demands of several applications with diverse energy requirements.Such a complex network is susceptible to faults caused due to several reasons such ...The present-day power system is a complex network that caters to the demands of several applications with diverse energy requirements.Such a complex network is susceptible to faults caused due to several reasons such as the failure of the equipment,hostile weather conditions,etc.These faults if not detected in the real-time may lead to cascading failures resulting in a blackout.These blackouts have catastrophic consequences which result in a huge loss of resources.For example,a blackout in 2004 caused an economic loss of 10 billion U.S dollars as per the report of the Electricity Consumers Resource Council.Subsequent investigation of the blackout revealed that the catastrophe could have been prevented if there was an early warning system.Similar other blackouts across the globe forced the power system engineers to devise an effective solution for real-time monitoring and control of the power system.The consequence of these efforts is the wide area measurement system(WAMS).The WAMS consists of several sensors known as the phasor measurement units(PMUs)that collect the real information pertaining to the health of the power grid.This information in the form time synchronized voltage and current phasors is communicated to the central control center or the phasor data concentrator(PDC)where the data is analyzed for detection of power system anomalies.The communication of the synchrophasor data from each PMU to the PDC constitutes the synchrophasor communication system(SPCS).Thus,the SPCS can be considered as the edifice of the WAMS and its reliable operation is essential for the effective monitoring and control of the power system.This paper presents a comprehensive review of the various synchrophasor communication technologies,communication standards and applications.It also identifies the existing knowledge gaps and the scope for future research work.展开更多
Synchrophasor measurements are essential to realtime situational awareness of the smart grid but vulnerable to cyber-attacks during the process of transmission and invocation.To ensure data security and mitigate the i...Synchrophasor measurements are essential to realtime situational awareness of the smart grid but vulnerable to cyber-attacks during the process of transmission and invocation.To ensure data security and mitigate the impact of spoofed synchrophasor measurements,this work proposes a novel object detection method using a Weight-based One-dimensional Convolutional Segmentation Network(WOCSN)with the ability of attack behavior identification and time localization.In WOCSN,automatic data feature extraction can be achieved by onedimensional convolution from the input signal,thereby reducing the impact of handcrafted features.A weight loss function is designed to distribute the contribution for normal and attack signals.Then,attack time is located via the proposed binary method based on pixel segmentation.Furthermore,the actual synchrophasor data collected from four locations are used for the performance evaluation of the WOCSN.Finally,combined with designed evaluation metrics,the time localization ability of WOCSN is validated in the scenarios of composite attacks with different spoofed intensities and time-sensitivities.展开更多
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...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.展开更多
Simultaneous human activities,such as the Super Bowl game,would cause certain impacts on frequency fluctuations in power systems.With the help of FNET/GridEye measurements,this paper aims to give comprehensive analyse...Simultaneous human activities,such as the Super Bowl game,would cause certain impacts on frequency fluctuations in power systems.With the help of FNET/GridEye measurements,this paper aims to give comprehensive analyses on the frequency fluctuations during Super Bowl LIV held on Feb.2,2020,so as to better understand several phenomena caused by simultaneous activities which will help system operations and controls.First,recent developments of the FNET/GridEye are briefly introduced.Second,the frequency fluctuations of the Eastern Interconnection(El),western electricity coordinating council(WECC),and electric reliability council of Texas(ERCOT)power systems during Super Bowl LIV are analyzed.Third,frequency fluctuations of Super Bowl Sunday and ordinary Sundays in 2020 are compared.Finally,the differences of frequency fluctuations among different years during the Super Bowl and their change trends are also given.Furthermore,several possible explanations,including the simultaneity of electricity consumption at the beginning of commercial breaks and the halftime show,the increasing usage of the Internet,and the increasing size of TV screens,are illustrated in detail in this paper.展开更多
High-precision synchronized measurement data with short measurement latency are required for the applications of phasor measurement units(PMUs).This paper proposes a synchrophasor measurement method based on cascaded ...High-precision synchronized measurement data with short measurement latency are required for the applications of phasor measurement units(PMUs).This paper proposes a synchrophasor measurement method based on cascaded infinite impulse response(IIR)and dual finite impulse response(FIR)filters,meeting the M-class and P-class requirements in the IEC/IEEE 60255-118-1 standard.A low-group-delay IIR filter is designed to remove out-of-band interference components.Two FIR filters with different center frequencies are designed to filter out the fundamental negative frequency component and obtain synchrophasor estimates.The ratio of the amplitudes of the synchrophasor is used to calculate the frequency according to the one-to-one correspondence between the ratio of the amplitude frequency response of the FIR filters and the frequency.To shorten the response time introduced by IIR filter,a step identification and processing method based on the rate of change of frequency(RoCoF)is proposed and analyzed.The synchrophasor is accurately compensated based on the frequency and the frequency response of the IIR and FIR filters,achieving high-precision synchrophasor and frequency estimates with short measurement latency.Simulation and experiment tests demonstrate that the proposed method is superior to existing methods and can provide synchronized measurement data for M-class PMU applications with short measurement latency.展开更多
文摘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.
文摘With the increased number of PMUs in the power grid, effective high speed, realtime methods to ascertain relevant data for situational awareness are needed. Several techniques have used data from PMUs in conjunction with state estimation to assess system stability and event detection. However, these techniques require system topology and a large computational time. This paper presents a novel approach that uses real-time PMU data streams without the need of system connectivity or additional state estimation. The new development is based on the approximation of the eigenvalues related to the decoupled discreet-time power flow Jacobian matrix using direct openPDC data in real-time. Results are compared with other methods, such as Prony’s method, which can be too slow to handle big data. The newly developed Discreet-Time Jacobian Eigenvalue Approximation (DDJEA) method not only proves its accuracy, but also shows its effectiveness with minimal computational time: an essential element when considering situational awareness.
基金supported by the China Key Technology Research on Risk Perception of Sub-Synchronous Oscillation of Grid with Large-Scale New Energy Access SGTYHT/21-JS-223.
文摘In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incident.This paper presents a Hankel dynamic mode decomposition(DMD)method to identify SSR parameters using synchrophasor data.The basic idea is to employ the DMD technique to explore the subspace of Hankel matrices constructed by synchrophasors.It is analytically demonstrated that the subspace of these Hankel matrices is a combination of fundamental and SSR modes.Therefore,the SSR parameters can be calculated once the modal parameter is extracted.Compared with the existing method,the presented work has better dynamic performances as it requires much less data.Thus,it is more suitable for practical cases in which the SSR characteristics are timevarying.The effectiveness and superiority of the proposed method have been verified by both simulations and field data.
文摘This paper proposes an extension of the algorithm in [1], as well as utilization of the wavelet transform in event detection, including High Impedance Fault (HIF). Techniques to analyze the abundant data of PMUs quickly and effectively are paramount to increasing response time to events and unstable parameters. With the amount of data PMUs output, unstable parameters, tie line oscillations, and HIFs are often overlooked in the bulk of the data. This paper explores model-free techniques to attain stability information and determine events in real-time. When full system connectivity is unknown, many traditional methods requiring other bus measurements can be impossible or computationally extensive to apply. The traditional method of interest is analyzing the power flow Jacobian for singularities and system weak points, attained by applying singular value decomposition. This paper further develops upon the approach in [1] to expand the Discrete-Time Jacobian Eigenvalue Approximation (DDJEA), giving values to significant off-diagonal terms while establishing a generalized connectivity between correlated buses. Statistical linear models are applied over large data sets to prove significance to each term. Then the off diagonal terms are given time-varying weights to account for changes in topology or sensitivity to events using a reduced system model. The results of this novel method are compared to the present errors of the previous publication in order to quantify the degree of improvement that this novel method imposes. The effective bus eigenvalues are briefly compared to Prony analysis to check similarities. An additional application for biorthogonal wavelets is also introduced to detect event types, including the HIF, for PMU data.
基金supported by the National Science Foundation of China (No.CNS-1553494)the Department of Energy Grant (No. 800006104)
文摘Synchrophasor devices guarantee situation awareness for real-time monitoring and operational visibility of smart grid. With their widespread implementation,significant challenges have emerged, especially in communication, data quality and cybersecurity. The existing literature treats these challenges as separate problems,when in reality, they have a complex interplay. This paper conducts a comprehensive review of quality and cybersecurity challenges for synchrophasors, and identifies the interdependencies between them. It also summarizes different methods used to evaluate the dependency and surveys how quality checking methods can be used to detect potential cyberattacks.
基金supported in part by the U.S.National Science Foundation(U.S.NSF)through the U.S.NSF/Department of Energy(DOE)Engineering Research Center Program under Award EEC-1041877 for CURENT
文摘Synchrophasor systems, providing low-latency,high-precision, and time-synchronized measurements to enhance power grid performances, are deployed globally.However, the synchrophasor system as a physical network,involves communication constraints and data quality issues, which will impact or even disable certain synchrophasor applications. This work investigates the data quality issue for synchrophasor applications. In Part I, the standards of synchrophasor systems and the classifications and data quality requirements of synchrophasor applications are reviewed. Also, the actual events of synchronization signal accuracy, synchrophasor data loss, and latency are counted and analyzed. The review and statistics are expected to provide an overall picture of data accuracy,loss, and latency issues for synchrophasor applications.
基金supported in part by the U.S.National Science Foundation(U.S.NSF)through the U.S.NSF/Department of Energy(DOE)Engineering Research Center Program under Award EEC-1041877 for CURENT
文摘This work investigates the data quality issue for synchrophasor applications, and pays particular attention to synchronization signal loss and synchrophasor data loss events. First, the historical synchronization signal loss events are analyzed and the potential reasons and solutions are discussed. Then, the scenario of a small amount of synchrophasor data loss is studied and a Lagrange interpolating polynomial method is used to adaptively estimate the incomplete and missing data. The performance of proposed method is demonstrated with simulation results.Specifically, the proposed method considers the trade-off between the estimation accuracy and the hardware cost,and could be efficiently employed in reality.
基金This work was supported in part by the National Natural Science Foundation of China(No.51777081).
文摘By maliciously manipulating the synchrophasors produced by phasor measurement units in power systems,cyber attackers can mislead the control center into taking wrong actions.From the viewpoint of machine learning,normal and malicious synchrophasors may exhibit different spatial distribution characteristics when mapped into a latent space.Hence,a malicious synchrophasor detector can be acquired by training a classification model with instances derived from historical operational synchrophasor data.However,malicious synchrophasors occur infrequently in practice.It is likely to incur a great deal of effort and may even introduce inevitable experience errors when extracting and labeling a sufficient number of malicious synchrophasors from historical operational data for training.For most existing detectors,if they are directly trained with highly imbalanced datasets,their performances may severely deteriorate.In this paper,a novel type of malicious synchrophasor detector is developed based on a combinatorial use of data rebalancing,Bagging-based ensemble learning,and the widely recognized eXtreme Gradient Boosting(XGBoost)classifier.Experiments show that although fewer malicious instances are provided,the proposed detector is still capable of detecting malicious synchrophasors.
文摘Synchrophasors are time-synchronized electrical measurements that represent both the magnitude and phase angle of the electrical sinusoids. Synchrophasors are measured by fast time-stamped devices called phasor measurement units(PMUs) to constitute the basis of realtime monitoring and control actions in the electric grid.Due to its enhanced situational awareness capabilities,many applications of PMUs are presented in the literature in the past decades. This paper presents a comprehensive summary of synchrophasor technology, its architecture,optimal placement techniques and its applications in electric power transmission and distribution systems. These applications include wide-area situational awareness and monitoring, state estimation, fault location and protective relaying, islanding detection etc. This review also covers some of the existing challenges in its implementation and its potential applications.
基金supported by National Natural Science Foundation of China(No.52077004).
文摘The subsynchronous oscillations(SSOs)related to renewable generation seriously affect the stability and safety of the power systems.To realize the dynamic monitoring of SSOs by utilizing the high computational efficiency and noise-resilient features of the matrix pencil method(MPM),this paper propos es an improved MPM-based parameter identification with syn chrophasors.The MPM is enhanced by the angular frequency fitting equations based on the characteristic polynomial coeffi cients of the matrix pencil to ensure the accuracy of the identi fied parameters,since the existing eigenvalue solution of the MPM ignores the angular frequency conjugation constraints of the two fundamental modes and two oscillation modes.Then,the identification and recovery of bad data are proposed by uti lizing the difference in temporal continuity of the synchropha sors before and after noise reduction.The proposed parameter identification is verified with synthetic,simulated,and actual measured phase measurement unit(PMU)data.Compared with the existing MPM,the improved MPM achieves better accuracy for parameter identification of each component in SSOs,better real-time performance,and significantly reduces the effect of bad data.
基金the Engineering Research Center Shared Facilities supported by the Engineering Research Center Program of the National Science Foundation and DOE under NSF Award Number EEC1041877 and the CURENT Industry Partnership Program.
文摘Wide-area monitoring systems(WAMS)are becoming increasingly vital for enhancing power grid operators’situational awareness capabilities.As a pilot WAMS that was initially deployed in 2003,the frequency monitoring network FNET/GridEye uses GPS-time-synchronized monitors called frequency disturbance recorders(FDRs)to capture dynamic grid behaviors.Over the past ten years,a large number of publications related to FNET/GridEye have been reported.In this paper,the most recent developments of FNET/GridEye sensors,data centers,and data analytics applications are reviewed.These works demonstrate that FNET/GridEye will become a costeffective situational awareness tool for the future smart grid.
文摘State estimation is a critical functionality of energy management system(EMS) to provide power system states in real-time operations. However, problems such as failure to converge, prone to failure during contingencies,and biased estimates while system is under stressed condition occur so that state estimation results may not be reliable.The unreliable results further impact downstream network and market applications, such as contingency analysis,voltage stability analysis, transient stability analysis, system alarming, and unit commitment. Thus, operators may lose the awareness of system condition in EMS. This paper proposes a fully independent and one-of-a-kind system by integrating linear state estimator into situational awareness applications based on real-time synchrophasor data. With guaranteed and accurate state estimation solution and advanced real-time data analytic and monitoring functionalities, the system is capable of assisting operators to assess and diagnose current system conditions for proactive and necessary corrective actions. The architecture, building components, and implementation of the proposed system are explored in detail. Two case studies with simulated data from the subsystems of Electric Reliability Council of Texas(ERCOT) and Los Angeles Department of Water and Power(LADWP) are presented. The test results show the effectiveness and reliability of the system, and its value for realtime power system operations.
文摘Increasing power demand,penetration of renew-ables,and limitations of necessary grid expansion are proffering new challenges to existing power system protection and control strategies.However,with the advancement in intelligent elec-tronic devices and relaying technology,fast,accurate and reliable protection schemes can be developed for smart power systems.In this paper,a new protection scheme based on admittance and power change has been proposed with dual-use line relays to detect symmetrical/asymmetrical faults in power systems.A large number of fault environments have been simulated by varying fault distances from relay location,fault resistance,and power angle in single machine infinite bus and WSCC 9-bus systems.Some crucial decisive fault scenarios e.g.close in/far end faults,faults in series compensated line,faults during asymmetrical swings,switching ON/OFF large loads,single and multi-modal swings have also been verified for the proposed index.In this paper,for the first time,detection of faults during power swings have been examined and verified in the presence of wind farms.The simulation results show the proficiency of the proposed algorithm for detecting faults in the presence or absence of power swings.
文摘The present-day power system is a complex network that caters to the demands of several applications with diverse energy requirements.Such a complex network is susceptible to faults caused due to several reasons such as the failure of the equipment,hostile weather conditions,etc.These faults if not detected in the real-time may lead to cascading failures resulting in a blackout.These blackouts have catastrophic consequences which result in a huge loss of resources.For example,a blackout in 2004 caused an economic loss of 10 billion U.S dollars as per the report of the Electricity Consumers Resource Council.Subsequent investigation of the blackout revealed that the catastrophe could have been prevented if there was an early warning system.Similar other blackouts across the globe forced the power system engineers to devise an effective solution for real-time monitoring and control of the power system.The consequence of these efforts is the wide area measurement system(WAMS).The WAMS consists of several sensors known as the phasor measurement units(PMUs)that collect the real information pertaining to the health of the power grid.This information in the form time synchronized voltage and current phasors is communicated to the central control center or the phasor data concentrator(PDC)where the data is analyzed for detection of power system anomalies.The communication of the synchrophasor data from each PMU to the PDC constitutes the synchrophasor communication system(SPCS).Thus,the SPCS can be considered as the edifice of the WAMS and its reliable operation is essential for the effective monitoring and control of the power system.This paper presents a comprehensive review of the various synchrophasor communication technologies,communication standards and applications.It also identifies the existing knowledge gaps and the scope for future research work.
基金This work is supported in part by the CURENT Industry Partnership Program,in part by the Engineering Research Center Program of the National Science Foundation,DOE under NSF Award Number EEC-1041877in part by the National Natural Science Foundation of China under award number 52177078in part with the project funded by China Postdoctoral Science Foundation under award number BX20220102.
文摘Synchrophasor measurements are essential to realtime situational awareness of the smart grid but vulnerable to cyber-attacks during the process of transmission and invocation.To ensure data security and mitigate the impact of spoofed synchrophasor measurements,this work proposes a novel object detection method using a Weight-based One-dimensional Convolutional Segmentation Network(WOCSN)with the ability of attack behavior identification and time localization.In WOCSN,automatic data feature extraction can be achieved by onedimensional convolution from the input signal,thereby reducing the impact of handcrafted features.A weight loss function is designed to distribute the contribution for normal and attack signals.Then,attack time is located via the proposed binary method based on pixel segmentation.Furthermore,the actual synchrophasor data collected from four locations are used for the performance evaluation of the WOCSN.Finally,combined with designed evaluation metrics,the time localization ability of WOCSN is validated in the scenarios of composite attacks with different spoofed intensities and time-sensitivities.
基金supported by the National Natural Science Foundation of China(No.51725702)。
文摘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.
基金supported by the NSF Cyber-Physical Systems(CPS)Program under award number 1931975.
文摘Simultaneous human activities,such as the Super Bowl game,would cause certain impacts on frequency fluctuations in power systems.With the help of FNET/GridEye measurements,this paper aims to give comprehensive analyses on the frequency fluctuations during Super Bowl LIV held on Feb.2,2020,so as to better understand several phenomena caused by simultaneous activities which will help system operations and controls.First,recent developments of the FNET/GridEye are briefly introduced.Second,the frequency fluctuations of the Eastern Interconnection(El),western electricity coordinating council(WECC),and electric reliability council of Texas(ERCOT)power systems during Super Bowl LIV are analyzed.Third,frequency fluctuations of Super Bowl Sunday and ordinary Sundays in 2020 are compared.Finally,the differences of frequency fluctuations among different years during the Super Bowl and their change trends are also given.Furthermore,several possible explanations,including the simultaneity of electricity consumption at the beginning of commercial breaks and the halftime show,the increasing usage of the Internet,and the increasing size of TV screens,are illustrated in detail in this paper.
基金supported by the National Natural Science Foundation of China(No.52377098)。
文摘High-precision synchronized measurement data with short measurement latency are required for the applications of phasor measurement units(PMUs).This paper proposes a synchrophasor measurement method based on cascaded infinite impulse response(IIR)and dual finite impulse response(FIR)filters,meeting the M-class and P-class requirements in the IEC/IEEE 60255-118-1 standard.A low-group-delay IIR filter is designed to remove out-of-band interference components.Two FIR filters with different center frequencies are designed to filter out the fundamental negative frequency component and obtain synchrophasor estimates.The ratio of the amplitudes of the synchrophasor is used to calculate the frequency according to the one-to-one correspondence between the ratio of the amplitude frequency response of the FIR filters and the frequency.To shorten the response time introduced by IIR filter,a step identification and processing method based on the rate of change of frequency(RoCoF)is proposed and analyzed.The synchrophasor is accurately compensated based on the frequency and the frequency response of the IIR and FIR filters,achieving high-precision synchrophasor and frequency estimates with short measurement latency.Simulation and experiment tests demonstrate that the proposed method is superior to existing methods and can provide synchronized measurement data for M-class PMU applications with short measurement latency.
