This paper addresses the problem of distributed secure state estimation for multi-agent systems under homologous sensor attacks.Two types of secure Luenberger-like distributed observers are proposed to estimate the sy...This paper addresses the problem of distributed secure state estimation for multi-agent systems under homologous sensor attacks.Two types of secure Luenberger-like distributed observers are proposed to estimate the system state and attack signal simultaneously.Specifically,the proposed two observers are applicable to deal with the cases in the presence and absence of time delays during network communication.It is also shown that the proposed observers can ensure the attack estimations from different agents asymptotically converge to the same value.Sufficient conditions for guaranteeing the asymptotic convergence of the estimation errors are derived.Simulation examples are finally provided to demonstrate the effectiveness of the proposed results.展开更多
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 w...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.展开更多
In order to have an accurate knowledge of system-wide operation states,it is necessary to perform state estimation for the integrated energy system(IES)as the basis of energy man-agement and control.Centralized state ...In order to have an accurate knowledge of system-wide operation states,it is necessary to perform state estimation for the integrated energy system(IES)as the basis of energy man-agement and control.Centralized state estimation is practically infeasible for IES due to the unreliability of communication,the barrier on privacy,and the large scale of integrated systems.This paper proposes a distributed state estimation algorithm based on the alternating direction method of multipliers(ADMM)for IES containing electricity,heat,and natural gas.Various coupling units are taken into full consideration in modeling of IES state estimation to reflect the harmonization of multi energy.On the basis of bilinear measurement model,the state estimation considering nonlinear measurements can be replaced by an equivalent three-stage problem containing two linear state estimations and an intermediate transformation to avoid non-convex optimization.The three-stage procedure for IES state estimation can be further decoupled over three sub-systems with coordination on coupling units,yielding a fully distributed scheme based on ADMM.A modified ADMM with the self-adjusting penalty parameter is also adopted to enhance the convergence.Simulation results demonstrate the validity and superiority of the proposed algorithm.展开更多
This paper proposes a new multi-area framework for unbalanced active distribution network(ADN) state estimation. Firstly, an innovative three-phase distributed generator(DG) model is presented to take the asymmetric c...This paper proposes a new multi-area framework for unbalanced active distribution network(ADN) state estimation. Firstly, an innovative three-phase distributed generator(DG) model is presented to take the asymmetric characteristics of DG three-phase outputs into consideration. Then a feasible method to set pseudo-measurements for unmonitored DGs is introduced. The states of DGs,together with the states of alternating current(AC) buses in ADNs, were estimated by using the weighted least squares(WLS) method. After that, the ADN was divided into several independent subareas. Based on the augmented Lagrangian method, this work proposes a fully distributed three-phase state estimator for the multi-area ADN.Finally, from the simulation results on the modified IEEE123-bus system, the effectiveness and applicability of the proposed methodology have been investigated and discussed.展开更多
In this paper,we present a distributed framework for the lidar-based relative state estimator which achieves highly accurate,real-time trajectory estimation of multiple Unmanned Aerial Vehicles(UAVs)in GPS-denied envi...In this paper,we present a distributed framework for the lidar-based relative state estimator which achieves highly accurate,real-time trajectory estimation of multiple Unmanned Aerial Vehicles(UAVs)in GPS-denied environments.The system builds atop a factor graph,and only on-board sensors and computing power are utilized.Benefiting from the keyframe strategy,each UAV performs relative state estimation individually and broadcasts very partial information without exchanging raw data.The complete system runs in real-time and is evaluated with three experiments in different environments.Experimental results show that the proposed distributed approach offers comparable performance with a centralized method in terms of accuracy and real-time performance.The flight test demonstrates that the proposed relative state estimation framework is able to be used for aggressive flights over 5 m/s.展开更多
Cyber-attacks that tamper with measurement information threaten the security of state estimation for the current distribution system.This paper proposes a cyber-attack detection strategy based on distribution system s...Cyber-attacks that tamper with measurement information threaten the security of state estimation for the current distribution system.This paper proposes a cyber-attack detection strategy based on distribution system state estimation(DSSE).The uncertainty of the distribution network is represented by the interval of each state variable.A three-phase interval DSSE model is proposed to construct the interval of each state variable.An improved iterative algorithm(IIA)is developed to solve the interval DSSE model and to obtain the lower and upper bounds of the interval.A cyber-attack is detected when the value of the state variable estimated by the traditional DSSE is out of the corresponding interval determined by the interval DSSE.To validate the proposed cyber-attack detection strategy,the basic principle of the cyber-attack is studied,and its general model is formulated.The proposed cyber-attack model and detection strategy are conducted on the IEEE 33-bus and 123-bus systems.Comparative experiments of the proposed IIA,Monte Carlo simulation algorithm,and interval Gauss elimination algorithm prove the validation of the proposed method.展开更多
Distribution state estimation(DSE)is an essential part of an active distribution network with high level of distributed energy resources.The challenges of accurate DSE with limited measurement data is a well-known pro...Distribution state estimation(DSE)is an essential part of an active distribution network with high level of distributed energy resources.The challenges of accurate DSE with limited measurement data is a well-known problem.In practice,the operation and usability of DSE depend on not only the estimation accuracy but also the ability to predict error variance.This paper investigates the application of error covariance in DSE by using the augmented complex Kalman filter(ACKF).The Kalman filter method inherently provides state error covariance prediction.It can be utilized to accurately infer the error covariance of other parameters and provide a method to determine optimal measurement locations based on the sensitivity of error covariance to measurement noise covariance.This paper also proposes a generalized formulation of ACKF to allow scalar measurements to be incorporated into the complex-valued estimator.The proposed method is simulated by using modified IEEE 34-bus and IEEE 123-bus test feeders,and randomly generates the load data of complex-valued Wiener process.The ACKF method is compared with an equivalent formulation using the traditional weighted least squares(WLS)method and iterated extended Kalman filter(IEKF)method,which shows improved accuracy and computation performance.展开更多
This paper investigates network partition and edge server placement problem to exploit the benefit of edge computing for distributed state estimation.A constrained many-objective optimization problem is formulated to ...This paper investigates network partition and edge server placement problem to exploit the benefit of edge computing for distributed state estimation.A constrained many-objective optimization problem is formulated to minimize the cost of edge server deployment,operation,and maintenance,avoid the difference in the partition sizes,reduce the level of coupling between connected partitions,and maximize the inner cohesion of each partition.Capacities of edge server are constrained against underload and overload.To efficiently solve the problem,an improved non-dominated sorting genetic algorithm III(NSGA-III)is developed,with a specifically designed directed mutation operator based on topological characteristics of the partitions to accelerate convergence.Case study validates that the proposed formulations effectively characterize the practical concerns and reveal their trade-offs,and the improved algorithm outperforms existing representative ones for large-scale networks in converging to a near-optimal solution.The optimized result contributes significantly to real-time distributed state estimation.展开更多
The accuracy of distribution system state estimation(DDSE)is reduced when phasor measurement unit(PMU)measurements contain outliers because of cyber attacks or global positioning system spoofing attacks.Therefore,to e...The accuracy of distribution system state estimation(DDSE)is reduced when phasor measurement unit(PMU)measurements contain outliers because of cyber attacks or global positioning system spoofing attacks.Therefore,to enhance the robustness of DDSE to measurement outliers,approximate the target distribution of Metropolis-Hastings(MH)sampling,and judge the prediction of the long short-term memory(LSTM)network,this paper proposes an outlier reconstruction based state estimation method using the equivalent model of the LSTM network and MH sampling(E-LM model),motivated by the characteristics of the chronological correlations of PMU measurements.First,the target distribution of outlier reconstruction is derived using a kernel density estimation function.Subsequently,the reasons and advantages of the E-LM model are explained and analyzed from a mathematical point of view.The proposed LSTM-based MH sampling can approximate the target distribution of MH sampling to decrease the number of the futile iterations.Moreover,the proposed MH-based forecasting of the LSTM can judge each LSTM prediction,which is independent of its true value.Finally,simulations are conducted to evaluate the performance of the E-LM model by integrating the LSTM network and the MH sampling into the outlier reconstruction based DDSE.展开更多
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 ...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.展开更多
In recent years, theoretical and practical research on event-based communication strategies has gained considerable research attention due primarily to their irreplaceable superiority in resource-constrained systems(...In recent years, theoretical and practical research on event-based communication strategies has gained considerable research attention due primarily to their irreplaceable superiority in resource-constrained systems(especially networked systems). For networked systems, event-based transmission scheme is capable of improving the efficiency in resource utilization and prolonging the lifetime of the network components compared with the widely adopted periodic transmission scheme. As such, it would be interesting to 1) examining how the event-triggering mechanisms affect the control or filtering performance for networked systems, and 2) developing some suitable approaches for the controller and filter design problems. In this paper, a bibliographical review is presented on event-based control and filtering problems for various networked systems. First, the event-driven communication scheme is introduced in detail according to its engineering background, characteristic, and representative research frameworks. Then, different event-based control and filtering(or state estimation) problems are categorized and then discussed. Finally, we conclude the paper by outlining future research challenges for event-based networked systems.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(buctrc202201)High Performance Computing Platform,College of Information Science and Technology,Beijing University of Chemical Technology。
文摘This paper addresses the problem of distributed secure state estimation for multi-agent systems under homologous sensor attacks.Two types of secure Luenberger-like distributed observers are proposed to estimate the system state and attack signal simultaneously.Specifically,the proposed two observers are applicable to deal with the cases in the presence and absence of time delays during network communication.It is also shown that the proposed observers can ensure the attack estimations from different agents asymptotically converge to the same value.Sufficient conditions for guaranteeing the asymptotic convergence of the estimation errors are derived.Simulation examples are finally provided to demonstrate the effectiveness of the proposed results.
基金supported by the Science and Technology Project of State Grid Corporation of China (No.5204JY20000B)。
文摘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.
文摘In order to have an accurate knowledge of system-wide operation states,it is necessary to perform state estimation for the integrated energy system(IES)as the basis of energy man-agement and control.Centralized state estimation is practically infeasible for IES due to the unreliability of communication,the barrier on privacy,and the large scale of integrated systems.This paper proposes a distributed state estimation algorithm based on the alternating direction method of multipliers(ADMM)for IES containing electricity,heat,and natural gas.Various coupling units are taken into full consideration in modeling of IES state estimation to reflect the harmonization of multi energy.On the basis of bilinear measurement model,the state estimation considering nonlinear measurements can be replaced by an equivalent three-stage problem containing two linear state estimations and an intermediate transformation to avoid non-convex optimization.The three-stage procedure for IES state estimation can be further decoupled over three sub-systems with coordination on coupling units,yielding a fully distributed scheme based on ADMM.A modified ADMM with the self-adjusting penalty parameter is also adopted to enhance the convergence.Simulation results demonstrate the validity and superiority of the proposed algorithm.
基金supported by National Natural Science Foundation of China(No.51277052)
文摘This paper proposes a new multi-area framework for unbalanced active distribution network(ADN) state estimation. Firstly, an innovative three-phase distributed generator(DG) model is presented to take the asymmetric characteristics of DG three-phase outputs into consideration. Then a feasible method to set pseudo-measurements for unmonitored DGs is introduced. The states of DGs,together with the states of alternating current(AC) buses in ADNs, were estimated by using the weighted least squares(WLS) method. After that, the ADN was divided into several independent subareas. Based on the augmented Lagrangian method, this work proposes a fully distributed three-phase state estimator for the multi-area ADN.Finally, from the simulation results on the modified IEEE123-bus system, the effectiveness and applicability of the proposed methodology have been investigated and discussed.
基金supported by the National Key Research and Development Program of China(No.2018AAA0102401)the National Natural Science Foundation of China(Nos.62022060,61773278,61873340).
文摘In this paper,we present a distributed framework for the lidar-based relative state estimator which achieves highly accurate,real-time trajectory estimation of multiple Unmanned Aerial Vehicles(UAVs)in GPS-denied environments.The system builds atop a factor graph,and only on-board sensors and computing power are utilized.Benefiting from the keyframe strategy,each UAV performs relative state estimation individually and broadcasts very partial information without exchanging raw data.The complete system runs in real-time and is evaluated with three experiments in different environments.Experimental results show that the proposed distributed approach offers comparable performance with a centralized method in terms of accuracy and real-time performance.The flight test demonstrates that the proposed relative state estimation framework is able to be used for aggressive flights over 5 m/s.
基金supported in part by the National Key Research and Development Program of China(No.2017YFB0902900)the State Grid Corporation of China
文摘Cyber-attacks that tamper with measurement information threaten the security of state estimation for the current distribution system.This paper proposes a cyber-attack detection strategy based on distribution system state estimation(DSSE).The uncertainty of the distribution network is represented by the interval of each state variable.A three-phase interval DSSE model is proposed to construct the interval of each state variable.An improved iterative algorithm(IIA)is developed to solve the interval DSSE model and to obtain the lower and upper bounds of the interval.A cyber-attack is detected when the value of the state variable estimated by the traditional DSSE is out of the corresponding interval determined by the interval DSSE.To validate the proposed cyber-attack detection strategy,the basic principle of the cyber-attack is studied,and its general model is formulated.The proposed cyber-attack model and detection strategy are conducted on the IEEE 33-bus and 123-bus systems.Comparative experiments of the proposed IIA,Monte Carlo simulation algorithm,and interval Gauss elimination algorithm prove the validation of the proposed method.
文摘Distribution state estimation(DSE)is an essential part of an active distribution network with high level of distributed energy resources.The challenges of accurate DSE with limited measurement data is a well-known problem.In practice,the operation and usability of DSE depend on not only the estimation accuracy but also the ability to predict error variance.This paper investigates the application of error covariance in DSE by using the augmented complex Kalman filter(ACKF).The Kalman filter method inherently provides state error covariance prediction.It can be utilized to accurately infer the error covariance of other parameters and provide a method to determine optimal measurement locations based on the sensitivity of error covariance to measurement noise covariance.This paper also proposes a generalized formulation of ACKF to allow scalar measurements to be incorporated into the complex-valued estimator.The proposed method is simulated by using modified IEEE 34-bus and IEEE 123-bus test feeders,and randomly generates the load data of complex-valued Wiener process.The ACKF method is compared with an equivalent formulation using the traditional weighted least squares(WLS)method and iterated extended Kalman filter(IEKF)method,which shows improved accuracy and computation performance.
基金supported by the Shanghai Sailing Program(No.19YF1423700)the National Key Research and Development Program of China(No.2016YFB0900100)the Key Project of Shanghai Science and Technology Committee(No.18DZ1100303).
文摘This paper investigates network partition and edge server placement problem to exploit the benefit of edge computing for distributed state estimation.A constrained many-objective optimization problem is formulated to minimize the cost of edge server deployment,operation,and maintenance,avoid the difference in the partition sizes,reduce the level of coupling between connected partitions,and maximize the inner cohesion of each partition.Capacities of edge server are constrained against underload and overload.To efficiently solve the problem,an improved non-dominated sorting genetic algorithm III(NSGA-III)is developed,with a specifically designed directed mutation operator based on topological characteristics of the partitions to accelerate convergence.Case study validates that the proposed formulations effectively characterize the practical concerns and reveal their trade-offs,and the improved algorithm outperforms existing representative ones for large-scale networks in converging to a near-optimal solution.The optimized result contributes significantly to real-time distributed state estimation.
基金supported by the National Key Research and Development Program(No.2017YFB0902900).
文摘The accuracy of distribution system state estimation(DDSE)is reduced when phasor measurement unit(PMU)measurements contain outliers because of cyber attacks or global positioning system spoofing attacks.Therefore,to enhance the robustness of DDSE to measurement outliers,approximate the target distribution of Metropolis-Hastings(MH)sampling,and judge the prediction of the long short-term memory(LSTM)network,this paper proposes an outlier reconstruction based state estimation method using the equivalent model of the LSTM network and MH sampling(E-LM model),motivated by the characteristics of the chronological correlations of PMU measurements.First,the target distribution of outlier reconstruction is derived using a kernel density estimation function.Subsequently,the reasons and advantages of the E-LM model are explained and analyzed from a mathematical point of view.The proposed LSTM-based MH sampling can approximate the target distribution of MH sampling to decrease the number of the futile iterations.Moreover,the proposed MH-based forecasting of the LSTM can judge each LSTM prediction,which is independent of its true value.Finally,simulations are conducted to evaluate the performance of the E-LM model by integrating the LSTM network and the MH sampling into the outlier reconstruction based DDSE.
基金The author Min Liu received the grant of the National Natural Science Foundation of China(http://www.nsfc.gov.cn/)(51967004).
文摘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.
基金supported by National Natural Science Foundation of China(No.61329301)the Royal Society of the UK+2 种基金the Research Fund for the Taishan Scholar Project of Shandong Province of Chinathe China Postdoctoral Science Foundation(No.2016M600547)the Alexander von Humboldt Foundation of Germany
文摘In recent years, theoretical and practical research on event-based communication strategies has gained considerable research attention due primarily to their irreplaceable superiority in resource-constrained systems(especially networked systems). For networked systems, event-based transmission scheme is capable of improving the efficiency in resource utilization and prolonging the lifetime of the network components compared with the widely adopted periodic transmission scheme. As such, it would be interesting to 1) examining how the event-triggering mechanisms affect the control or filtering performance for networked systems, and 2) developing some suitable approaches for the controller and filter design problems. In this paper, a bibliographical review is presented on event-based control and filtering problems for various networked systems. First, the event-driven communication scheme is introduced in detail according to its engineering background, characteristic, and representative research frameworks. Then, different event-based control and filtering(or state estimation) problems are categorized and then discussed. Finally, we conclude the paper by outlining future research challenges for event-based networked systems.