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A false data injection attack method for generator dynamic state estimation
[article]
2019
pre-print
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Then, three attack scenarios were set according to the degree of the FDI attacks, and they were tested by the cubature Kalman filter (CKF) and the robust cubature Kalman filter (RCKF). ...
In this regard, this paper proposes for the first time an FDI attack model based on the dynamic state estimation of generators. ...
5.2 评估指标
Dynamic state estimation index of generator 1 图 4 和图 5 显示了无攻击情形下分别基于 CKF 和
RCKF 的发电机功角和角速度的估计结果；图 6, 8, 10
分别显示了在三种 FDI 攻击场景下，发电机功角的估
计结果；图 7, 9, 11 分别显示了在三种 FDI 攻击场景
下，发电机角速度的估计结果。 ...
doi:10.19595/j.cnki.1000-6753.tces.181150
arXiv:1908.07689v1
fatcat:davzi7x2zbgcxf2ypdyshlczzy
Robust Cubature Kalman Filter for Dynamic State Estimation of Synchronous Machines under Unknown Measurement Noise Statistics
2019
IEEE Access
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Kalman-type filtering techniques including cubature Kalman filter (CKF) does not work well in non-Gaussian environments, especially in the presence of outliers. ...
To solve this problem, Huber's M-estimation based robust CKF (RCKF) is proposed for synchronous machines by combining the Huber's M-estimation theory with the classical CKF, which is capable of coping ...
The successful industrial application of wide-area measurement system has recently made possible the estimation of all the state variables of a synchronous machine through the use of dynamic state estimations ...
doi:10.1109/access.2019.2900228
fatcat:tovismcrdzfxlbwp35w7fbmbja
Dynamic State Estimation under Cyber Attacks: A Comparative Study of Kalman Filters and Observers
[article]
2015
arXiv
pre-print
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Utilizing highly synchronized measurements from synchrophasors, dynamic state estimation (DSE) can be applied for real-time monitoring of smart grids. ...
Particularly, we (a) present an overview of concurrent estimation techniques, highlighting key deficiencies, (b) develop DSE methods based on cubature Kalman filter and dynamic observers, (c) rigorously ...
In this paper, we discuss different dynamic state estimation methods by presenting an overview of state-of-the-art estimation techniques and developing alternatives, including the cubature Kalman filter ...
arXiv:1508.07252v1
fatcat:dkijjw3tcnhbznjr74apfzp7gq
Comparing Kalman Filters and Observers for Power System Dynamic State Estimation with Model Uncertainty and Malicious Cyber Attacks
[article]
2018
arXiv
pre-print
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Kalman filters and observers are two main classes of dynamic state estimation (DSE) routines. ...
Various Kalman filters and the observer are then tested on the 16-machine, 68-bus system given realistic scenarios under model uncertainty and different types of cyber attacks against synchrophasor measurements ...
Therefore, dynamic state estimation (DSE) processes estimating the dynamic states (i.e., the internal states of generators) by using highly synchronized PMU measurements with high sampling rates will be ...
arXiv:1605.01030v3
fatcat:oy7u7rcccnec5o3tfx7giblhve
A Review of State Estimation Techniques for Grid-Connected PMSG-Based Wind Turbine Systems
2023
Energies
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This review article enables readers to understand the current trends in state estimation methods and related issues of designing control, filtering, and state observers. ...
However, many advanced studies on state estimation of PMSG-based WTS deal with real-time information of operating variables through filters and observers, analysis, and summary of these strategies are ...
Adaptive Cubature Kalman Filter-Based Dynamic State Estimation An adaptive cubature Kalman filter (ACKF)-based dynamic state estimation technique for the voltage source converter operation was presented ...
doi:10.3390/en16020634
fatcat:xy3k7rfpzfbqfjkfwakgtnfaki
A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques
2021
Sensors
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robustness to component variation, stability and noise reduction. ...
The basics of fractional-order filters are reviewed, with a focus on the popular fractional-order Kalman filter, as well as those related to sensing. ...
Two new Kalman filters for state estimation in fractional-order systems using colored measurement noise are developed in [102] . ...
doi:10.3390/s21175920
pmid:34502811
fatcat:jmbfxn3hkje27faxceeru3rxya
Nonlinear State Estimation Algorithms for Autonomous Vehicles
[chapter]
2014
Computational Intelligence in Aerospace Sciences
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Nonlinear State Estimation Algorithms and their Applications State estimation is a process of estimating the unmeasured or noisy states using the measured outputs and control inputs along with process ...
The main tools for nonlinear state estimation are cubature Kalman filter (CKF) and its variants. A solution to simultaneous localisation and mapping (SLAM) problem using CKF is proposed. ...
However in the previously discussed nonlinear state estimators, the statistical properties of the noises are assumed to be known apriori and, in addition, they may not be robust against parametric uncertainties ...
doi:10.2514/5.9781624102714.0181.0220
fatcat:q3vzmwnlbvh75naeihwnni3cae
A Survey of Recent Indoor Localization Scenarios and Methodologies
2021
Sensors
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For Bayesian filtering methods, apart from the basic linear Kalman filter (LKF) methods, nonlinear stochastic filters such as extended KF, cubature KF, unscented KF and particle filters are introduced. ...
The key localization techniques like RSSI-based fingerprinting technique are presented using supervised machine learning methods, namely SVM (support vector machine), KNN (K nearest neighbors) and NN ( ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s21238086
pmid:34884090
fatcat:juacgglap5f5jaezn3w2lrur3u
A Survey for Recent Techniques and Algorithms of Geolocation and Target Tracking in Wireless and Satellite Systems
2021
Applied Sciences
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been addressed, including H∞ and Kalman Filtering versions that have been implemented and investigated by authors. ...
This survey introduces a review of various conventional geolocation techniques, current orientations, and state-of-the-art techniques and highlights some approaches and algorithms employed in wireless ...
Kalman Filtering Algorithm The Kalman filter (KF) uses feedback control to estimate the state of a target. ...
doi:10.3390/app11136079
fatcat:6vgotxtkrjanzhu5rjh7t5rkju
A Review of Nonlinear Kalman Filter Appling to Sensorless Control for AC Motor Drives
2019
China Electrotechnical Society Transactions on Electrical Machines and Systems
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This paper reviews the application of extended Kalman filter (EKF), unscented Kalman filter (UKF), and cubature Kalman filter (CKF) in speed sensorless control for AC motor drives. ...
Among the existing speed sensorless control methods, nonlinear Kalman filter-based one has attached widespread attention due to its superb estimation accuracy and inherent resistibility to noise. ...
The robust M-estimation theory is used to obtain the unknown measurement noise statistics. The validity of this method is proved by adding different types of noises. ...
doi:10.30941/cestems.2019.00047
fatcat:fu46zqp6drbqdd4nsmsakdh7na
An Effective Attack-Resilient Kalman Filter-Based Approach for Dynamic State Estimation of Synchronous Machine
2020
Iranian Journal of Electrical and Electronic Engineering
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Kalman filtering has been widely considered for dynamic state estimation in smart grids. ...
Despite its unique merits, the Kalman Filter (KF)-based dynamic state estimation can be undesirably influenced by cyber adversarial attacks that can potentially be launched against the communication links ...
The advantage of this method lies in its high robustness against the measurement noises. ...
doaj:c5c7183c95e845a499a19286a3ee73cd
fatcat:m2d5b5t4rrhf7px7gxoii26rom
Derivative-Free Kalman Filtering Based Approaches to Dynamic State Estimation for Power Systems With Unknown Inputs
2018
IEEE Transactions on Power Systems
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Unknown input estimation of Gen. 5 under high process and measurement noise levels, using measurement noise impact reduction measures
Derivative-free Kalman filtering based Approaches to Dynamic State ...
Index Terms-Dynamic state estimation, Kalman filters, phasor measurements, power system dynamics, state estimation, synchronous generator, unscented transformation NOMENCLATURE α Difference between rotor ...
doi:10.1109/tpwrs.2017.2663107
fatcat:wivpihaqzjc2zco4ij6x3bf7uu
A Multiplicative Noises and Additive Correlated Noises Cubature Kalman Filter and its Application in Quadruped Robot
2020
IEEE Access
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To solve this issue, this paper proposes Multiplicative Noises and Additive Correlated Noises Cubature Kalman Filter (MACNCKF), which solves state estimation problems involving multiplicative noise and ...
The traditional Cubature Kalman Filter (CKF) and its derived algorithms cannot work without the two hypotheses of Kalman Filter (KF), one is that the system model is accurate and the other is the system ...
Estimation algorithms are generally based on several improved forms of the KF algorithm, such as Extended Kalman Filter (EKF) [2] , Unscented Kalman Filter (UKF) [3] , and Cubature Kalman Filter (CKF ...
doi:10.1109/access.2020.3021494
fatcat:7ub45zcwrzc7hpvvtyw5nnjgiu
A Survey on Hybrid SCADA/WAMS State Estimation Methodologies in Electric Power Transmission Systems
2023
Energies
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State estimation (SE) is an essential tool of energy management systems (EMS), providing power system operators with an overall grasp of the actual power system operating conditions and aiding them in ...
Various HSE methods which overcome these challenges are reviewed, for both static and dynamic SE implementations. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/en16020618
fatcat:djpywlcvdvdmdmda4myp3qdx2y
Tracking Power System State Evolution with Maximum-correntropy-based Extended Kalman Filter
2020
Journal of Modern Power Systems and Clean Energy
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The results show that the method deals with non-Gaussian noises in both the process and measurement, and provides accurate estimates of the system state under normal and abnormal conditions. interests ...
This paper develops a novel approach to track power system state evolution based on the maximum correntropy criterion, due to its robustness against non-Gaussian errors. ...
Reference [27] uses the generalized correntropy concept within an unscented Kalman filter to improve the robustness against outliers. ...
doi:10.35833/mpce.2020.000122
fatcat:thpcfwkaevetbezolsqiyfwzm4
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