A robust extended Kalman filter for power system dynamic state estimation using PMU measurements
Marcos Netto,Junbo Zhao,Lamine Mili +2 more
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TLDR
This paper develops a robust extended Kalman filter to estimate the rotor angles and the rotor speeds of synchronous generators of a multimachine power system using a batch-mode regression form and based on a robust GM-estimator that bounds the influence of vertical outliers and bad leverage points.Abstract:
This paper develops a robust extended Kalman filter to estimate the rotor angles and the rotor speeds of synchronous generators of a multimachine power system. Using a batch-mode regression form, the filter processes together predicted state vector and PMU measurements to track the system dynamics faster than the standard extended Kalman filter. Our proposed filter is based on a robust GM-estimator that bounds the influence of vertical outliers and bad leverage points, which are identified by means of the projection statistics. Good statistical efficiency under the Gaussian distribution assumption of the process and the observation noise is achieved thanks to the use of the Huber cost function, which is minimized via the iteratively reweighted least squares algorithm. The asymptotic covariance matrix of the state estimation error vector is derived via the covariance matrix of the total influence function of the GM-estimator. Simulations carried out on the IEEE 39-bus test system reveal that our robust extended Kalman filter exhibits good tracking capabilities under Gaussian process and observation noise while suppressing observation outliers, even in position of leverage. These good performances are obtained only under the validity of the linear approximation of the power system model.read more
Citations
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A Robust Data-Driven Koopman Kalman Filter for Power Systems Dynamic State Estimation
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TL;DR: Numerical simulations carried out on the IEEE 39-bus test system reveal that the GM-KKF has a faster convergence rate than the non-robust Koopman operator-based Kalman filter thanks to the adoption of a batch-mode regression formulation.
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Diagnosis of Outliers and Cyber Attacks in Dynamic PMU-Based Power State Estimation
TL;DR: A robust method to detect random errors and cyber-attacks targeting alternating current (AC) dynamic state estimation through false data injection and an improved detection of outliers in the smart grid literature are introduced.
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TL;DR: In this article, the authors developed a data-driven technique to compute the participation factors for nonlinear systems based on the Koopman mode decomposition, which generalizes the original definition of the linear mode-in-state participation factors.
Proceedings ArticleDOI
Robust dynamic state estimator to outliers and cyber attacks
TL;DR: A robust iterated extended Kalman filter based on the generalized maximum likelihood approach (termed GM-IEKF) for dynamic state estimation that can effectively suppress observation and innovation outliers, which may be induced by model parameter gross errors and cyber attacks.
Journal ArticleDOI
New Kalman Filter Approach Exploiting Frequency Knowledge for Accurate PMU-Based Power System State Estimation
TL;DR: A new Kalman filter (KF) approach to power system state estimation (SE) based on phasor measurement units (PMUs), in which the knowledge of the system frequency is exploited to ensure the accuracy of the estimated quantities even under off-nominal conditions.
References
More filters
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Unscented filtering and nonlinear estimation
Simon Julier,Jeffrey Uhlmann +1 more
TL;DR: The motivation, development, use, and implications of the UT are reviewed, which show it to be more accurate, easier to implement, and uses the same order of calculations as linearization.
Book
Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches
TL;DR: With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory.
Journal ArticleDOI
Dynamic State Estimation in Power System by Applying the Extended Kalman Filter With Unknown Inputs to Phasor Measurements
TL;DR: In this paper, an extended Kalman filter (EKF) technique for dynamic state estimation of a synchronous machine using phasor measurement unit (PMU) quantities is developed.
Journal ArticleDOI
WACS-Wide-Area Stability and Voltage Control System: R&D and Online Demonstration
TL;DR: Online demonstration of a new response-based (feedback) Wide-Area stability and voltage Control System (WACS) is described, developed as a flexible platform to prevent blackouts and facilitate electrical commerce.
Journal ArticleDOI
Unscented kalman filter for power system dynamic state estimation
TL;DR: In this article, the unscented Kalman filter (UKF) is proposed for power system dynamic state estimation, which is based on the application of the Unscented Transformation (UT) combined with the Kalman Filter theory.