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tracking Power System state Evolution with Maximum-correntropy-based Extended Kalman Filter

Journal of Modern Power Systems and Clean Energy 2020年第4期8卷 616-626页

作者： Julio A.D.Massignan João B.A.London Jr. Vladimiro Miranda IEEE Department of Electrical and Computing Engineering School of Engineering of São CarlosUniversity of São PauloSão CarlosBrazil Faculty of Engineering University of Porto and INESC TECPortoPortugal

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 *** includes the temporal aspects on the estimation process within a maximum-correntropy-based extended Kalman filter(MCEKF),which is able to deal with both nonlinear supervisory control and data acquisition(SCADA)and phasor measurement unit(PMU)measurement *** representing the behavior of the state variables with a nonparametric model within the kernel density estimation,it is possible to include abrupt state transitions as part of the process noise with non-Gaussian ***,a novel strategy to update the size of Parzen windows in the kernel estimation is proposed to suppress the effects of suspect *** properly adjusting the kernel bandwidth,the proposed MCEKF keeps its accuracy during sudden load changes and contingencies,or in the presence of bad *** with IEEE test systems and the Brazilian interconnected system are carried *** 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.

关键词： tracking state estimation Kalman filter maximum correntropy power system Parzen window

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