Robust extended complex Kalman Filter applied to distorted power system signals for frequency estimation

Panigrahi, Rakhee; Rauta, S; Panda, P. C.

doi:10.1109/icpws.2009.5442752

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…Consequently, the value of the proposed robust exponential function decreases faster and finally a fast reduction of weighting and mitigation of error can be achieved. Thus, estimation using the proposed RECKF is better under grid perturbations as compared with the method mentioned earlier in [15, 16].…”

Section: Proposed Reference Current Generationmentioning

confidence: 86%

“…The aforesaid estimation approaches have not considered these grid perturbations and hence in view of addressing these above issues (harmonics, voltage distortion, noise), we focus on the development of a new estimation algorithm (RECKF), in which a weighted exponential function

{normale}^{- false(y - h false(x false) false)^{2}}

has been incorporated considering all the above grid perturbations to estimate the reference current in SAPF. With arising abnormal condition, the value of ‘ y − h ( x )’ increases faster because of inclusion of a ‘square’ term in the proposed function, as a result the influences of abnormality can be decreased at a faster rate as compared with the exponential function mentioned earlier in [15, 16] and hence the proposed RECKF approach provides improved estimation which is independent of all grid perturbations.…”

Section: Introductionmentioning

confidence: 98%

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Model predictive‐based shunt active power filter with a new reference current estimation strategy

Panigrahi

Subudhi

Panda

2015

IET Power Electronics

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This study presents a new reference current estimation method using proposed robust extended complex Kalman filter (RECKF) together with model predictive current (MPC) control strategy in the development of a three-phase shunt active power filter (SAPF). A new exponential function embedded into the RECKF algorithm helps in the estimation of in phase fundamental component of voltage (v h) at the point of common coupling considering grid perturbations such as distorted voltage, measurement noise and phase angle jump and also for the estimation of fundamental amplitude of the load current (i h). The estimation of these two variables (v h , i h) is used to generate reference signals for MPC. The proposed RECKF-MPC needs less number of voltage sensors and resolves the difficulty of gain tuning of proportional-integral (PI) controller. The proposed RECKF-MPC approach is implemented using MATLAB/SIMULINK and also Opal-RT was used to obtain the real-time results. The results obtained using the proposed RECKF together with different variants of Kalman filters (Kalman filter (KF), extended KF (EKF) and extended complex KF (ECKF)) and PI controller are analysed both in the steady state as well as transient state conditions. From the above experimentation, it was observed that the proposed RECKF-MPC control strategy outperforms over PI controller and other variants of Kalman filtering approaches in terms of reference tracking error, power factor distortion and percentage total harmonic distortion in the SAPF system.

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Section: Proposed Reference Current Generationmentioning

confidence: 86%

{normale}^{- false(y - h false(x false) false)^{2}}

Section: Introductionmentioning

confidence: 98%

Model predictive‐based shunt active power filter with a new reference current estimation strategy

Panigrahi

Subudhi

Panda

2015

IET Power Electronics

Self Cite

View full text Add to dashboard Cite

show abstract

“…Thus, frequency tracking and estimation is necessary to respond to such unwanted conditions. Different techniques and algorithms have been introduced in the literature to estimate frequency, including discrete Fourier transform and its modifications [1][2][3], phase-locked loop [4][5][6], adaptive filters [7][8][9][10] and recursive state estimation-based non-linear observers [8,11], adaptive notch filters [12][13][14], recursive total least-square [15], continuous-time adaptive filter [16], state space algorithms based on Kalman filters [17][18][19][20]. A review of the frequency estimation methods can be found in [6,21,22].…”

Section: Introductionmentioning

confidence: 99%

Robust frequency estimation in three‐phase power systems using correntropy‐based adaptive filter

Khalili

Rastegarnia

Sanei

2015

IET Science, Measurement & Technology

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Improvement in power quality using hybrid power filters based on robust extended Kalman filter

Ray¹,

Das

Mohanty

et al. 2018

2018 19th International Carpathian Control Conference (ICCC)

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Robust extended complex Kalman Filter applied to distorted power system signals for frequency estimation

Cited by 4 publications

References 15 publications

Model predictive‐based shunt active power filter with a new reference current estimation strategy

Model predictive‐based shunt active power filter with a new reference current estimation strategy

Robust frequency estimation in three‐phase power systems using correntropy‐based adaptive filter

Improvement in power quality using hybrid power filters based on robust extended Kalman filter

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