DocumentCode :
2006166
Title :
Online grid impedance estimation for the control of grid connected converters in inductive-resistive distributed power-networks using extended kalman-filter
Author :
Hoffmann, Nils ; Fuchs, Friedrich W.
Author_Institution :
Inst. for Power Electron. & Electr. Drives, Christian-Albrechts-Univ. of Kiel, Kiel, Germany
fYear :
2012
fDate :
15-20 Sept. 2012
Firstpage :
922
Lastpage :
929
Abstract :
Real-time estimation of the equivalent grid impedance and the equivalent grid voltage seen from a power converter connected to the public electric distribution network by means of Extended Kalman-Filter is addressed. The theoretical background of the Extended Kalman-Filter used for equivalent grid impedance estimation is introduced. Practical aspects like the use of the filter in an environment with highly distorted voltage waveforms, the tuning of the noise covariance matrices and the implementation on a laboratory system are discussed. The theoretical analysis is verified on a 22 kW test-bench where a grid impedance emulator is used to simulate grid impedance steps in the laboratory environment. The proposed Extended Kalman-Filter is designed to utilize the noise that is already present at the connection point of the power converter to overcome the need of active disturbance injection to estimate the equivalent grid impedance.
Keywords :
Kalman filters; distributed power generation; nonlinear filters; power grids; power system measurement; equivalent grid impedance; equivalent grid voltage; extended Kalman-filter; grid connected converters; inductive-resistive distributed power-networks; online grid impedance estimation; power 22 kW; power converter; Current measurement; Impedance; Noise; Observers; Parameter estimation; Prediction algorithms; Voltage measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Energy Conversion Congress and Exposition (ECCE), 2012 IEEE
Conference_Location :
Raleigh, NC
Print_ISBN :
978-1-4673-0802-1
Electronic_ISBN :
978-1-4673-0801-4
Type :
conf
DOI :
10.1109/ECCE.2012.6342720
Filename :
6342720
Link To Document :
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