Observer-based pulsed signal injection for grid impedance estimation in three phase systems

Garcia, Pablo, Sumner, M., Navarro-Rodríguez, Ángel, Guerrero, Juan M. and Garcia, Jorge (2018) Observer-based pulsed signal injection for grid impedance estimation in three phase systems. IEEE Transactions on Industrial Electronics . ISSN 1557-9948

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This paper addresses the estimation of the grid impedance and the control of grid-tied converters by combining pulsed-signal injection and observer based techniques. A Luenberger based observer is used for controlling the grid-side current of an LCL filter by only measuring the converter-side currents and the grid-side voltage. This configuration mitigates the effects of parameter variation at the LCL filter. Under grid impedance changes, the observer control signal will be used for triggering the signal injection. A Pulsed Signal Injection (PSI) approach is employed for estimating online the grid impedance using an RLS algorithm. Compared with existing grid-impedance estimation techniques, the proposed method can: 1) identify a generic RL grid impedance, even under unbalanced conditions; 2) reduce the distortion induced by the excitation signal by relying on the observer to triggering the injection when a grid impedance change is detected; 3) Identify grid impedance values much lower than the converter filter impedance, which is the usual situation when the converter rated power is well below the grid rating. Finally, it is worth pointing out that the proposed estimation technique is well suited to be incorporated into an adaptive current controller scheme.

Item Type: Article
Additional Information: 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution.
Keywords: Impedance, Observers, Voltage control, Voltage measurement, Frequency estimation, Adaptation models
Schools/Departments: University of Nottingham, UK > Faculty of Engineering > Department of Electrical and Electronic Engineering
Identification Number:
Depositing User: Burns, Rebecca
Date Deposited: 07 Feb 2018 15:03
Last Modified: 04 May 2020 19:30

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