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DFIG damping controller design using robust CKF-based adaptive dynamic programming

DFIG damping controller design using robust CKF-based adaptive dynamic programming
DFIG damping controller design using robust CKF-based adaptive dynamic programming
An adaptive, Lyapunov stable, computational optimal control scheme based on a policy iteration algorithm is presented for the damping control of oscillatory dynamics and overall stability improvement of a grid-connected doubly fed induction generator (DFIG) based wind energy conversion system. The proposed controller employs adaptive dynamic programming and uses the online information of estimated internal states, terminal measurements, and controller output to solve the nonlinear algebraic Riccati equation. The unobservable internal states of the DFIG are estimated from terminal measurements (stator current and terminal voltage) using a robust nonlinear dynamic state estimator based on spherical-radial cubature rule. The controller does not require any prior knowledge of the linearized system matrices and hence assumes unknown system dynamics, thereby avoiding the considerable computational burden of system linearization. A detailed model of the DFIG has been considered, and the effectiveness of the proposed controller has been compared with an optimally tuned conventional damping controller and traditional linear quadratic regulator. A scaled laboratory setup using coupled rapid prototyping controller and real-time station has been used to demonstrate the real-time applicability of the developed scheme. A modified IEEE WSCC 9-bus system with DFIG interconnection has also been used as a test system for controller evaluation in the multimachine environment
1949-3029
839 - 850
Mir, Abdul Saleem
491bb457-cbe5-4705-ab36-860b78763332
Senroy, Nilanjan
b4565b4f-78eb-4a88-8af9-9d8c29238a4d
Mir, Abdul Saleem
491bb457-cbe5-4705-ab36-860b78763332
Senroy, Nilanjan
b4565b4f-78eb-4a88-8af9-9d8c29238a4d

Mir, Abdul Saleem and Senroy, Nilanjan (2019) DFIG damping controller design using robust CKF-based adaptive dynamic programming. IEEE Transactions on Sustainable Energy, 11 (2), 839 - 850. (doi:10.1109/TSTE.2019.2910262).

Record type: Article

Abstract

An adaptive, Lyapunov stable, computational optimal control scheme based on a policy iteration algorithm is presented for the damping control of oscillatory dynamics and overall stability improvement of a grid-connected doubly fed induction generator (DFIG) based wind energy conversion system. The proposed controller employs adaptive dynamic programming and uses the online information of estimated internal states, terminal measurements, and controller output to solve the nonlinear algebraic Riccati equation. The unobservable internal states of the DFIG are estimated from terminal measurements (stator current and terminal voltage) using a robust nonlinear dynamic state estimator based on spherical-radial cubature rule. The controller does not require any prior knowledge of the linearized system matrices and hence assumes unknown system dynamics, thereby avoiding the considerable computational burden of system linearization. A detailed model of the DFIG has been considered, and the effectiveness of the proposed controller has been compared with an optimally tuned conventional damping controller and traditional linear quadratic regulator. A scaled laboratory setup using coupled rapid prototyping controller and real-time station has been used to demonstrate the real-time applicability of the developed scheme. A modified IEEE WSCC 9-bus system with DFIG interconnection has also been used as a test system for controller evaluation in the multimachine environment

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Published date: 11 April 2019

Identifiers

Local EPrints ID: 449236
URI: http://eprints.soton.ac.uk/id/eprint/449236
ISSN: 1949-3029
PURE UUID: 9f6ea3a7-2563-482c-a7a5-3a172063f7f9

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Date deposited: 20 May 2021 16:31
Last modified: 16 Mar 2024 12:20

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Contributors

Author: Abdul Saleem Mir
Author: Nilanjan Senroy

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