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Decentralized nonlinear adaptive optimal control scheme for enhancement of power system stability

Decentralized nonlinear adaptive optimal control scheme for enhancement of power system stability
Decentralized nonlinear adaptive optimal control scheme for enhancement of power system stability
An adaptive decentralized control scheme is proposed for real-time control of oscillatory dynamics and overall stability improvement of an interconnected power system. A standard framework of continuous-time (CT) infinite-horizon optimal control paradigm is defined and an extended online actor-critic (AC) algorithm based on policy iteration is used for its solution. The AC structure uses neural networks (NNs) whose weights are updated adaptively. The proof for the convergence of the scheme guarantees the system stability. The unobservable internal states of the synchronous machine are estimated using a numerically stable, swift and relatively accurate decentralized dynamic state estimator (DDSE) based on spherical-radial cubature rule. Applicability of the developed scheme has been demonstrated on a benchmark power system (IEEE 2.2, 16 machine 68 bus system) model via nonlinear time-domain simulations. Multi-processor technology based scaled laboratory setup was used for controller performance validation in real-time.
0885-8950
1400 - 1410
Mir, Abdul Saleem
491bb457-cbe5-4705-ab36-860b78763332
Bhasin, Shubhendu
954a250f-61e4-49b3-9a1b-c04410676f46
Senroy, Nilanjan
b4565b4f-78eb-4a88-8af9-9d8c29238a4d
Mir, Abdul Saleem
491bb457-cbe5-4705-ab36-860b78763332
Bhasin, Shubhendu
954a250f-61e4-49b3-9a1b-c04410676f46
Senroy, Nilanjan
b4565b4f-78eb-4a88-8af9-9d8c29238a4d

Mir, Abdul Saleem, Bhasin, Shubhendu and Senroy, Nilanjan (2019) Decentralized nonlinear adaptive optimal control scheme for enhancement of power system stability. IEEE Transactions on Power Systems, 35 (2), 1400 - 1410. (doi:10.1109/TPWRS.2019.2939394).

Record type: Article

Abstract

An adaptive decentralized control scheme is proposed for real-time control of oscillatory dynamics and overall stability improvement of an interconnected power system. A standard framework of continuous-time (CT) infinite-horizon optimal control paradigm is defined and an extended online actor-critic (AC) algorithm based on policy iteration is used for its solution. The AC structure uses neural networks (NNs) whose weights are updated adaptively. The proof for the convergence of the scheme guarantees the system stability. The unobservable internal states of the synchronous machine are estimated using a numerically stable, swift and relatively accurate decentralized dynamic state estimator (DDSE) based on spherical-radial cubature rule. Applicability of the developed scheme has been demonstrated on a benchmark power system (IEEE 2.2, 16 machine 68 bus system) model via nonlinear time-domain simulations. Multi-processor technology based scaled laboratory setup was used for controller performance validation in real-time.

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Published date: 4 September 2019

Identifiers

Local EPrints ID: 449234
URI: http://eprints.soton.ac.uk/id/eprint/449234
ISSN: 0885-8950
PURE UUID: 3add16b6-df26-4f0a-b0e1-73b8e4dac4c0

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Date deposited: 20 May 2021 16:31
Last modified: 20 May 2021 16:32

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Contributors

Author: Abdul Saleem Mir
Author: Shubhendu Bhasin
Author: Nilanjan Senroy

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