Decentralized dynamic state estimation in power systems using unscented transformation
Decentralized dynamic state estimation in power systems using unscented transformation
This paper proposes a decentralized algorithm for real-time estimation of the dynamic states of a power system. The scheme employs phasor measurement units (PMUs) for the measurement of local signals at each generation unit, and subsequent state estimation using unscented Kalman filtering (UKF). The novelty of the scheme is that the state estimation at one generation unit is independent from the estimation at other units, and therefore the transmission of remote signals to a central estimator is not required. This in turn reduces the complexity of each distributed estimator, and makes the estimation process highly efficient, accurate and easily implementable. The applicability of the proposed algorithm has been thoroughly demonstrated on a representative model.
Decentralized, dynamic state estimation, Kalman filter, phasor measurement units, unscented transformation
794-804
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Pal, Bikash C.
c062978e-53eb-4d5d-ace8-746ccafa5fb0
1 March 2014
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Pal, Bikash C.
c062978e-53eb-4d5d-ace8-746ccafa5fb0
Singh, Abhinav Kumar and Pal, Bikash C.
(2014)
Decentralized dynamic state estimation in power systems using unscented transformation.
IEEE Transactions on Power Systems, 29 (2), , [6616007].
(doi:10.1109/TPWRS.2013.2281323).
Abstract
This paper proposes a decentralized algorithm for real-time estimation of the dynamic states of a power system. The scheme employs phasor measurement units (PMUs) for the measurement of local signals at each generation unit, and subsequent state estimation using unscented Kalman filtering (UKF). The novelty of the scheme is that the state estimation at one generation unit is independent from the estimation at other units, and therefore the transmission of remote signals to a central estimator is not required. This in turn reduces the complexity of each distributed estimator, and makes the estimation process highly efficient, accurate and easily implementable. The applicability of the proposed algorithm has been thoroughly demonstrated on a representative model.
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More information
Accepted/In Press date: 6 September 2013
e-pub ahead of print date: 30 September 2013
Published date: 1 March 2014
Keywords:
Decentralized, dynamic state estimation, Kalman filter, phasor measurement units, unscented transformation
Identifiers
Local EPrints ID: 431010
URI: http://eprints.soton.ac.uk/id/eprint/431010
ISSN: 0885-8950
PURE UUID: 18f9ddbb-c72a-4f44-b5e2-cbe3dec85483
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Date deposited: 21 May 2019 16:30
Last modified: 16 Mar 2024 04:40
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Contributors
Author:
Abhinav Kumar Singh
Author:
Bikash C. Pal
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