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Decentralized robust dynamic state estimation in power systems using instrument transformers

Decentralized robust dynamic state estimation in power systems using instrument transformers
Decentralized robust dynamic state estimation in power systems using instrument transformers

This paper proposes a decentralized method for estimation of dynamic states of a power system. The method remains robust to time-synchronization errors and high noise levels in measurements. Robustness of the method has been achieved by incorporating internal angle in the dynamic model used for estimation and by decoupling the estimation process into two stages with continuous updation of measurement-noise variances. Additionally, the proposed estimation method does not need measurements obtained from phasor measurement units; instead, it just requires analog measurements of voltages and currents directly acquired from instrument transformers. This is achieved through statistical signal processing of analog voltages and currents to obtain their magnitudes and frequencies, followed by application of unscented Kalman filtering for nonlinear estimation. The robustness and feasibility of the method have been demonstrated on a benchmark power system model.

Decentralized, discrete-time Fourier transform (DFT), dynamic state estimation (DSE), Hanning-window, instrument transformers, internal angle, phasor measurement unit (PMU), pseudo-input, statistical signal processing, time-synchronization error, unscented Kalman filtering (UKF)
1053-587X
1541-1550
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Pal, Bikash C.
c062978e-53eb-4d5d-ace8-746ccafa5fb0
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Pal, Bikash C.
c062978e-53eb-4d5d-ace8-746ccafa5fb0

Singh, Abhinav Kumar and Pal, Bikash C. (2018) Decentralized robust dynamic state estimation in power systems using instrument transformers. IEEE Transactions on Signal Processing, 66 (6), 1541-1550, [8249743]. (doi:10.1109/TSP.2017.2788424).

Record type: Article

Abstract

This paper proposes a decentralized method for estimation of dynamic states of a power system. The method remains robust to time-synchronization errors and high noise levels in measurements. Robustness of the method has been achieved by incorporating internal angle in the dynamic model used for estimation and by decoupling the estimation process into two stages with continuous updation of measurement-noise variances. Additionally, the proposed estimation method does not need measurements obtained from phasor measurement units; instead, it just requires analog measurements of voltages and currents directly acquired from instrument transformers. This is achieved through statistical signal processing of analog voltages and currents to obtain their magnitudes and frequencies, followed by application of unscented Kalman filtering for nonlinear estimation. The robustness and feasibility of the method have been demonstrated on a benchmark power system model.

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Accepted/In Press date: 9 December 2017
e-pub ahead of print date: 8 January 2018
Published date: 15 March 2018
Keywords: Decentralized, discrete-time Fourier transform (DFT), dynamic state estimation (DSE), Hanning-window, instrument transformers, internal angle, phasor measurement unit (PMU), pseudo-input, statistical signal processing, time-synchronization error, unscented Kalman filtering (UKF)

Identifiers

Local EPrints ID: 430935
URI: http://eprints.soton.ac.uk/id/eprint/430935
ISSN: 1053-587X
PURE UUID: 601dae54-8ae6-410a-938e-0df5e5191556
ORCID for Abhinav Kumar Singh: ORCID iD orcid.org/0000-0003-3376-6435

Catalogue record

Date deposited: 17 May 2019 16:30
Last modified: 07 Oct 2020 02:24

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Contributors

Author: Abhinav Kumar Singh ORCID iD
Author: Bikash C. Pal

University divisions

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