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Dynamic State and Parameter Estimation of Synchronous Generator from Digital Relay Records

Challa, KK and Gurrala, G (2020) Dynamic State and Parameter Estimation of Synchronous Generator from Digital Relay Records. In: Electric Power Systems Research, 189 .

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Official URL: https://doi.org/10.1016/j.epsr.2020.106743


This paper proposes an approach for the estimation of dynamic states and parameters of a synchronous generator from digital protective relay (DPR) records. Digital fault recorder data or phasor measurement data based approaches are mostly used for aggregate generator models in the literature. The DPR records are usually available for individual generators in a plant and hence can be used for individual generator model development. Constrained Iterative Unscented Kalman Filter (CIUKF) is used in this paper which combines the benefit of iterations and constraints on variables to improve the accuracy of estimation. Adomian Decomposition Method (ADM) is used for solving the IEEE model 1.1 synchronous machine equations which has a less computational burden and higher accuracy when compared to the widely used Modified-Euler (ME) method. The effectiveness of the proposed approach is demonstrated using the WECC-3 generator 9 bus system. The simulation data is generated from a transient stability program with 1 kHz sampling rate for a duration of 3s to resemble a DPR record. The CIUKF is tailored to get good convergence and accuracy with short data records. It has been observed that the accuracy obtained with the proposed approach is good enough to preserve the rotor modes of oscillation. © 2020 Elsevier B.V.

Item Type: Journal Article
Publication: Electric Power Systems Research
Publisher: Elsevier Ltd
Additional Information: Copyright to this article belongs to Elsevier Ltd
Keywords: Electric fault currents; Iterative methods; Relay protection; Synchronous generators, Adomian decomposition methods; Computational burden; Digital fault recorder; Digital protective relay; Generator modeling; Iterative unscented kalman filters; State and parameter estimations; Synchronous machine, Parameter estimation
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 30 Jul 2021 11:41
Last Modified: 30 Jul 2021 11:41
URI: http://eprints.iisc.ac.in/id/eprint/66347

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