Rate of change of frequency estimation for power systems using interpolated DFT and Kalman filter
Rate of change of frequency estimation for power systems using interpolated DFT and Kalman filter
This paper presents a new method for estimating rate of change of frequency (RoCoF) of voltage or current signals measured using instrument transformers. The method is demonstrably superior to currently available methods in literature, in terms of estimation-latency and estimation-error. The estimation is performed in two steps. In the first step, the analog voltage or current signal obtained from an instrument transformer is statistically processed using interpolated discrete Fourier transform in order to obtain the means and variances of the signal parameters. These means and variances are then given as inputs to the second step, in which Kalman filtering is used to find the final RoCoF estimate. Accurate mathematical expressions for the means and variances of signal parameters have been derived and used in the second step, which is the main reason behind the superior performance of the method. The applicability of the method has been demonstrated on a benchmark power system model.
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Pal, Bikash Chandra
3a9349b4-c9e5-4740-8564-92350e677ebe
June 2019
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Pal, Bikash Chandra
3a9349b4-c9e5-4740-8564-92350e677ebe
Singh, Abhinav Kumar and Pal, Bikash Chandra
(2019)
Rate of change of frequency estimation for power systems using interpolated DFT and Kalman filter.
IEEE Transactions on Power Systems, 34 (4).
(doi:10.1109/TPWRS.2018.2881151).
Abstract
This paper presents a new method for estimating rate of change of frequency (RoCoF) of voltage or current signals measured using instrument transformers. The method is demonstrably superior to currently available methods in literature, in terms of estimation-latency and estimation-error. The estimation is performed in two steps. In the first step, the analog voltage or current signal obtained from an instrument transformer is statistically processed using interpolated discrete Fourier transform in order to obtain the means and variances of the signal parameters. These means and variances are then given as inputs to the second step, in which Kalman filtering is used to find the final RoCoF estimate. Accurate mathematical expressions for the means and variances of signal parameters have been derived and used in the second step, which is the main reason behind the superior performance of the method. The applicability of the method has been demonstrated on a benchmark power system model.
Text
08630817
- Accepted Manuscript
Text
08630817
- Version of Record
More information
Accepted/In Press date: 28 October 2018
e-pub ahead of print date: 31 January 2019
Published date: June 2019
Identifiers
Local EPrints ID: 430927
URI: http://eprints.soton.ac.uk/id/eprint/430927
ISSN: 0885-8950
PURE UUID: a0a9ba57-53cf-45b2-854d-b7aa2ea5630c
Catalogue record
Date deposited: 17 May 2019 16:30
Last modified: 16 Mar 2024 04:40
Export record
Altmetrics
Contributors
Author:
Abhinav Kumar Singh
Author:
Bikash Chandra Pal
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics