CLC number: TM921
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2016-10-19
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Mehdi Ahmadi Jirdehi, Reza Hemmati, Vahid Abbasi, Hedayat Saboori. A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(11): 1218-1227.
@article{title="A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes",
author="Mehdi Ahmadi Jirdehi, Reza Hemmati, Vahid Abbasi, Hedayat Saboori",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="17",
number="11",
pages="1218-1227",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500301"
}
%0 Journal Article
%T A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes
%A Mehdi Ahmadi Jirdehi
%A Reza Hemmati
%A Vahid Abbasi
%A Hedayat Saboori
%J Frontiers of Information Technology & Electronic Engineering
%V 17
%N 11
%P 1218-1227
%@ 2095-9184
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500301
TY - JOUR
T1 - A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes
A1 - Mehdi Ahmadi Jirdehi
A1 - Reza Hemmati
A1 - Vahid Abbasi
A1 - Hedayat Saboori
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 17
IS - 11
SP - 1218
EP - 1227
%@ 2095-9184
Y1 - 2016
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1500301
Abstract: We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the kalman filter theory. The proposed algorithm also successfully detects and identifies sudden load changes in power systems. The method uses three normalized vectors to process errors at each sampling time: normalized measurement residual, normalized Lagrange multiplier, and normalized innovation vector. An IEEE 14-bus test system was used to verify and demonstrate the effectiveness of the proposed method. Numerical results are presented and discussed to show the accuracy of the method.
This paper proposed a new and efficient algorithm for simultaneous detection, identification and correction of measurement and branch parameter errors based on the DSE algorithm and KF theory. The proposed correction methodology also successfully detected and identified the sudden load changes. The suitable results were obtained and it was shown that the proposed method successfully processed the anomalies and identified and corrected the errors, with high accuracy. The ideas in the paper are interesting and the theoretic results obtained have some potential in applications.
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