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Mohammad Bayat

Mohammad Bayat

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0003-1465-0015
Education: PhD.
ScopusId: 56681445600
Faculty: Engineering
Address: Arak University
Phone:

Research

Title
A robust fusion bus frequency estimation method to improve frequency oscillation damping in power systems
Type
JournalPaper
Keywords
remote bus frequency estimation, Frequency Divider, frequency oscillation damping, Generalized Maximum-likelihood UKF, Robust state estimation
Year
2023
Journal IET Generation, Transmission & Distribution
DOI
Researchers Ali Farahani ، Amirhossein Abolmasoumi ، Lamine Mili ، Mohammad Bayat

Abstract

This paper proposes a new robust method for accurately and reliably estimating remote bus frequencies in a power system. Two different measurement sources for the remote bus frequency are considered, that is, the ideal Frequency Divider (FD) and the Synchronous Reference Frame Phase Locked Loops (SRF-PLLs). Each measurement signal encounters different uncertainties and data quality issues. In this paper, both data sources are employed and fused together to better estimate the remote bus frequencies. To this end, the model structure of the power system is selected and an Unscented Kalman Filter (UKF)is utilized together with a fusion covariance intersection method to enhance the accuracy of the estimated bus frequency. Since the fusion estimation method fails in case of quality issues on both channels, a robust Generalized Maximum-likelihood UKF (GM-UKF)using a novel outlier detection criteria is developed. The impact of the resulting robust fusion filter on the estimation of the remote bus frequencies and on the performance of WAPSS, which makes use of the estimated frequencies as the feedback signal, is examined via simulations. The results demonstrate the excellent performance and reliability of the proposed method in dealing with noise filtering and outlier suppression while ensuring a high statistical efficiency