Method of Accelerated Low-Frequency Oscillation Analysis in Low-Inertia Power Systems Based on Orthogonal Decomposition

The peculiarity of the functioning of modern electric power systems, caused by the presence of renewable energy sources, flexible control devices based on power electronics, and the reduction of the reserve of the transmission capacity of the electric network, increases the relevance of identifying and damping low-frequency oscillations (LFOs) of the electrical mode. This paper presents a comparative analysis of methods for estimating the parameters of low-frequency oscillations. Their applicability limits are shown as well as their peculiarity associated with low adaptability, and time costs in assessing the parameters of the electrical mode with low-frequency oscillations are revealed. A method for the accelerated evaluation of low-frequency oscillation parameters is proposed, the delay of which is ¼ of the oscillation cycle. The method was tested on both synthetic and physical signals. In the first case, the source of data was a four-machine mathematical model of a power system. In the second case, signals of transient processes occurring in a real power system were used as physical data. The accuracy of the proposed method was obtained by calculating the difference between the original and reconstructed signals. As a result, calculated error values were obtained, describing the accuracy and efficiency of the proposed method. The proposed algorithm for estimating LFO parameters displayed an error value not exceeding 0.8% for both synthetic and physical data.

Authors

Institutions

Publication Details

Journal
Electronics
Published
2025-10-20
DOI
https://doi.org/10.3390/electronics14204105
Primary Topic
Vibration and Dynamic Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Method of Accelerated Low-Frequency Oscillation Analysis in Low-Inertia Power Systems Based on Orthogonal Decomposition

Murodbek Safaraliev, Svetlana Beryozkina, Mihail Senyuk, Ismoil N. Odinaev et al.
Electronics
Vibration and Dynamic Analysis
article

Method of Accelerated Low-Frequency Oscillation Analysis in Low-Inertia Power Systems Based on Orthogonal Decomposition

Murodbek Safaraliev, Svetlana Beryozkina, Mihail Senyuk, Ismoil N. Odinaev, Inga Zicmane
article en

Abstract

The peculiarity of the functioning of modern electric power systems, caused by the presence of renewable energy sources, flexible control devices based on power electronics, and the reduction of the reserve of the transmission capacity of the electric network, increases the relevance of identifying and damping low-frequency oscillations (LFOs) of the electrical mode. This paper presents a comparative analysis of methods for estimating the parameters of low-frequency oscillations. Their applicability limits are shown as well as their peculiarity associated with low adaptability, and time costs in assessing the parameters of the electrical mode with low-frequency oscillations are revealed. A method for the accelerated evaluation of low-frequency oscillation parameters is proposed, the delay of which is ¼ of the oscillation cycle. The method was tested on both synthetic and physical signals. In the first case, the source of data was a four-machine mathematical model of a power system. In the second case, signals of transient processes occurring in a real power system were used as physical data. The accuracy of the proposed method was obtained by calculating the difference between the original and reconstructed signals. As a result, calculated error values were obtained, describing the accuracy and efficiency of the proposed method. The proposed algorithm for estimating LFO parameters displayed an error value not exceeding 0.8% for both synthetic and physical data.

ElectronicsVol. 14(20)
Ural Federal University (RU), Riga Technical University (LV), American University of the Middle East (KW)
Ural Federal University, Ministry of Science and Higher Education of the Russian Federation
Openalex Percentile: Top 62%
Vibration and Dynamic Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.