Comparative Analysis of High-Speed Methods of Frequency Measurement of the Power Grids

There are many digital methods for measuring the frequency of the power grid. The main disadvantage of all existing methods is the long time required to perform measurements, which complicates their use in modern control systems and control tasks that require getting a quick result. In mentioned areas, a group of so-called "fast" measurement methods is used, the most outstanding of which are the method of three samples and the method of the second derivative of the input signal. This publication provides a comparative analysis of these methods. The causes of static and dynamic measurement errors under sinusoidal and non-sinusoidal input signals are considered. It is shown that the main cause of error is the difference between the input signal shape from the sinusoidal one. For the measurement method based on the second derivative of the input signal, options for constructing digital differentiators are considered. The effect of the differentiator on the frequency measurement error under sinusoidal and non-sinusoidal input signals is estimated. For the least squares method, the accuracy of calculating the number of samples is given, the result for ensuring high measurement accuracy while maintaining low time. Methods for reducing errors are considered and their effectiveness is assessed using simulation modeling in Matlab/Simulink.

Authors

Institutions

Publication Details

Published
2024-10-17
DOI
https://doi.org/10.1109/eexpolytech62224.2024.10755731
Citations
1
Primary Topic
Electric Power Systems and Control
Type
article
Field-Weighted Citation Impact
0.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative Analysis of High-Speed Methods of Frequency Measurement of the Power Grids

Alexei O. Orlov, Andrey N. Serov, Darya S. Evtekhova, Anton V. Pavlovich
1 citations
Electric Power Systems and Control
0.21
article

Comparative Analysis of High-Speed Methods of Frequency Measurement of the Power Grids

Alexei O. Orlov, Andrey N. Serov, Darya S. Evtekhova, Anton V. Pavlovich
article en
1 citations

Abstract

There are many digital methods for measuring the frequency of the power grid. The main disadvantage of all existing methods is the long time required to perform measurements, which complicates their use in modern control systems and control tasks that require getting a quick result. In mentioned areas, a group of so-called "fast" measurement methods is used, the most outstanding of which are the method of three samples and the method of the second derivative of the input signal. This publication provides a comparative analysis of these methods. The causes of static and dynamic measurement errors under sinusoidal and non-sinusoidal input signals are considered. It is shown that the main cause of error is the difference between the input signal shape from the sinusoidal one. For the measurement method based on the second derivative of the input signal, options for constructing digital differentiators are considered. The effect of the differentiator on the frequency measurement error under sinusoidal and non-sinusoidal input signals is estimated. For the least squares method, the accuracy of calculating the number of samples is given, the result for ensuring high measurement accuracy while maintaining low time. Methods for reducing errors are considered and their effectiveness is assessed using simulation modeling in Matlab/Simulink.

Moscow Power Engineering Institute (RU)
Affordable and clean energy
Openalex Percentile: Top 46%
Electric Power Systems and Control
0.21
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.