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Related Experiment Video

Updated: Sep 10, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

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Published on: December 15, 2023

635

Robust algorithm development of frequency estimation in smart grid.

Yongqian Yu1, Yi Yang1, Xinyang Wang1

  • 1School of Computer & Communication Engineering, University of Science & Technology Beijing, Beijing, 100083, China.

Scientific Reports
|August 26, 2025
PubMed
Summary
This summary is machine-generated.

A new improved augmented complex least mean square (ACLMS) algorithm and a variable step size version (VSS-IACLMS) offer robust frequency estimation in power systems, even with impulsive noise.

Keywords:
IACLMSImpulsive noiseRobust frequency estimationSmart gridsUnbalanced three-phase power systemsVSS-IACLMS

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Power Systems

Background:

  • The augmented complex least mean square (ACLMS) algorithm is effective for frequency estimation in unbalanced three-phase power systems.
  • ACLMS relies on the [Formula: see text]-norm, limiting its performance in impulsive noise environments common in smart grids.

Purpose of the Study:

  • To develop a generalized ACLMS algorithm (IACLMS) robust to heavy-tailed noise.
  • To devise a variable step size IACLMS (VSS-IACLMS) algorithm for improved convergence and accuracy.

Main Methods:

  • The IACLMS algorithm replaces the [Formula: see text]-norm with a [Formula: see text]-norm for noise robustness.
  • The VSS-IACLMS algorithm incorporates a variable step size into the IACLMS framework.
  • Both algorithms utilize a widely linear complex-valued model and Clarke's transformation.

Main Results:

  • The proposed IACLMS and VSS-IACLMS algorithms demonstrate superior robustness and faster convergence compared to ACLMS.
  • VSS-IACLMS outperforms IACLMS, achieving mean square error performance close to the Cramér-Rao lower bound.

Conclusions:

  • IACLMS and VSS-IACLMS provide effective solutions for frequency estimation in noisy power systems.
  • VSS-IACLMS offers enhanced accuracy and convergence, making it highly suitable for smart grid applications.