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Multi-Harmonic Source Localization Based on Sparse Component Analysis and Minimum Conditional Entropy.

Yongzhen Du1, Honggeng Yang1, Xiaoyang Ma1

  • 1College of Electrical Engineering, Sichuan University, Chengdu 610065, China.

Entropy (Basel, Switzerland)
|December 8, 2020
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Summary
This summary is machine-generated.

A new method using sparse component analysis and minimum conditional entropy accurately locates harmonic sources in power distribution systems, even with unknown network impedance and an undetermined number of sources.

Keywords:
conditional entropyharmonic source localizationindependent component analysisnetwork impedancesparse component analysis

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Area of Science:

  • Electrical Engineering
  • Power Systems Analysis
  • Signal Processing

Background:

  • Independent component analysis (ICA) has limitations in harmonic source location due to requiring numerous measurement points and failing under underdetermined conditions.
  • Accurate identification of harmonic sources is crucial for maintaining power quality in distribution systems.

Purpose of the Study:

  • To propose a novel method for identifying multiple harmonic source locations in distribution systems under underdetermined conditions.
  • To address the limitations of existing methods like ICA regarding measurement point requirements and unknown system parameters.

Main Methods:

  • A measurement node configuration algorithm selects optimal positions for accurate harmonic current separation.
  • Sparse component analysis (SCA) is employed to determine harmonic current waveforms from selected node voltage data under underdetermined conditions.
  • Minimum conditional entropy is used to pinpoint harmonic source locations by calculating entropy between harmonic currents and system nodes.

Main Results:

  • The proposed method successfully identifies harmonic source locations in an IEEE 14-node system simulation.
  • The algorithm demonstrates effectiveness and accuracy, outperforming traditional ICA methods in underdetermined scenarios.
  • Simulation results confirm the correctness and reliability of the novel approach.

Conclusions:

  • The developed sparse component analysis and minimum conditional entropy method provides an effective solution for harmonic source location in power distribution systems.
  • This technique overcomes the limitations of ICA, offering accurate localization even with unknown network impedance and an undetermined number of harmonic sources.
  • The findings validate the proposed algorithm's potential for practical application in power system harmonic analysis.