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Harmonic Contribution Assessment Based on the Random Sample Consensus and Recursive Least Square Methods

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  • Jong-Il Park

    (School of Electrical Engineering, College of Engineering, Pukyong National University, 45 Yongso-ro, Nam-gu, Busan 48513, Korea)

  • Chang-Hyun Park

    (School of Electrical Engineering, College of Engineering, Pukyong National University, 45 Yongso-ro, Nam-gu, Busan 48513, Korea)

Abstract

This paper deals with a method of quantifying the harmonic contribution of each harmonic source to system voltage distortion. Assessing the harmonic contribution of individual harmonic sources is essential for mitigating and managing system harmonic levels. Harmonic contributions can be evaluated using the principle of voltage superposition with equivalent voltage models for harmonic sources. In general, the parameters of equivalent voltage models are estimated numerically because it is difficult to measure them directly. In this paper, we present an effective method for estimating equivalent model parameters based on the random sample consensus (RANSAC) and recursive least square (RLS) with a variable forgetting factor. The procedure for quantifying harmonic contributions using equivalent models is also introduced. Additionally, we propose a network diagram of harmonic contributions that makes it easy to understand the harmonic distortion contributions of all harmonic sources.

Suggested Citation

  • Jong-Il Park & Chang-Hyun Park, 2022. "Harmonic Contribution Assessment Based on the Random Sample Consensus and Recursive Least Square Methods," Energies, MDPI, vol. 15(17), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6448-:d:905937
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    References listed on IDEAS

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    1. Łukasz Michalec & Michał Jasiński & Tomasz Sikorski & Zbigniew Leonowicz & Łukasz Jasiński & Vishnu Suresh, 2021. "Impact of Harmonic Currents of Nonlinear Loads on Power Quality of a Low Voltage Network–Review and Case Study," Energies, MDPI, vol. 14(12), pages 1-19, June.
    2. Ravi Shankar Singh & Vladimir Ćuk & Sjef Cobben, 2020. "Measurement-Based Distribution Grid Harmonic Impedance Models and Their Uncertainties," Energies, MDPI, vol. 13(16), pages 1-16, August.
    3. Allan Manito & Ubiratan Bezerra & Maria Tostes & Edson Matos & Carminda Carvalho & Thiago Soares, 2018. "Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks," Energies, MDPI, vol. 11(12), pages 1-13, November.
    4. Mingzhe Zou & Sasa Z. Djokic, 2020. "A Review of Approaches for the Detection and Treatment of Outliers in Processing Wind Turbine and Wind Farm Measurements," Energies, MDPI, vol. 13(16), pages 1-30, August.
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    Cited by:

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    2. Stefani Freitas & Luis Carlos Oliveira & Priscila Oliveira & Bruno Exposto & José Gabriel Pinto & Joao L. Afonso, 2023. "New Topology of a Hybrid, Three-Phase, Four-Wire Shunt Active Power Filter," Energies, MDPI, vol. 16(3), pages 1-28, January.

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