IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i17p6448-d905937.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/17/6448/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/17/6448/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Oscar G. Duarte & Javier A. Rosero & María del Carmen Pegalajar, 2022. "Data Preparation and Visualization of Electricity Consumption for Load Profiling," Energies, MDPI, vol. 15(20), pages 1-30, October.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nien-Che Yang & Danish Mehmood & Kai-You Lai, 2021. "Multi-Objective Artificial Bee Colony Algorithm with Minimum Manhattan Distance for Passive Power Filter Optimization Problems," Mathematics, MDPI, vol. 9(24), pages 1-19, December.
    2. Goran Petrovic & Juraj Alojzije Bosnic & Goran Majic & Marin Despalatovic, 2019. "A Design of PWM Controlled Calibrator of Non-Sinusoidal Voltage Waveforms," Energies, MDPI, vol. 12(10), pages 1-14, May.
    3. Abdulelah Alkesaiberi & Fouzi Harrou & Ying Sun, 2022. "Efficient Wind Power Prediction Using Machine Learning Methods: A Comparative Study," Energies, MDPI, vol. 15(7), pages 1-24, March.
    4. Moshammed Nishat Tasnim & Tofael Ahmed & Monjila Afrin Dorothi & Shameem Ahmad & G. M. Shafiullah & S. M. Ferdous & Saad Mekhilef, 2023. "Voltage-Oriented Control-Based Three-Phase, Three-Leg Bidirectional AC–DC Converter with Improved Power Quality for Microgrids," Energies, MDPI, vol. 16(17), pages 1-32, August.
    5. Tüysüz, Metin & Okumuş, Halil Ibrahim & Aymaz, Şeyma & Çavdar, Bora, 2024. "Real-time application of a demand-side management strategy using optimization algorithms," Applied Energy, Elsevier, vol. 368(C).
    6. Karol Jakub Listewnik, 2022. "A Method for the Evaluation of Power-Generating Sets Based on the Assessment of Power Quality Parameters," Energies, MDPI, vol. 15(14), pages 1-24, July.
    7. Shahram Hanifi & Saeid Lotfian & Hossein Zare-Behtash & Andrea Cammarano, 2022. "Offshore Wind Power Forecasting—A New Hyperparameter Optimisation Algorithm for Deep Learning Models," Energies, MDPI, vol. 15(19), pages 1-21, September.
    8. Ning Wang & Shuai Zheng & Weiqiang Gao, 2022. "Microgrid Harmonic Mitigation Strategy Based on the Optimal Allocation of Active Power and Harmonic Mitigation Capacities of Multi-Functional Grid-Connected Inverters," Energies, MDPI, vol. 15(17), pages 1-20, August.
    9. Mushtaq, Khurram & Waris, Asim & Zou, Runmin & Shafique, Uzma & Khan, Niaz B. & Khan, M. Ijaz & Jameel, Mohammed & Khan, Muhammad Imran, 2024. "A comprehensive approach to wind turbine power curve modeling: Addressing outliers and enhancing accuracy," Energy, Elsevier, vol. 304(C).
    10. Łukasz Michalec & Paweł Kostyła & Zbigniew Leonowicz, 2022. "Supraharmonic Pollution Emitted by Nonlinear Loads in Power Networks—Ongoing Worldwide Research and Upcoming Challenges," Energies, MDPI, vol. 16(1), pages 1-14, December.
    11. Zbigniew Leonowicz & Michal Jasinski, 2022. "Machine Learning and Data Mining Applications in Power Systems," Energies, MDPI, vol. 15(5), pages 1-2, February.
    12. Xing Sun & Wanjun Lei & Yuqi Dai & Yilin Yin & Qian Liu, 2022. "Optimization Configuration of Grid-Connected Inverters to Suppress Harmonic Amplification in a Microgrid," Energies, MDPI, vol. 15(14), pages 1-15, July.
    13. Oktay Karakaya & Murat Erhan Balci & Mehmet Hakan Hocaoglu, 2023. "Minimization of Voltage Harmonic Distortion of Synchronous Generators under Non-Linear Loading via Modulated Field Current," Energies, MDPI, vol. 16(4), pages 1-17, February.
    14. Flávia P. Monteiro & Suzane A. Monteiro & Maria E. Tostes & Ubiratan H. Bezerra, 2019. "Using True RMS Current Measurements to Estimate Harmonic Impacts of Multiple Nonlinear Loads in Electric Distribution Grids," Energies, MDPI, vol. 12(21), pages 1-21, October.
    15. Luis Alfonso Menéndez-García & Paulino José García-Nieto & Esperanza García-Gonzalo & Fernando Sánchez Lasheras & Laura Álvarez-de-Prado & Antonio Bernardo-Sánchez, 2023. "Method for the Detection of Functional Outliers Applied to Quality Monitoring Samples in the Vicinity of El Musel Seaport in the Metropolitan Area of Gijón (Northern Spain)," Mathematics, MDPI, vol. 11(12), pages 1-23, June.
    16. Anna Ostrowska & Łukasz Michalec & Marek Skarupski & Michał Jasiński & Tomasz Sikorski & Paweł Kostyła & Robert Lis & Grzegorz Mudrak & Tomasz Rodziewicz, 2022. "Power Quality Assessment in a Real Microgrid-Statistical Assessment of Different Long-Term Working Conditions," Energies, MDPI, vol. 15(21), pages 1-26, October.
    17. Luigi Fortuna & Arturo Buscarino, 2022. "Nonlinear Technologies in Advanced Power Systems: Analysis and Control," Energies, MDPI, vol. 15(14), pages 1-4, July.
    18. Nien-Che Yang & Danish Mehmood, 2022. "Multi-Objective Bee Swarm Optimization Algorithm with Minimum Manhattan Distance for Passive Power Filter Optimization Problems," Mathematics, MDPI, vol. 10(1), pages 1-20, January.
    19. Christian A. Rojas & Samir Kouro & Ruben Inzunza & Yasuaki Mitsugi & Abraham M. Alcaide, 2022. "Harmonic Impedance Model of Multiple Utility-Interactive Multilevel Photovoltaic Inverters," Energies, MDPI, vol. 15(24), pages 1-21, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6448-:d:905937. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.