IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i6p2548-d1091099.html
   My bibliography  Save this article

Alternative Current Injection Newton and Fast Decoupled Power Flow

Author

Listed:
  • Cristina Coutinho de Oliveira

    (Federal Institute of Amapá (IFAP), Pedra Branca do Amapari Center, Macapá 68945-000, Brazil)

  • Alfredo Bonini Neto

    (School of Sciences and Engineering, São Paulo State University (Unesp), Tupã 17602-496, Brazil)

  • Dilson Amancio Alves

    (School of Engineering, São Paulo State University (Unesp), Ilha Solteira 15385-000, Brazil)

  • Carlos Roberto Minussi

    (School of Engineering, São Paulo State University (Unesp), Ilha Solteira 15385-000, Brazil)

  • Carlos Alberto Castro

    (Technology Center, Pontifical Catholic University of Campinas (PUC), Campinas 13087-571, Brazil)

Abstract

This article presents an alternative Newton-Raphson power flow method version. This method has been developed based on current injection equations formulated in polar coordinates. Likewise, the fast decoupled power flow, elaborated using current injection (BX version), is presented. These methods are tested considering electrical power systems composed of 57-, 118-, and 300-bus, as well as a realistic system of 787-bus. For the robustness analysis, simulations were performed considering different loading conditions and R/X ratios of the transmission line. Based on the simulations that were realized, there is evidence that the performance of the proposed current injection methods is similar to the power injection methods.

Suggested Citation

  • Cristina Coutinho de Oliveira & Alfredo Bonini Neto & Dilson Amancio Alves & Carlos Roberto Minussi & Carlos Alberto Castro, 2023. "Alternative Current Injection Newton and Fast Decoupled Power Flow," Energies, MDPI, vol. 16(6), pages 1-17, March.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2548-:d:1091099
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/6/2548/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/6/2548/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alfredo Bonini Neto & Dilson Amancio Alves & Carlos Roberto Minussi, 2022. "Artificial Neural Networks: Multilayer Perceptron and Radial Basis to Obtain Post-Contingency Loading Margin in Electrical Power Systems," Energies, MDPI, vol. 15(21), pages 1-14, October.
    2. Yan Huang & Yuntao Ju & Zeping Zhu, 2019. "An Asymptotic Numerical Continuation Power Flow to Cope with Non-Smooth Issue," Energies, MDPI, vol. 12(18), pages 1-17, September.
    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. Guilherme Barbosa Lima & Alfredo Bonini Neto & Dilson Amancio Alves & Carlos Roberto Minussi & Estélio da Silva Amorim & Luiz Carlos Pereira da Silva, 2023. "Technique for Reactive Loss Reduction and Loading Margin Enhancement Using the Curves of Losses versus Voltage Magnitude," Energies, MDPI, vol. 16(16), pages 1-21, August.
    2. Sebastian Bottler & Christian Weindl, 2023. "State-Space Load Flow Calculation of an Energy System with Sector-Coupling Technologies," Energies, MDPI, vol. 16(12), pages 1-22, June.

    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. Mengqiang Zhang & Yurong Tang & Hong Zhang & Haipeng Lan & Hao Niu, 2023. "Parameter Optimization of Spiral Fertilizer Applicator Based on Artificial Neural Network," Sustainability, MDPI, vol. 15(3), pages 1-13, January.
    2. Hyun-Tae Kim & Jungju Lee & Myungseok Yoon & Moon-Jeong Lee & Namhun Cho & Sungyun Choi, 2020. "Continuation Power Flow Based Distributed Energy Resource Hosting Capacity Estimation Considering Renewable Energy Uncertainty and Stability in Distribution Systems," Energies, MDPI, vol. 13(17), pages 1-16, August.

    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:16:y:2023:i:6:p:2548-:d:1091099. 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.