IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i19p7247-d932030.html
   My bibliography  Save this article

A Novel Classification of the 330 kV Nigerian Power Network Using a New Voltage Stability Pointer

Author

Listed:
  • Tayo Uthman Badrudeen

    (Department of Electrical and Electronics Engineering, Oduduwa University, Ile-Ife 5533, Nigeria
    Department of Electronic and Electrical Engineering, Obafemi Awolowo University, Ile-Ife 220282, Nigeria)

  • Funso Kehinde Ariyo

    (Department of Electronic and Electrical Engineering, Obafemi Awolowo University, Ile-Ife 220282, Nigeria)

  • Saheed Lekan Gbadamosi

    (Center for Cyber Physical Food, Energy and Water Systems, University of Johannesburg, Johannesburg 2006, South Africa)

  • Nnamdi I. Nwulu

    (Center for Cyber Physical Food, Energy and Water Systems, University of Johannesburg, Johannesburg 2006, South Africa)

Abstract

The incessant power outages that characterize the Nigerian power network (NGP), as in all developing countries, are not limited to the shortage of fuel for power generation. However, differential power shortages between the generated power and the load demand are alarming. In this study, we propose a new voltage stability pointer (NVSP) based on a reduced one-line power network to act as a classifier. The NVSP was trained with a support vector machine (SVM) using a medium Gaussian kernel classification toolbox (mGkCT) in the MATLAB environment. This classification is based on the power network susceptibility to voltage instability. NGP 28-bus 330 kV data were extracted and modeled in the MATLAB environment and tested with the NVSP-mGkCT classifier. The NVSP-mGkCT was able to classify the lines viz. stable and unstable lines for the base and contingency cases. Similarly, the linear load dynamics and non-linear load dynamics were evaluated on the basis of critical buses using the NVSP. The aim of this work was to help the Transmission Company of Nigeria (TCN) and the National Control Centre (NCC) to be pre-emptive with respect to possible voltage collapse due to voltage instability. The simulation results show that NVSP was able to flag vulnerable lines in the NGP.

Suggested Citation

  • Tayo Uthman Badrudeen & Funso Kehinde Ariyo & Saheed Lekan Gbadamosi & Nnamdi I. Nwulu, 2022. "A Novel Classification of the 330 kV Nigerian Power Network Using a New Voltage Stability Pointer," Energies, MDPI, vol. 15(19), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:7247-:d:932030
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/19/7247/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/19/7247/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. P. Abirami & C. N. Ravi, 2022. "Enhancing grid stability by maintaining power quality in distribution network using FOPID and ANN controlled shunt active filter," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 7551-7578, June.
    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. Tayo Uthman Badrudeen & Nnamdi I. Nwulu & Saheed Lekan Gbadamosi, 2023. "Neural Network Based Approach for Steady-State Stability Assessment of Power Systems," Sustainability, MDPI, vol. 15(2), pages 1-13, 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.

      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:19:p:7247-:d:932030. 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.