IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v9y2024i6p80-d1413933.html
   My bibliography  Save this article

Data for Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection

Author

Listed:
  • Santiago Bustamante-Mesa

    (Departamento de Eléctrica, Facultad de Ingenieria, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellín 050036, Colombia
    Grupo de Investigación Transmisión y Distribución de Energía Eléctrica (TyD), Universidad Pontificia Bolivariana, Medellín 050031, Colombia)

  • Jorge W. Gonzalez-Sanchez

    (Grupo de Investigación Transmisión y Distribución de Energía Eléctrica (TyD), Universidad Pontificia Bolivariana, Medellín 050031, Colombia)

  • Sergio D. Saldarriaga-Zuluaga

    (Departamento de Eléctrica, Facultad de Ingenieria, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellín 050036, Colombia)

  • Jesús M. López-Lezama

    (Research Group on Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellín 050010, Colombia)

  • Nicolás Muñoz-Galeano

    (Research Group on Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellín 050010, Colombia)

Abstract

The data presented in this paper are related to the paper entitled “Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection”, available in the Energies journal. Here, data are included to show the results of an Under-Frequency Load Shedding (UFLS) scheme that considers the injection of virtual inertia by a VSC-HVDC link. The data obtained in six cases which were considered and analyzed are shown. In this paper, each case represents a different frequency response configuration in the event of generation loss, taking into account the presence or absence of a VSC-HVDC link, traditional and optimized UFLS schemes, as well as the injection of virtual inertia by the VSC-HVDC link. Data for each example contain the state of the relay, threshold, position in every delay, load shed, and relay configuration parameters. Data were obtained through Digsilent Power Factory and Python simulations. The purpose of this dataset is so that other researchers can reproduce the results reported in our paper.

Suggested Citation

  • Santiago Bustamante-Mesa & Jorge W. Gonzalez-Sanchez & Sergio D. Saldarriaga-Zuluaga & Jesús M. López-Lezama & Nicolás Muñoz-Galeano, 2024. "Data for Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection," Data, MDPI, vol. 9(6), pages 1-8, June.
    • Handle: RePEc:gam:jdataj:v:9:y:2024:i:6:p:80-:d:1413933
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/9/6/80/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/9/6/80/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Patrick Huber & Melvin Ott & Martin Friedli & Andreas Rumsch & Andrew Paice, 2020. "Residential Power Traces for Five Houses: The iHomeLab RAPT Dataset," Data, MDPI, vol. 5(1), pages 1-14, February.
    2. Andrey Karpachevskiy & German Titov & Oksana Filippova, 2021. "Development of A Spatiotemporal Database for Evolution Analysis of the Moscow Backbone Power Grid," Data, MDPI, vol. 6(12), pages 1-14, November.
    3. Talaat, M. & Hatata, A.Y. & Alsayyari, Abdulaziz S. & Alblawi, Adel, 2020. "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, Elsevier, vol. 190(C).
    Full references (including those not matched with items on IDEAS)

    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. Rambabu Muppidi & Ramakrishna S. S. Nuvvula & S. M. Muyeen & SK. A. Shezan & Md. Fatin Ishraque, 2022. "Optimization of a Fuel Cost and Enrichment of Line Loadability for a Transmission System by Using Rapid Voltage Stability Index and Grey Wolf Algorithm Technique," Sustainability, MDPI, vol. 14(7), pages 1-19, April.
    2. Sheha, Moataz & Mohammadi, Kasra & Powell, Kody, 2021. "Techno-economic analysis of the impact of dynamic electricity prices on solar penetration in a smart grid environment with distributed energy storage," Applied Energy, Elsevier, vol. 282(PA).
    3. Fan, Dongming & Ren, Yi & Feng, Qiang & Liu, Yiliu & Wang, Zili & Lin, Jing, 2021. "Restoration of smart grids: Current status, challenges, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    4. Lei Yao & Jinhao Wang & Chen Zhao, 2024. "Non-Intrusive Load Monitoring Based on Multiscale Attention Mechanisms," Energies, MDPI, vol. 17(8), pages 1-23, April.
    5. Hazwani Mohd Rosli & Hazlie Mokhlis & Nurulafiqah Nadzirah Mansor & Norazliani Md Sapari & Syahirah Abd Halim & Li Wang & Mohamad Fani Sulaima, 2023. "A Binary Archimedes Optimization Algorithm and Weighted Sum Method for UFLS in Islanded Distribution Systems Considering the Stability Index and Load Priority," Energies, MDPI, vol. 16(13), pages 1-21, July.
    6. Antans Sauhats & Andrejs Utans & Jurijs Silinevics & Gatis Junghans & Dmitrijs Guzs, 2021. "Enhancing Power System Frequency with a Novel Load Shedding Method Including Monitoring of Synchronous Condensers’ Power Injections," Energies, MDPI, vol. 14(5), pages 1-21, March.
    7. Santiago Bustamante-Mesa & Jorge W. Gonzalez-Sanchez & Sergio D. Saldarriaga-Zuluaga & Jesús M. López-Lezama & Nicolás Muñoz-Galeano, 2024. "Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection," Energies, MDPI, vol. 17(2), pages 1-20, January.
    8. Talaat, M. & Farahat, M.A. & Mansour, Noura & Hatata, A.Y., 2020. "Load forecasting based on grasshopper optimization and a multilayer feed-forward neural network using regressive approach," Energy, Elsevier, vol. 196(C).
    9. Mahdiyeh Eslami & Mehdi Neshat & Saifulnizam Abd. Khalid, 2022. "A Novel Hybrid Sine Cosine Algorithm and Pattern Search for Optimal Coordination of Power System Damping Controllers," Sustainability, MDPI, vol. 14(1), pages 1-27, January.
    10. Ying-Yi Hong & Chih-Yang Hsiao, 2021. "Event-Based Under-Frequency Load Shedding Scheme in a Standalone Power System," Energies, MDPI, vol. 14(18), pages 1-19, September.
    11. Margherita Povolato & Alessandro Prada & Sara Verones & Paolo Baggio, 2022. "On the Effect of the Time Interval Base and Home Appliance on the Renewable Quota of a Building in an Alpine Location," Energies, MDPI, vol. 16(1), pages 1-13, 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:jdataj:v:9:y:2024:i:6:p:80-:d:1413933. 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.