IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i6p1456-d334797.html
   My bibliography  Save this article

Underfrequency Load Shedding: An Innovative Algorithm Based on Fuzzy Logic

Author

Listed:
  • Robert Małkowski

    (Gdańsk University of Technology, 11/12 Gabriela Narutowicza Street, 80-233 Gdańsk, Poland)

  • Janusz Nieznański

    (Gdańsk University of Technology, 11/12 Gabriela Narutowicza Street, 80-233 Gdańsk, Poland)

Abstract

In contemporary power systems, the load shedding schemes are typically based on disconnecting a pre-specified amount of load after the frequency drops below a predetermined value. The actual conditions at the time of disturbance may largely differ from the assumptions, which can lead to non-optimal or ineffective operation of the load shedding scheme. For many years, increasing the effectiveness of the underfrequency load shedding (UFLS) schemes has been the subject of research around the world. Unfortunately, the proposed solutions often require costly technical resources and/or large amounts of real-time data monitoring. This paper puts forth an UFLS scheme characterized by increased effectiveness in the case of large disturbances and reduced disconnected power in the case of small and medium disturbances compared to the conventional load-shedding solutions. These advantages are achieved by replacing time-consuming consecutive load dropping with the simultaneous load dropping mechanism and by replacing ineffective fixed-frequency activation thresholds independent of the state of the system with implicit adaptive thresholds based on fuzzy logic computations. The proposed algorithm does not require complex and costly technical solutions. The performance of the proposed scheme was validated using multivariate computer simulations. Selected test results are included in this paper.

Suggested Citation

  • Robert Małkowski & Janusz Nieznański, 2020. "Underfrequency Load Shedding: An Innovative Algorithm Based on Fuzzy Logic," Energies, MDPI, vol. 13(6), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:6:p:1456-:d:334797
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/6/1456/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/6/1456/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jafar Jallad & Saad Mekhilef & Hazlie Mokhlis & Javed Laghari & Ola Badran, 2018. "Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation," Energies, MDPI, vol. 11(5), pages 1-25, May.
    2. Shun Li & Fei Tang & Youguo Shao & Qingfen Liao, 2017. "Adaptive Under-Frequency Load Shedding Scheme in System Integrated with High Wind Power Penetration: Impacts and Improvements," Energies, MDPI, vol. 10(9), pages 1-16, September.
    3. Mohammad Dreidy & Hazlie Mokhlis & Saad Mekhilef, 2017. "Application of Meta-Heuristic Techniques for Optimal Load Shedding in Islanded Distribution Network with High Penetration of Solar PV Generation," Energies, MDPI, vol. 10(2), pages 1-24, January.
    4. Qi Wang & Yi Tang & Feng Li & Mengya Li & Yang Li & Ming Ni, 2016. "Coordinated Scheme of Under-Frequency Load Shedding with Intelligent Appliances in a Cyber Physical Power System," Energies, MDPI, vol. 9(8), pages 1-14, August.
    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. Skrjanc, T. & Mihalic, R. & Rudez, U., 2023. "A systematic literature review on under-frequency load shedding protection using clustering methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 180(C).
    2. Shun Li & Fei Tang & Youguo Shao & Qingfen Liao, 2017. "Adaptive Under-Frequency Load Shedding Scheme in System Integrated with High Wind Power Penetration: Impacts and Improvements," Energies, MDPI, vol. 10(9), pages 1-16, September.
    3. Sheng Li & Zhinong Wei & Yanan Ma, 2018. "Fuzzy Load-Shedding Strategy Considering Photovoltaic Output Fluctuation Characteristics and Static Voltage Stability," Energies, MDPI, vol. 11(4), pages 1-18, March.
    4. Lutfu Saribulut & Gorkem Ok & Arman Ameen, 2023. "A Case Study on National Electricity Blackout of Turkey," Energies, MDPI, vol. 16(11), pages 1-20, May.
    5. Hazlee Azil Illias & Wee Zhao Liang, 2018. "Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-15, January.
    6. Denis Sodin & Rajne Ilievska & Andrej Čampa & Miha Smolnikar & Urban Rudez, 2020. "Proving a Concept of Flexible Under-Frequency Load Shedding with Hardware-in-the-Loop Testing," Energies, MDPI, vol. 13(14), pages 1-17, July.
    7. Olumuyiwa T. Amusan & Nnamdi I. Nwulu & Saheed Lekan Gbadamosi, 2022. "Identification of Weak Buses for Optimal Load Shedding Using Differential Evolution," Sustainability, MDPI, vol. 14(6), pages 1-12, March.
    8. Ifedayo Oladeji & Ramon Zamora & Tek Tjing Lie, 2021. "An Online Security Prediction and Control Framework for Modern Power Grids," Energies, MDPI, vol. 14(20), pages 1-27, October.
    9. Florin-Constantin Baiceanu & Ovidiu Ivanov & Razvan-Constantin Beniuga & Bogdan-Constantin Neagu & Ciprian-Mircea Nemes, 2023. "A Continuous Multistage Load Shedding Algorithm for Industrial Processes Based on Metaheuristic Optimization," Mathematics, MDPI, vol. 11(12), pages 1-19, June.
    10. Mohammad Dreidy & Hazlie Mokhlis & Saad Mekhilef, 2017. "Application of Meta-Heuristic Techniques for Optimal Load Shedding in Islanded Distribution Network with High Penetration of Solar PV Generation," Energies, MDPI, vol. 10(2), pages 1-24, January.
    11. Laura M. Cruz & David L. Alvarez & Ameena S. Al-Sumaiti & Sergio Rivera, 2020. "Load Curtailment Optimization Using the PSO Algorithm for Enhancing the Reliability of Distribution Networks," Energies, MDPI, vol. 13(12), pages 1-15, June.
    12. Jafar Jallad & Saad Mekhilef & Hazlie Mokhlis & Javed Laghari & Ola Badran, 2018. "Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation," Energies, MDPI, vol. 11(5), pages 1-25, May.
    13. Kuihua Wu & Kun Li & Rong Liang & Runze Ma & Yuxuan Zhao & Jian Wang & Lujie Qi & Shengyuan Liu & Chang Han & Li Yang & Minxiang Huang, 2018. "A Joint Planning Method for Substations and Lines in Distribution Systems Based on the Parallel Bird Swarm Algorithm," Energies, MDPI, vol. 11(10), pages 1-14, October.
    14. 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.
    15. Sohail Sarwar & Hazlie Mokhlis & Mohamadariff Othman & Munir Azam Muhammad & J. A. Laghari & Nurulafiqah Nadzirah Mansor & Hasmaini Mohamad & Alireza Pourdaryaei, 2020. "A Mixed Integer Linear Programming Based Load Shedding Technique for Improving the Sustainability of Islanded Distribution Systems," Sustainability, MDPI, vol. 12(15), pages 1-23, August.
    16. Kai Wang & Lixia Kang & Songhao Yang, 2022. "A Coordination Optimization Method for Load Shedding Considering Distribution Network Reconfiguration," Energies, MDPI, vol. 15(21), pages 1-18, November.

    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:13:y:2020:i:6:p:1456-:d:334797. 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.