IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2021i1p199-d713379.html
   My bibliography  Save this article

Probability-Based Customizable Modeling and Simulation of Protective Devices in Power Distribution Systems

Author

Listed:
  • Chengwei Lei

    (The Department of Computer and Electrical Engineering and Computer Science, California State University Bakersfield, Bakersfield, CA 93311, USA)

  • Weisong Tian

    (The Department of Electrical Engineering, Widener University, Chester, PA 19013, USA)

Abstract

Fused contactors and thermal magnetic circuit breakers are commonly applied protective devices in power distribution systems to protect the circuits when short-circuit faults occur. A power distribution system may contain various makes and models of protective devices, as a result, customizable simulation models for protective devices are demanded to effectively conduct system-level reliable analyses. To build the models, thermal energy-based data analysis methodologies are first applied to the protective devices’ physical properties, based on the manufacturer’s time/current data sheet. The models are further enhanced by integrating probability tools to simulate uncertainties in real-world application facts, for example, fortuity, variance, and failure rate. The customizable models are expected to aid the system-level reliability analysis, especially for the microgrid power systems.

Suggested Citation

  • Chengwei Lei & Weisong Tian, 2021. "Probability-Based Customizable Modeling and Simulation of Protective Devices in Power Distribution Systems," Energies, MDPI, vol. 15(1), pages 1-15, December.
  • Handle: RePEc:gam:jeners:v:15:y:2021:i:1:p:199-:d:713379
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/1/199/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/1/199/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carnero, María Carmen & Gómez, Andrés, 2017. "Maintenance strategy selection in electric power distribution systems," Energy, Elsevier, vol. 129(C), pages 255-272.
    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. Maria Psillaki & Nikolaos Apostolopoulos & Ilias Makris & Panagiotis Liargovas & Sotiris Apostolopoulos & Panos Dimitrakopoulos & George Sklias, 2023. "Hospitals’ Energy Efficiency in the Perspective of Saving Resources and Providing Quality Services through Technological Options: A Systematic Literature Review," Energies, MDPI, vol. 16(2), pages 1-21, January.
    2. LaCommare, Kristina Hamachi & Eto, Joseph H. & Dunn, Laurel N. & Sohn, Michael D., 2018. "Improving the estimated cost of sustained power interruptions to electricity customers," Energy, Elsevier, vol. 153(C), pages 1038-1047.
    3. Fahime Lotfian Delouyi & Seyed Hassan Ghodsypour & Maryam Ashrafi, 2021. "Dynamic Portfolio Selection in Gas Transmission Projects Considering Sustainable Strategic Alignment and Project Interdependencies through Value Analysis," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    4. Sidney Jose Meireles de Andrade & Plácido Rogério Pinheiro & Glauber Jean Alves Narciso & José Tarcisio Pimentel Neto & João Pedro da Silva Bandeira & Vinicius Sales de Andrade & Cayo Cid de França Mo, 2022. "Prioritising Maintenance Work Orders in a Thermal Power Plant: A Multicriteria Model Application," Sustainability, MDPI, vol. 15(1), pages 1-19, December.
    5. Shayesteh, E. & Yu, J. & Hilber, P., 2018. "Maintenance optimization of power systems with renewable energy sources integrated," Energy, Elsevier, vol. 149(C), pages 577-586.
    6. Toubeau, Jean-François & Pardoen, Lorie & Hubert, Louis & Marenne, Nicolas & Sprooten, Jonathan & De Grève, Zacharie & Vallée, François, 2022. "Machine learning-assisted outage planning for maintenance activities in power systems with renewables," Energy, Elsevier, vol. 238(PC).
    7. Ghasemi, Mostafa & Dashti, Reza, 2018. "Designing a decision model to assess the reward and penalty scheme of electric distribution companies," Energy, Elsevier, vol. 147(C), pages 329-336.
    8. Afzali, Peyman & Keynia, Farshid & Rashidinejad, Masoud, 2019. "A new model for reliability-centered maintenance prioritisation of distribution feeders," Energy, Elsevier, vol. 171(C), pages 701-709.

    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:2021:i:1:p:199-:d:713379. 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.