IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v10y2019i4d10.1007_s13198-018-0712-2.html
   My bibliography  Save this article

Distance relay reliability enhancement using false trip root cause analysis

Author

Listed:
  • Abdelkader Zitouni

    (University of M’hamed Bougara)

  • Abderrahmane Ouadi

    (University of M’hamed Bougara)

  • Hamid Bentarzi

    (University of M’hamed Bougara)

  • Mahfoud Chafai

    (University of M’hamed Bougara)

Abstract

A distance relay, which is widely used for protecting a power transmission line as the primary as well as remote backup device, may be affected by the power disturbances such as power swings and post-faults. Consequently, false trips of protection system may be resulted. Root cause analysis based on fault tree analysis has been used to identify disturbances which may lead to false trips. Once the critical root causes have been identified, conventional mitigation measures are used and then, new blocking function and digital filters are proposed to enhance the security of the system. The quantitative analysis of the improved model shows a significant increase in the security which implies an appreciable enhancement of the reliability of the considered protection system.

Suggested Citation

  • Abdelkader Zitouni & Abderrahmane Ouadi & Hamid Bentarzi & Mahfoud Chafai, 2019. "Distance relay reliability enhancement using false trip root cause analysis," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(4), pages 475-483, August.
    • Handle: RePEc:spr:ijsaem:v:10:y:2019:i:4:d:10.1007_s13198-018-0712-2
    DOI: 10.1007/s13198-018-0712-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-018-0712-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-018-0712-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Valipour, Mohammad & Gholami Sefidkouhi, Mohammad Ali & Raeini−Sarjaz, Mahmoud, 2017. "Selecting the best model to estimate potential evapotranspiration with respect to climate change and magnitudes of extreme events," Agricultural Water Management, Elsevier, vol. 180(PA), pages 50-60.
    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. Shiva Moslemi & Mohammad Hossein Zavvar Sabegh & Abolfazl Mirzazadeh & Yucel Ozturkoglu & Eric Maass, 2017. "A multi-objective model for multi-production and multi-echelon closed-loop pharmaceutical supply chain considering quality concepts: NSGAII approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1717-1733, November.
    2. Amaresh Sarkar & Mrinmoy Majumder, 2019. "Real-time monitoring of water requirement in protected farms by using polynomial neural networks and image processing," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(3), pages 1451-1483, June.
    3. Xiang, Keyu & Li, Yi & Horton, Robert & Feng, Hao, 2020. "Similarity and difference of potential evapotranspiration and reference crop evapotranspiration – a review," Agricultural Water Management, Elsevier, vol. 232(C).
    4. Granata, Francesco, 2019. "Evapotranspiration evaluation models based on machine learning algorithms—A comparative study," Agricultural Water Management, Elsevier, vol. 217(C), pages 303-315.
    5. Yang, Yong & Chen, Rensheng & Han, Chuntan & Liu, Zhangwen, 2021. "Evaluation of 18 models for calculating potential evapotranspiration in different climatic zones of China," Agricultural Water Management, Elsevier, vol. 244(C).
    6. Xueping Zhu & Chi Zhang & Guangtao Fu & Yu Li & Wei Ding, 2017. "Bi-Level Optimization for Determining Operating Strategies for Inter-Basin Water Transfer-Supply Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4415-4432, November.
    7. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    8. Xiao, Chunan & Cai, Jiabing & Zhang, Baozhong & Chang, Hongfang & Wei, Zheng, 2023. "Evaluation and verification of two evapotranspiration models based on precision screening and partitioning of field temperature data," Agricultural Water Management, Elsevier, vol. 278(C).
    9. Zhao, Xiancong & Bai, Hao & Shi, Qi & Lu, Xin & Zhang, Zhihui, 2017. "Optimal scheduling of a byproduct gas system in a steel plant considering time-of-use electricity pricing," Applied Energy, Elsevier, vol. 195(C), pages 100-113.
    10. Peddinti, Srinivasa Rao & Kambhammettu, BVN P, 2019. "Dynamics of crop coefficients for citrus orchards of central India using water balance and eddy covariance flux partition techniques," Agricultural Water Management, Elsevier, vol. 212(C), pages 68-77.
    11. Shirmohammadi-Aliakbarkhani, Zahra & Saberali, Seyed Farhad, 2020. "Evaluating of eight evapotranspiration estimation methods in arid regions of Iran," Agricultural Water Management, Elsevier, vol. 239(C).
    12. Su, Qiong & Singh, Vijay P. & Karthikeyan, Raghupathy, 2022. "Improved reference evapotranspiration methods for regional irrigation water demand estimation," Agricultural Water Management, Elsevier, vol. 274(C).
    13. Dong, Juan & Xing, Liwen & Cui, Ningbo & Guo, Li & Liang, Chuan & Zhao, Lu & Wang, Zhihui & Gong, Daozhi, 2024. "Estimating reference crop evapotranspiration using optimized empirical methods with a novel improved Grey Wolf Algorithm in four climatic regions of China," Agricultural Water Management, Elsevier, vol. 291(C).
    14. Kostić, Srđan & Vasović, Nebojša & Todorović, Kristina & Franović, Igor, 2018. "Nonlinear dynamics behind the seismic cycle: One-dimensional phenomenological modeling," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 310-316.
    15. Lei Tian & Jiming Jin & Pute Wu & Guo-yue Niu, 2018. "Assessment of the Effects of Climate Change on Evapotranspiration with an Improved Elasticity Method in a Nonhumid Area," Sustainability, MDPI, vol. 10(12), pages 1-17, 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:spr:ijsaem:v:10:y:2019:i:4:d:10.1007_s13198-018-0712-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.