IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i20p7122-d1261557.html
   My bibliography  Save this article

Development of Methods for an Overhead Cable Health Index Evaluation That Considers Economic Feasibility

Author

Listed:
  • Hyeseon Lee

    (Distribution Power Laboratory, KEPCO Research Institute, Daejeon 34056, Republic of Korea)

  • Byungsung Lee

    (Distribution Power Laboratory, KEPCO Research Institute, Daejeon 34056, Republic of Korea)

  • Gyurim Han

    (Department of Electrical Engineering, Incheon National University, Incheon 22012, Republic of Korea)

  • Yuri Kim

    (Department of Electrical Engineering, Incheon National University, Incheon 22012, Republic of Korea)

  • Yongha Kim

    (Department of Electrical Engineering, Incheon National University, Incheon 22012, Republic of Korea)

Abstract

To supply stable and high-quality power according to the advancement of industrial growth, electric power companies have performed maintenance of power facilities using various methods. In the case of domestic power distribution facilities, there are limitations in performing diagnostic management on all facilities owing to the large number of facilities; therefore, old facilities are managed using the health index assessment method. The health index assessment comprises only facility operation data and external environmental data and is managed only for four types of distribution facilities including overhead/underground transformers and switchgears. In the case of high voltage overhead lines, there are a large number of wires such as transformers and switchgears connected to the lines, and the ripple effect of power outages is large. However, in Korea, there is no overhead line health index standard. In overseas cases, a health index for overhead lines was developed, but only the material characteristics and surrounding environment of the overhead lines were considered and economic feasibility was not considered. Therefore, in this paper, we developed a health index evaluation methodology for ultra-high voltage overhead lines that considers economic feasibility. In this paper, unlike the existing health index evaluation method that uses only operational data and external environmental data to determine facility performance evaluation and aging replacement standards, we developed an economic health index evaluation methodology that additionally considers failure probability and risk costs. Using the health index assessment methodology developed in this paper, it is possible to expect a reduction in facility operating costs and investment costs from the perspective of the electric power companies through the replacement of old extra-high voltage overhead cables. In addition, from the perspective of consumers, it is expected to increase power reliability and reduce the ripple effect of failure by preferentially replacing equipment with a high probability of failure.

Suggested Citation

  • Hyeseon Lee & Byungsung Lee & Gyurim Han & Yuri Kim & Yongha Kim, 2023. "Development of Methods for an Overhead Cable Health Index Evaluation That Considers Economic Feasibility," Energies, MDPI, vol. 16(20), pages 1-13, October.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7122-:d:1261557
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/20/7122/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/20/7122/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Muhammad Sharil Yahaya & Norhafiz Azis & Mohd Zainal Abidin Ab Kadir & Jasronita Jasni & Mohd Hendra Hairi & Mohd Aizam Talib, 2017. "Estimation of Transformers Health Index Based on the Markov Chain," Energies, MDPI, vol. 10(11), pages 1-11, November.
    2. Emran Jawad Kadim & Norhafiz Azis & Jasronita Jasni & Siti Anom Ahmad & Mohd Aizam Talib, 2018. "Transformers Health Index Assessment Based on Neural-Fuzzy Network," Energies, MDPI, vol. 11(4), pages 1-14, March.
    3. Ruqayyah Hashim & Fathoni Usman & Intan Nor Zuliana Baharuddin, 2019. "Determining Health Index of Transmission Line Asset using Condition-Based Method," Resources, MDPI, vol. 8(2), pages 1-14, April.
    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. Jun Yu & Zhijian Zhang & Weifeng Ren & Dongxing Yang & Dian Wu & Zhiqiang Ning & Chunhua Fang & Junxiong Wu, 2024. "Aging Analysis of Semiconductive Silicone Rubber for 10 kV Cold-Shrink Cable Accessories," Energies, MDPI, vol. 17(3), pages 1-18, February.

    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. Patryk Bohatyrewicz & Andrzej Mrozik, 2021. "The Analysis of Power Transformer Population Working in Different Operating Conditions with the Use of Health Index," Energies, MDPI, vol. 14(16), pages 1-14, August.
    2. Nguyen Thanh Viet & Alla G. Kravets, 2022. "The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management," Energies, MDPI, vol. 15(18), pages 1-26, September.
    3. Georgi Ivanov & Anelia Spasova & Valentin Mateev & Iliana Marinova, 2023. "Applied Complex Diagnostics and Monitoring of Special Power Transformers," Energies, MDPI, vol. 16(5), pages 1-24, February.
    4. Muhammad Sharil Yahaya & Norhafiz Azis & Amran Mohd Selva & Mohd Zainal Abidin Ab Kadir & Jasronita Jasni & Emran Jawad Kadim & Mohd Hendra Hairi & Young Zaidey Yang Ghazali, 2018. "A Maintenance Cost Study of Transformers Based on Markov Model Utilizing Frequency of Transition Approach," Energies, MDPI, vol. 11(8), pages 1-14, August.
    5. Oussama Laayati & Hicham El Hadraoui & Adila El Magharaoui & Nabil El-Bazi & Mostafa Bouzi & Ahmed Chebak & Josep M. Guerrero, 2022. "An AI-Layered with Multi-Agent Systems Architecture for Prognostics Health Management of Smart Transformers: A Novel Approach for Smart Grid-Ready Energy Management Systems," Energies, MDPI, vol. 15(19), pages 1-28, October.
    6. Muhammad Sharil Yahaya & Norhafiz Azis & Amran Mohd Selva & Mohd Zainal Abidin Ab Kadir & Jasronita Jasni & Mohd Hendra Hairi & Young Zaidey Yang Ghazali & Mohd Aizam Talib, 2018. "Effect of Pre-Determined Maintenance Repair Rates on the Health Index State Distribution and Performance Condition Curve Based on the Markov Prediction Model for Sustainable Transformers Asset Managem," Sustainability, MDPI, vol. 10(10), pages 1-13, September.
    7. Cattareeya Suwanasri & Ittiphong Yongyee & Thanapong Suwanasri, 2024. "Age Estimation of Transmission Line Using Statistical Health Index and Failure Probability Curve-Fitting Method," Energies, MDPI, vol. 17(3), pages 1-17, January.
    8. Alhaytham Alqudsi & Ayman El-Hag, 2019. "Application of Machine Learning in Transformer Health Index Prediction," Energies, MDPI, vol. 12(14), pages 1-13, July.

    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:16:y:2023:i:20:p:7122-:d:1261557. 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.