IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i12p4395-d840502.html
   My bibliography  Save this article

Fuzzy Dynamic Thermal Rating System-Based Thermal Aging Model for Transmission Lines

Author

Listed:
  • Yasir Yaqoob

    (School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), Nibong Tebal 14300, Malaysia)

  • Arjuna Marzuki

    (School of Science and Technology, Wawasan Open University, George Town 10050, Malaysia)

  • Ching-Ming Lai

    (Department of Electrical Engineering, National Chung Hsing University (NCHU), 145 Xing Da Road, South District, Taichung 402, Taiwan)

  • Jiashen Teh

    (School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), Nibong Tebal 14300, Malaysia)

Abstract

Electricity demand has surged over the last several years and will persist in the future. Increased transmission loads cause transmission lines to operate much closer to their security limits, leading to thermal and mechanical stress and thus affecting the transmission reliability and thermal aging. Accordingly, monitoring the conductor temperature over time is critical to identifying power transmission networks that may need extra attention and perhaps maintenance. This paper presents a fuzzy thermal aging model for transmission lines equipped with a fuzzy dynamic thermal rating system based on the IEEE 738 standard. In this framework, the ampacity of the transmission line was calculated. The conductor temperature was computed with the back-calculation method by considering the fully loaded transmission line. The estimated conductor temperature was employed to determine the corresponding conductor fuzzy loss of tensile strength, i.e., the fuzzy annealing degree of the conductor based on the Harvey model. Additionally, a tensile strength loss cost profile is provided. Simulation and numerical results indicate that the proposed framework is robust against various operating conditions of the parameters considered in the study and provides crucial information for managing transmission assets and transmission network operation.

Suggested Citation

  • Yasir Yaqoob & Arjuna Marzuki & Ching-Ming Lai & Jiashen Teh, 2022. "Fuzzy Dynamic Thermal Rating System-Based Thermal Aging Model for Transmission Lines," Energies, MDPI, vol. 15(12), pages 1-23, June.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4395-:d:840502
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/12/4395/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/12/4395/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiashen Teh & Ching-Ming Lai & Yu-Huei Cheng, 2018. "Improving the Penetration of Wind Power with Dynamic Thermal Rating System, Static VAR Compensator and Multi-Objective Genetic Algorithm," Energies, MDPI, vol. 11(4), pages 1-16, April.
    2. Lai, Ching-Ming & Teh, Jiashen, 2022. "Network topology optimisation based on dynamic thermal rating and battery storage systems for improved wind penetration and reliability," Applied Energy, Elsevier, vol. 305(C).
    3. F. Gülşen Erdinç & Ozan Erdinç & Recep Yumurtacı & João P. S. Catalão, 2020. "A Comprehensive Overview of Dynamic Line Rating Combined with Other Flexibility Options from an Operational Point of View," Energies, MDPI, vol. 13(24), pages 1-30, December.
    4. Ildar Daminov & Rémy Rigo-Mariani & Raphael Caire & Anton Prokhorov & Marie-Cécile Alvarez-Hérault, 2021. "Demand Response Coupled with Dynamic Thermal Rating for Increased Transformer Reserve and Lifetime," Energies, MDPI, vol. 14(5), pages 1-27, March.
    5. Chiodo, Elio & Lauria, Davide & Mottola, Fabio & Pisani, Cosimo, 2016. "Lifetime characterization via lognormal distribution of transformers in smart grids: Design optimization," Applied Energy, Elsevier, vol. 177(C), pages 127-135.
    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. Mohamed Khamies & Salah Kamel & Mohamed H. Hassan & Mohamed F. Elnaggar, 2022. "A Developed Frequency Control Strategy for Hybrid Two-Area Power System with Renewable Energy Sources Based on an Improved Social Network Search Algorithm," Mathematics, MDPI, vol. 10(9), pages 1-31, May.
    2. Giri, Binoy Krishna & Roy, Sankar Kumar, 2024. "Fuzzy-random robust flexible programming on sustainable closed-loop renewable energy supply chain," Applied Energy, Elsevier, vol. 363(C).
    3. Ramitha Dissanayake & Akila Wijethunge & Janaka Wijayakulasooriya & Janaka Ekanayake, 2022. "Optimizing PV-Hosting Capacity with the Integrated Employment of Dynamic Line Rating and Voltage Regulation," Energies, MDPI, vol. 15(22), pages 1-19, November.
    4. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2023. "Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy," Applied Energy, Elsevier, vol. 349(C).
    5. Behzad Keyvani & Eoin Whelan & Eadaoin Doddy & Damian Flynn, 2023. "Indirect weather‐based approaches for increasing power transfer capabilities of electrical transmission networks," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(3), May.
    6. Ildar Daminov & Rémy Rigo-Mariani & Raphael Caire & Anton Prokhorov & Marie-Cécile Alvarez-Hérault, 2021. "Demand Response Coupled with Dynamic Thermal Rating for Increased Transformer Reserve and Lifetime," Energies, MDPI, vol. 14(5), pages 1-27, March.
    7. Yu Su & Niancheng Zhou & Qianggang Wang & Chao Lei & Jian Fang, 2018. "Optimal Planning Method of On-load Capacity Regulating Distribution Transformers in Urban Distribution Networks after Electric Energy Replacement Considering Uncertainties," Energies, MDPI, vol. 11(6), pages 1-25, June.
    8. Lin, Yu-Hsiu & Shen, Ting-Yu, 2023. "Novel cell screening and prognosing based on neurocomputing-based multiday-ahead time-series forecasting for predictive maintenance of battery modules in frequency regulation-energy storage systems," Applied Energy, Elsevier, vol. 351(C).
    9. Jeff Laninga & Ali Nasr Esfahani & Gevindu Ediriweera & Nathan Jacob & Behzad Kordi, 2023. "Monitoring Technologies for HVDC Transmission Lines," Energies, MDPI, vol. 16(13), pages 1-32, June.
    10. Paolo Sospiro & Lohith Amarnath & Vincenzo Di Nardo & Giacomo Talluri & Foad H. Gandoman, 2021. "Smart Grid in China, EU, and the US: State of Implementation," Energies, MDPI, vol. 14(18), pages 1-16, September.
    11. Meng, He & Jia, Hongjie & Xu, Tao & Wei, Wei & Wu, Yuhan & Liang, Lemeng & Cai, Shuqi & Liu, Zuozheng & Wang, Rujing & Li, Mengchao, 2022. "Optimal configuration of cooperative stationary and mobile energy storage considering ambient temperature: A case for Winter Olympic Game," Applied Energy, Elsevier, vol. 325(C).
    12. Qiao, Qiao & Zeng, Xianhai & Lin, Boqiang, 2024. "Mitigating wind curtailment risk in China: The impact of subsidy reduction policy," Applied Energy, Elsevier, vol. 368(C).
    13. Diana Enescu & Pietro Colella & Angela Russo & Radu Florin Porumb & George Calin Seritan, 2021. "Concepts and Methods to Assess the Dynamic Thermal Rating of Underground Power Cables," Energies, MDPI, vol. 14(9), pages 1-23, May.
    14. Megersa Tesfaye Boke & Semu Ayalew Moges & Zeleke Agide Dejen, 2022. "Optimizing renewable-based energy supply options for power generation in Ethiopia," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-15, January.
    15. Levente Rácz & Bálint Németh & Gábor Göcsei & Dimitar Zarchev & Valeri Mladenov, 2022. "Performance Analysis of a Dynamic Line Rating System Based on Project Experiences," Energies, MDPI, vol. 15(3), pages 1-11, January.
    16. Glaum, Philipp & Hofmann, Fabian, 2023. "Leveraging the existing German transmission grid with dynamic line rating," Applied Energy, Elsevier, vol. 343(C).
    17. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Amir Mansouri, Seyed & Jurado, Francisco, 2022. "Day-ahead scheduling of 100% isolated communities under uncertainties through a novel stochastic-robust model," Applied Energy, Elsevier, vol. 328(C).
    18. Pedro Faria & Zita Vale, 2023. "Demand Response in Smart Grids," Energies, MDPI, vol. 16(2), pages 1-3, January.
    19. Mansouri, Seyed Amir & Nematbakhsh, Emad & Jordehi, Ahmad Rezaee & Marzband, Mousa & Tostado-Véliz, Marcos & Jurado, Francisco, 2023. "An interval-based nested optimization framework for deriving flexibility from smart buildings and electric vehicle fleets in the TSO-DSO coordination," Applied Energy, Elsevier, vol. 341(C).
    20. Raquel Martinez & Mario Manana & Alberto Arroyo & Sergio Bustamante & Alberto Laso & Pablo Castro & Rafael Minguez, 2021. "Dynamic Rating Management of Overhead Transmission Lines Operating under Multiple Weather Conditions," Energies, MDPI, vol. 14(4), pages 1-21, February.

    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:2022:i:12:p:4395-:d:840502. 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.