IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i7p2581-d785322.html
   My bibliography  Save this article

A Multi-Variable DTR Algorithm for the Estimation of Conductor Temperature and Ampacity on HV Overhead Lines by IoT Data Sensors

Author

Listed:
  • Rossana Coccia

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana, 18, 00184 Rome, Italy)

  • Veronica Tonti

    (TERNA S.p.A., Viale Egidio Galbani, 70, 00156 Rome, Italy)

  • Chiara Germanò

    (ELIS Innovation Hub, Via Sandro Sandri, 81, 00159 Rome, Italy)

  • Francesco Palone

    (TERNA S.p.A., Viale Egidio Galbani, 70, 00156 Rome, Italy)

  • Lorenzo Papi

    (TERNA S.p.A., Viale Egidio Galbani, 70, 00156 Rome, Italy)

  • Lorenzo Ricciardi Celsi

    (ELIS Innovation Hub, Via Sandro Sandri, 81, 00159 Rome, Italy)

Abstract

The transfer capabilities of High-Voltage Overhead Lines (HV OHLs) are often limited by the critical power line temperature that depends on the magnitude of the transferred current and the ambient conditions, i.e., ambient temperature, wind, etc. To utilize existing power lines more effectively (with a view to progressive decarbonization) and more safely with respect to the critical power line temperatures, this paper proposes a Dynamic Thermal Rating (DTR) approach using IoT sensors installed on some HV OHLs located in different Italian geographical locations. The goal is to estimate the OHL conductor temperature and ampacity, using a data-driven thermo-mechanical model with the Bayesian probability approach, in order to improve the confidence interval of the results. This work highlights that it could be possible to estimate a space-time distribution of temperature for each OHL and an increase in the actual current threshold values for optimizing OHL ampacity. The proposed model is validated using the Monte Carlo method.

Suggested Citation

  • Rossana Coccia & Veronica Tonti & Chiara Germanò & Francesco Palone & Lorenzo Papi & Lorenzo Ricciardi Celsi, 2022. "A Multi-Variable DTR Algorithm for the Estimation of Conductor Temperature and Ampacity on HV Overhead Lines by IoT Data Sensors," Energies, MDPI, vol. 15(7), pages 1-13, April.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2581-:d:785322
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/7/2581/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/7/2581/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hideharu Sugihara & Tsuyoshi Funaki & Nobuyuki Yamaguchi, 2017. "Evaluation Method for Real-Time Dynamic Line Ratings Based on Line Current Variation Model for Representing Forecast Error of Intermittent Renewable Generation," Energies, MDPI, vol. 10(4), pages 1-16, April.
    2. Nour Alhuda Sulieman & Lorenzo Ricciardi Celsi & Wei Li & Albert Zomaya & Massimo Villari, 2022. "Edge-Oriented Computing: A Survey on Research and Use Cases," Energies, MDPI, vol. 15(2), pages 1-28, January.
    3. Fabio Massaro & Mariano Giuseppe Ippolito & Gaetano Zizzo & Giovanni Filippone & Andrea Puccio, 2018. "Methodologies for the Exploitation of Existing Energy Corridors. GIS Analysis and DTR Applications," Energies, MDPI, vol. 11(4), pages 1-15, April.
    4. Eleonora Arena & Alessandro Corsini & Roberto Ferulano & Dario Alfio Iuvara & Eric Stefan Miele & Lorenzo Ricciardi Celsi & Nour Alhuda Sulieman & Massimo Villari, 2021. "Anomaly Detection in Photovoltaic Production Factories via Monte Carlo Pre-Processed Principal Component Analysis," Energies, MDPI, vol. 14(13), pages 1-16, July.
    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. Salvatore Favuzza & Mariano Giuseppe Ippolito & Fabio Massaro & Liliana Mineo & Rossano Musca & Gaetano Zizzo, 2018. "New Energy Corridors in the Euro-Mediterranean Area: The Pivotal Role of Sicily," Energies, MDPI, vol. 11(6), pages 1-14, June.
    2. Carlo Olivieri & Francesco de Paulis & Antonio Orlandi & Giorgio Giannuzzi & Roberto Salvati & Roberto Zaottini & Carlo Morandini & Lorenzo Mocarelli, 2019. "Remote Monitoring of Joints Status on In-Service High-Voltage Overhead Lines," Energies, MDPI, vol. 12(6), pages 1-17, March.
    3. Fabio Massaro & Mariano Giuseppe Ippolito & Gaetano Zizzo & Giovanni Filippone & Andrea Puccio, 2018. "Methodologies for the Exploitation of Existing Energy Corridors. GIS Analysis and DTR Applications," Energies, MDPI, vol. 11(4), pages 1-15, April.
    4. Jian Hu & Xiaofu Xiong & Jing Chen & Wei Wang & Jian Wang, 2018. "Transient Temperature Calculation and Multi-Parameter Thermal Protection of Overhead Transmission Lines Based on an Equivalent Thermal Network," Energies, MDPI, vol. 12(1), pages 1-25, December.
    5. Nan Shao & Yu Chen, 2022. "Abnormal Data Detection and Identification Method of Distribution Internet of Things Monitoring Terminal Based on Spatiotemporal Correlation," Energies, MDPI, vol. 15(6), pages 1-19, March.
    6. Mengxia Wang & Mingqiang Wang & Jinxin Huang & Zhe Jiang & Jinyan Huang, 2018. "A Thermal Rating Calculation Approach for Wind Power Grid-Integrated Overhead Lines," Energies, MDPI, vol. 11(6), pages 1-15, June.
    7. Tito G. Amaral & Vitor Fernão Pires & Armando J. Pires, 2021. "Fault Detection in PV Tracking Systems Using an Image Processing Algorithm Based on PCA," Energies, MDPI, vol. 14(21), pages 1-18, November.
    8. Chiara Martini & Claudia Toro, 2022. "Special Issue “Industry and Tertiary Sectors towards Clean Energy Transition”," Energies, MDPI, vol. 15(11), pages 1-5, June.

    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:7:p:2581-:d:785322. 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.