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Forecasting for dynamic line rating

Author

Listed:
  • Michiorri, Andrea
  • Nguyen, Huu-Minh
  • Alessandrini, Stefano
  • Bremnes, John Bjørnar
  • Dierer, Silke
  • Ferrero, Enrico
  • Nygaard, Bjørn-Egil
  • Pinson, Pierre
  • Thomaidis, Nikolaos
  • Uski, Sanna

Abstract

This paper presents an overview of the state of the art on the research on Dynamic Line Rating forecasting. It is directed at researchers and decision-makers in the renewable energy and smart grids domain, and in particular at members of both the power system and meteorological community. Its aim is to explain the details of one aspect of the complex interconnection between the environment and power systems.

Suggested Citation

  • Michiorri, Andrea & Nguyen, Huu-Minh & Alessandrini, Stefano & Bremnes, John Bjørnar & Dierer, Silke & Ferrero, Enrico & Nygaard, Bjørn-Egil & Pinson, Pierre & Thomaidis, Nikolaos & Uski, Sanna, 2015. "Forecasting for dynamic line rating," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1713-1730.
    • Handle: RePEc:eee:rensus:v:52:y:2015:i:c:p:1713-1730
    DOI: 10.1016/j.rser.2015.07.134
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    References listed on IDEAS

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    Cited by:

    1. Akhlaghi, M. & Moravej, Z. & Bagheri, A., 2022. "Maximizing wind energy utilization in smart power systems using a flexible network-constrained unit commitment through dynamic lines and transformers rating," Energy, Elsevier, vol. 261(PA).
    2. José Agüero-Rubio & Javier López-Martínez & Marta Gómez-Galán & Ángel-Jesús Callejón-Ferre, 2020. "A Didactic Procedure to Solve the Equation of Steady-Static Response in Suspended Cables," Mathematics, MDPI, vol. 8(9), pages 1-19, September.
    3. Glaum, Philipp & Hofmann, Fabian, 2023. "Leveraging the existing German transmission grid with dynamic line rating," Applied Energy, Elsevier, vol. 343(C).
    4. Bracale, Antonio & Carpinelli, Guido & De Falco, Pasquale, 2017. "A new finite mixture distribution and its expectation-maximization procedure for extreme wind speed characterization," Renewable Energy, Elsevier, vol. 113(C), pages 1366-1377.
    5. Phillips, Tyler & DeLeon, Rey & Senocak, Inanc, 2017. "Dynamic rating of overhead transmission lines over complex terrain using a large-eddy simulation paradigm," Renewable Energy, Elsevier, vol. 108(C), pages 380-389.
    6. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    7. Romain Dupin & Laura Cavalcante & Ricardo J. Bessa & Georges Kariniotakis & Andrea Michiorri, 2020. "Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation," Energies, MDPI, vol. 13(12), pages 1-21, June.
    8. 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.
    9. Zhao Liu & Honglei Deng & Ruidong Peng & Xiangyang Peng & Rui Wang & Wencheng Zheng & Pengyu Wang & Deming Guo & Gang Liu, 2020. "An Equivalent Heat Transfer Model Instead of Wind Speed Measuring for Dynamic Thermal Rating of Transmission Lines," Energies, MDPI, vol. 13(18), pages 1-18, September.
    10. Karimi, Soheila & Musilek, Petr & Knight, Andrew M., 2018. "Dynamic thermal rating of transmission lines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 600-612.
    11. Fan Song & Yanling Wang & Hongbo Yan & Xiaofeng Zhou & Zhiqiang Niu, 2019. "Increasing the Utilization of Transmission Lines Capacity by Quasi-Dynamic Thermal Ratings," Energies, MDPI, vol. 12(5), pages 1-13, February.

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