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Evaluation Method for Real-Time Dynamic Line Ratings Based on Line Current Variation Model for Representing Forecast Error of Intermittent Renewable Generation

Author

Listed:
  • Hideharu Sugihara

    (Division of Electrical, Electronic and Information Engineering, Graduate School of Engineering, Osaka University, Suita 565-0871, Japan)

  • Tsuyoshi Funaki

    (Division of Electrical, Electronic and Information Engineering, Graduate School of Engineering, Osaka University, Suita 565-0871, Japan)

  • Nobuyuki Yamaguchi

    (Department of Electrical Engineering, Faculty of Engineering Division, Tokyo University of Science, Tokyo 125-8585, Japan)

Abstract

Due the high penetration of intermittent renewable energy sources (IRESs), transmission line currents show large fluctuations and thus significant uncertainty. This makes it difficult to operate a power system without violating transmission capacity constraints. This paper evaluates the dynamic line ratings (DLRs) of overhead lines based on changes in the line current owing to the high penetration of intermittent renewable energy sources. In particular, by focusing on extremely large (but rare) forecasting errors in the intermittent renewable energy source output, which are generally inevitable in most forecasting methods, a model for representing the forecasting error in line with current variation due to intermittent renewable energy source output is developed. The model is based on a shape parameter that represents the equivalent current variation required for the same temperature increase as that due to the extremely large forecasting error. Finally, based on the annual minute-by-minute irradiance data, preventive control of the transmission network with dynamic line ratings is evaluated using worst-case parameter values.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:4:p:503-:d:95312
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    References listed on IDEAS

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    1. Alberto Arroyo & Pablo Castro & Raquel Martinez & Mario Manana & Alfredo Madrazo & Ramón Lecuna & Antonio Gonzalez, 2015. "Comparison between IEEE and CIGRE Thermal Behaviour Standards and Measured Temperature on a 132-kV Overhead Power Line," Energies, MDPI, vol. 8(12), pages 1-12, December.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    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.

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