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Increasing the Utilization of Transmission Lines Capacity by Quasi-Dynamic Thermal Ratings

Author

Listed:
  • Fan Song

    (School of Mechanical, Electrical and Information Engineering, Shandong University (Weihai), Weihai 264209, China)

  • Yanling Wang

    (School of Mechanical, Electrical and Information Engineering, Shandong University (Weihai), Weihai 264209, China)

  • Hongbo Yan

    (School of Mechanical, Electrical and Information Engineering, Shandong University (Weihai), Weihai 264209, China)

  • Xiaofeng Zhou

    (Department of Mechanical-Electrical Engineering, Weihai Vocational College, Weihai 264210, China)

  • Zhiqiang Niu

    (State Grid Weihai Power Supply Company, Weihai 264200, China)

Abstract

The power grid is under pressure to maintain a reliable supply because of constrained budgets and environmental policies. In order to effectively make use of existing transmission lines, it is important to accurately evaluate the line capacity. Dynamic thermal rating (DTR) offers a way to increase the utilization of capacity under real-time meteorological data. However, DTR relies on a number of sensors and the cost is high. Therefore, a method of improving the utilization of capacity by quasi-dynamic thermal rating (QDR) is proposed in this paper. QDR at different confidence levels and time scales is determined through the statistical analysis of line ampacity driven by key parameters, and the key parameters is identified by control variate method. In addition, the operation risk and tension loss is evaluated. The results show that QDR can increase the utilization of line capacity and in the absence of along-line measuring devices, QDR is more accurate, reliable and cost-saving. The managers can determine the appropriate confidence level according to the operation risk and tension loss that the system can bear, and shorten the time scale with the permission of the operation and control complexity.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:792-:d:209467
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    References listed on IDEAS

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    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. 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.
    3. Jiashen Teh & Chia Ai Ooi & Yu-Huei Cheng & Muhammad Ammirrul Atiqi Mohd Zainuri & Ching-Ming Lai, 2018. "Composite Reliability Evaluation of Load Demand Side Management and Dynamic Thermal Rating Systems," Energies, MDPI, vol. 11(2), pages 1-15, February.
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    Cited by:

    1. Zhengwei Shen & Yong Tang & Jun Yi & Changsheng Chen & Bing Zhao & Guangru Zhang, 2019. "Corrective Control by Line Switching for Relieving Voltage Violations Based on A Three-Stage Methodology," Energies, MDPI, vol. 12(7), pages 1-15, March.
    2. 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.

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