Dynamic Thermal Rating of Overhead Transmission Lines Based on GRAPES Numerical Weather Forecast

Hongbo Yan, Yanling Wang, Xiaofeng Zhou, Likai Liang, Zhijun Yin and Wei Wang
Volume: 15, No: 4, Page: 724 ~ 736, Year: 2019
10.3745/JIPS.04.0122
Keywords: Dynamic Thermal Rating, Global/Regional Assimilation and Prediction System (GRAPES), Meteorological Data, Power Grids, Thermal Load Capacity, Transmission Line
Full Text:

Abstract
Dynamic thermal rating technology can effectively improve the thermal load capacity of transmission lines. However, its availability is limited by the quantity and high cost of the hardware facilities. This paper proposes a new dynamic thermal rating technology based on global/regional assimilation and prediction system (GRAPES) and geographic information system (GIS). The paper will also explore the method of obtaining any point meteorological data along the transmission line by using GRAPES and GIS, and provide the strategy of extracting and decoding meteorological data. In this paper, the accuracy of numerical weather prediction was verified from the perspective of time and space. Also, the 750-kV transmission line in Shaanxi Province is considered as an example to analyze. The results of the study indicate that dynamic thermal rating based on GRAPES and GIS can fully excavate the line power potential without additional cost on hardware, which saves a lot of investment.

Article Statistics
Multiple requests among the same broswer session are counted as one view (or download).
If you mouse over a chart, a box will show the data point's value.


Cite this article
IEEE Style
H. Yan, Y. Wang, X. Zhou, L. Liang, Z. Yin and W. Wang, "Dynamic Thermal Rating of Overhead Transmission Lines Based on GRAPES Numerical Weather Forecast," Journal of Information Processing Systems, vol. 15, no. 4, pp. 724~736, 2019. DOI: 10.3745/JIPS.04.0122.

ACM Style
Hongbo Yan, Yanling Wang, Xiaofeng Zhou, Likai Liang, Zhijun Yin, and Wei Wang. 2019. Dynamic Thermal Rating of Overhead Transmission Lines Based on GRAPES Numerical Weather Forecast, Journal of Information Processing Systems, 15, 4, (2019), 724~736. DOI: 10.3745/JIPS.04.0122.