Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022)

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Intelligent Revision Application of Similar Collection Method in Strong Wind Forecasting in Complex Terrain Areas of Transmission Channels

Authors
PengYou Lai1, *, JingTao Yang2, LeXi Liu1
1College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang, 524088, Guangdong, China
2College of Mathematics and Computer Science, Guangdong Ocean University, Zhanjiang, 524088, Guangdong, China
*Corresponding author. Email: laipengyou@stu.gdou.edu.cn
Corresponding Author
PengYou Lai
Available Online 29 December 2022.
DOI
10.2991/978-2-494069-31-2_16How to use a DOI?
Keywords
Transmission channels; Micrometeorological device observation; Revision of numerical forecasts; Similar set methods; Strong wind forecasting for complex terrain
Abstract

With the continuous development of numerical weather prediction technology, the weather forecast mode can provide refined forecasts of meteorological elements such as wind fields and temperatures for the power grid, but there are large errors in the terrain of the power grid transmission channel area. This paper selects in-situ microeoreorological observations of power grid transmission channels during Typhoon Hagupit no. 04 in 2020, and uses the similar set (AnEn) algorithm to re-analyze grid data of European short- and medium-term forecasting centers, and constructs a revised model of wind field forecasting in complex terrain areas of transmission channels, and applies them to strong wind forecasting of transmission channels. The results show that the numerical forecasting mode has a large forecast error in the near-ground area of the complex transmission channel, with a root mean square error of 5.1 m/s. The forecast error in the complex terrain area of western Zhejiang is greater than that in the northern and eastern coastal areas; The similar set method can effectively correct the near-ground wind field, and the forecast error is 4.09 m/s before revision, and the error is reduced to 1 m/s after revision.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
29 December 2022
ISBN
978-2-494069-31-2
ISSN
2352-5398
DOI
10.2991/978-2-494069-31-2_16How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - PengYou Lai
AU  - JingTao Yang
AU  - LeXi Liu
PY  - 2022
DA  - 2022/12/29
TI  - Intelligent Revision Application of Similar Collection Method in Strong Wind Forecasting in Complex Terrain Areas of Transmission Channels
BT  - Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022)
PB  - Atlantis Press
SP  - 129
EP  - 137
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-494069-31-2_16
DO  - 10.2991/978-2-494069-31-2_16
ID  - Lai2022
ER  -