Refined transmission line ice-cover prediction model and optimization study
Abstract This study aims to develop a fine-grained transmission line ice-cover prediction model and conduct an optimization study. Ice cover is one of the important factors leading to transmission line accidents, so accurately predicting the ice cover of transmission lines is crucial to ensure the safe operation of power grids. In this paper, an efficient ice-cover prediction model is constructed based on advanced machine learning algorithms and optimization methods and is validated and optimized with a large amount of experimental data. The results show that the proposed model has high accuracy and prediction capability in ice cover prediction, which provides important support for the safe operation of transmission lines.
Authors
- Huamin Sun
- Maojie Tian
- Guozhu Yang
- S. S. Sun (ORCID: https://orcid.org/0000-0002-0453-7388)
- Jingru Liu
Institutions
- State Grid Corporation of China (China) (CN)
Publication Details
- Journal
- Journal of Physics Conference Series
- Published
- 2024-11-01
- DOI
- https://doi.org/10.1088/1742-6596/2876/1/012014
- Citations
- 1
- Primary Topic
- Icing and De-icing Technologies
- Type
- article
- Field-Weighted Citation Impact
- 1.30