Meteorological fault risk assessment of power grid based on improved association rules algorithm

In order to improve the evaluation effect of meteorological fault risk of power grid, a new method is proposed to deal with the fault risk of power grid under extreme weather conditions. This method combines the advantages of traditional association rules algorithm and makes specific improvements to identify the potential association between power grid faults and meteorological conditions more accurately. Through the comprehensive analysis of historical meteorological data and power grid fault records, the key factors affecting the stable operation of power grid are dug out, and the corresponding risk assessment model is constructed. Experiments show that the risk assessment model based on improved association rules algorithm can accurately assess the fault risk of power grid under different meteorological conditions, and the improved algorithm is obviously better than the traditional Apriori algorithm in terms of running time, which can improve the accuracy and intelligence level of power grid meteorological fault risk assessment.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.05.167
Primary Topic
Advanced Computational Techniques and Applications
Type
article
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article

Meteorological fault risk assessment of power grid based on improved association rules algorithm

Mingming Meng, Zhenghuan Xia, Tao Zhang, Yuanchao Li
Procedia Computer Science
Advanced Computational Techniques and Applications
article

Meteorological fault risk assessment of power grid based on improved association rules algorithm

Mingming Meng, Zhenghuan Xia, Tao Zhang, Yuanchao Li
article en

Abstract

In order to improve the evaluation effect of meteorological fault risk of power grid, a new method is proposed to deal with the fault risk of power grid under extreme weather conditions. This method combines the advantages of traditional association rules algorithm and makes specific improvements to identify the potential association between power grid faults and meteorological conditions more accurately. Through the comprehensive analysis of historical meteorological data and power grid fault records, the key factors affecting the stable operation of power grid are dug out, and the corresponding risk assessment model is constructed. Experiments show that the risk assessment model based on improved association rules algorithm can accurately assess the fault risk of power grid under different meteorological conditions, and the improved algorithm is obviously better than the traditional Apriori algorithm in terms of running time, which can improve the accuracy and intelligence level of power grid meteorological fault risk assessment.

Procedia Computer ScienceVol. 262
Accenture (Switzerland) (CH), State Grid Corporation of China (China) (CN)
Climate action
Openalex Percentile: Top 94%
Advanced Computational Techniques and Applications
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Meteorological fault risk assessment of power grid based on improved association rules algorithm — Mingming Meng, Zhenghuan Xia, et al. · Procedia Computer Science (2025) | TGRS Research Map | TGRS