基于多源数据融合的台风灾害下电网风险预警方法及系统
By employing a multi-source data fusion approach for power grid risk early warning during typhoon disasters, and utilizing gridded processing of power grid, geographic, and meteorological data along with a regression decision tree model, this method addresses the problem of inaccurate prediction of the number of power grid equipment failures during typhoon disasters. It enables accurate early warning of power grid risks and effective deployment of emergency resources, thereby enhancing the power grid's response capabilities.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NARI INFORMATION & COMM TECH
- Filing Date
- 2022-10-27
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies struggle to effectively integrate multi-source data, leading to inaccurate predictions of power grid equipment failures during typhoons and a lack of effective risk warning technologies.
By establishing a multi-source data fusion method for early warning of power grid risks under typhoon disasters, including gridded processing of power grid, geographic and meteorological data, and using Copeland scores and regression decision tree models, the method can accurately predict the number of power grid equipment failures.
It enables accurate prediction of the number of power grid equipment failures under typhoon disasters, provides power grid risk quantification and early warning, allows power grid operators to deploy emergency resources in advance, improves the power grid's ability to respond to typhoon disasters, and reduces economic losses.
Smart Images
Figure CN115688032B_ABST