RESEARCH AND IMPLEMENTATION OF ACTIVE PUSH TECHNOLOGY FOR TRANSMISSION LINE RISKS BASED ON METEOROLOGICAL INFORMATION

Abstract

Frequent extreme meteorological disasters trigger numerous faults of transmission lines such as ice coating, wind deflection, lightning damage and wildfires. Existing power grid meteorological early warning systems suffer from drawbacks including single-dimensional data, insufficient accuracy of risk research and judgment, and generalized early warning push, which fail to support refined disaster prevention, operation and maintenance for single towers and local line sections. To address these issues, this paper conducts research on the technical system and application platform for active push of transmission line risks based on multi-source meteorological information. First, three types of power-specific multi-source meteorological data supporting line risk assessment are sorted out, namely real-time monitoring data, short-term forecast data and historical statistical data. Six categories of meteorological disasters threatening lines, including strong wind, ice coating, lightning, rainstorm and flood, wildfire and pollution flashover, are classified, and existing deficiencies in early warning for each disaster type are analyzed . Second, the overall architecture of the early warning push system based on the i-State Grid is designed. Centering on four core modules: information collection, standardized assembly, intelligent sorting and multi-channel push, screening and integration processes for early warning information for multiple scenarios such as meteorological forecasts and severe convection are constructed respectively. Multi-batch comparison and space-time matching algorithms are adopted to reduce false early warning alarms. Finally, a hierarchical and classified accurate push mechanism is established, realizing precise matching between risk points and operation & maintenance personnel combined with post responsibilities. Early warning information is issued through coordinated channels including i-State Grid and short messages. Engineering applications verify that the proposed technology breaks the data barrier between meteorological data and power grid equipment data, enabling intelligent research and judgment of tower-level refined meteorological risks and hierarchical active push. It transforms the traditional extensive and lagging passive prevention and control mode, significantly improving the pre-disaster prevention and control capacity of the power grid against meteorological disasters, reducing meteorology-induced line faults and emergency disposal costs, and providing technical support for the construction of meteorological disaster prevention systems for smart power grids.