Research On GIC EArly Warning ANalysis Based On Multi-Source Data Fusion Technology

GIC has made great influence on safe and stable operation of artificial networks on the earth such as power grid, underground metal pipe.etc. With the development of the EHV and UHV AC/DC transmission system, the risk with the impact of GIC on the safe and stable operation of power grid has increased. So it is of great significance to the reliable and effective early-warning of GIC in power grid.North China Electric Power University has achieved some results and accumulated many data during the analysis and research of GIC since2000. The data which includes monitoring data from geomagnetic stations, astronomical sites、 substations and configuration parameters of power grid.etc. come from different platforms and have different formats and meanings. The fusion, analysis and data mining of these data and GIC is important for the stable operation of power grid and give valuable information to forecast GIC.This paper first makes an introduction of the existing data and explains the meanings of necessity of research and analysis of GIC early-warning adopting multivariate data fusion method. Then, make fusion processing of numerous existing data and GIC data and analyze the relationship of existing data and GIC to make preparation for the construction of analysis system for GIC early-warning based on multivariate data fusion. In the end, introduce a multiple linear regression analysis theory and use it in Guangzhou Lingao nuclear power station for data analysis and build a mode based on it.