Automated Data Generation Method for Power System Online Security Assessment Based on Multi-Source Heterogeneous Information Fusion

To improve the efficiency and quality of power system online security analysis data generation, an innovative solution based on intelligent fusion of multi-source heterogeneous information is proposed. The approach integrates real-time online and offline mode data to construct a data fusion model tailored for online analysis of power systems. The multi-source data fusion method includes key modules such as data parsing and verification, power grid topology analysis, model extension and parameter fusion. Building on the aforementioned theoretical methodology, a new-generation power grid parallel computing platform based on dynamic load balancing technology has been developed. This platform employs a distributed computing architecture, integrates the power system analysis software package (PSASP) computing engine, and supports real-time simulation and analysis of large-scale power systems. Currently, this system has been successfully deployed in multiple provincial dispatch centers of the State Grid Corporation of China, providing reliable technical support for online security assessment and intelligent dispatch decision-making in large-scale power grids.