Framework for artificial intelligence analysis in large-scale power grids based on digital simulation

The planning, design, operation, control and scientific research of power systems all require a variety of simulation analysis. Thus power grid simulation analysis is a fundamental supporting technology of large-scale power grids. In power grid simulation analysis, in addition to simulation calculations, there are many links for analysis and decision-making, relying on specialists. The introduction of advanced artificial intelligence technology provides a new method to improve the efficiency and accuracy of power grid simulation analysis. Nevertheless, the research of the related artificial intelligence technologies face a great deal of new challenges due to the complexity of the large-scale power grid simulation data, including massive volumes, high dimensionality, strong coupling and complex correlations. Also a great deal of knowledge and experience need to be integrated in the process of analysis. In order to deal with these challenges, based on the existing works, this paper focuses on the core scientific problem of artificial intelligence analysis and decision making related to the massive simulation results of large-scale power grids, and proposes an artificial intelligence analysis method framework for large-scale power grids based on digital simulation, which includes the power grid simulation analysis knowledge model with application method, the power grid simulation knowledge mining method and the artificial intelligence models with transfer learning ability of diversified grids as well as analyzing and calculation adjusting for large-scale power grid simulation results, etc. This work is expected to open up a new technical approach for large-scale power grid simulation analysis and provide strong technical support for the safe and stable operation of large-scale power grids.