An artificial intelligence adjustment method of large-scale power flow based on knowledge-driven

With China's power grid gradually showing the characteristics of long distance, heavy load, large-area interconnection, and introduction of market competition, the situation that power flow calculation does not converge appears more and more frequently. Therefore, solving the problem of power flow non-convergence will become the focus and difficulty of power flow calculation. At present, analysis and calculation personnel often can only make adjustments based on experience. This traditional adjustment method is inefficient, which has high work intensity, and the effects is also not obvious. This paper proposes a artificial intelligence adjustment method of large-scale power flow based on knowledge-driven. This method expresses the knowledge and experience accumulated in power flow adjustment process in the form of knowledge graph, and builds knowledge base on this basis. And then, this paper takes the knowledge base rules as the criterion of power flow intelligent adjustment, which can provides the reasoning and deduction of logical and possible about the adjustment direction and adjustment measures So as to make correct judgments and decisions. Finally this paper realizes the artificial intelligence adjustment of the large-scale power flow.