To deal with the problem of complex frequency response characteristics of power system after disturbance caused by high proportion of new energy grid connection

an intelligent frequency regulation method based on large language model is proposed. Firstly

by analyzing the key technologies such as prompt word engineering

RAG

function call and large model fine-tuning

and combining the low-frequency load shedding optimization rules based on vector database formed by natural language processing technology

a large model of vertical field of power system is constructed. Then

the adaptive ability of artificial intelligence generated content (AIGC) technology is used to achieve efficient frequency optimization control

which makes up for the lack of adaptability of traditional under-frequency load shedding methods in new energy power systems. The simulation results show that the frequency regulation optimized by this scheme significantly improves the stability of the power system

and the regulation results in multiple offline scenarios are better than those of the traditional methods. The research of this paper provides a new technical path for the intelligent control of power system frequency and has high application potentials.