In this paper

we study the application of big language modeling and artificial intelligence in power systems. First

we introduce the basic principles and characteristics of big language model

including its development history and application areas. Then

we discuss the current status and prospects of the application of artificial intelligence technology in power systems. We analyze three key application areas of big language models in power systems: power load forecasting

power equipment fault diagnosis

and power system security assessment. In power load forecasting

the big language model can realize accurate load forecasting by learning historical data and environmental features

providing powerful support for power system operation and scheduling. In power equipment fault diagnosis

the big language model can automatically identify and locate faults according to the operating state of the equipment and fault characteristics

improving the diagnostic efficiency of equipment faults. In power system security assessment

the Big Language Model can analyze system operation data and risk factors

quickly assess the security status of the system

and provide early warning and decision support. Finally

we discuss the challenges and countermeasures for the application of big language modeling and artificial intelligence in power systems. We believe that with the continuous development of big language modeling and the continuous innovation of AI technology

the operational efficiency and security of power systems will be significantly improved.