Generative AI Application in Power System Asset Management

As the global efforts to address climate change goals advance, the demand for renewable energy grows, and governments around the world actively promote low-carbon economies and green energy policies, the power system is undergoing profound changes. This transformation not only affects the mode of power production but also profoundly alters the way, focus, and technical means of power equipment asset management. The diversification of equipment types has increased management complexity, as new types of equipment such as photovoltaic inverters, wind turbine blades, and energy storage systems require specialized maintenance knowledge and technologies. To enhance the reliability and safety of power equipment, and reduce maintenance costs, this paper aims to explore the integration path of generative AI technology and the knowledge base of power equipment asset management, establish a knowledge base for the life cycle of asset equipment, adopt emerging generative AI information technology, and build an intelligent power asset equipment management question-answer platform to achieve intelligent management of various assets, thereby reducing unplanned downtime and improving the stability of power grid operation. Firstly, establish a knowledge base for power equipment management and combine it with the retrieval-augmented generation technology of generative AI to enable it to understand and generate professional knowledge and technical guidance related to power equipment. Then, deploy the application on a cloud platform and create an interactive intelligent assistant that can analyze emerging problems in real time and provide targeted solution suggestions. At the same time, it enables front-line technicians to quickly obtain effective help and support even when facing complex situations, they have never encountered before.