Research on the Application of Knowledge Graph in Demand-Side Flexible Resource Profiling and Aggregation Techniques

This paper commences by assessing the current landscape of power system development, focusing on the theory, principles, and structures of demand-side flexible resources and their aggregation technology. Utilizing network crawler technology within a knowledge graph framework, the research data pertinent to demand-side flexible resources and aggregation technology are extracted. These data undergo a meticulous cleaning process before being stored, culminating in the development of a knowledge graph tailored to the imaging and technology of demand-side flexible resources. The findings reveal a response rate of 7.25% ± 1.15%, with an uncertainty interval of 2.33%. Variations in air-conditioning load states appear to exert minimal impact on the response time lag. Following the issuance of a response signal, all systems can rapidly initiate appropriate response actions, demonstrating an uncertainty interval of approximately 52s±11s and 22s. The duration of the responses averages around 75s±11s, with an uncertainty interval of about 30s. This study fulfills the power system criteria for standards of demand-side flexible resources and augments the competitiveness of China’s power market.