In the dynamic world of power systems, the integration of distributed energy resources and the expansion of power grids have created a pressing need for comprehensive and accurate power system models. These models are the backbone of analysis and decision-making processes, guiding the efficient and reliable operation of our energy infrastructure. However, the frequent updates to the Common Information Model (CIM), which underpins these models, and the inevitable custom extensions, pose significant challenges to maintaining model quality.
Enter Xiaolu Li, a researcher from the College of Electrical Engineering at Shanghai University of Electric Power. Li has proposed a groundbreaking method for validating the knowledge graph of power system models using the Shapes Constraint Language (SHACL). This innovative approach addresses the complexities and dynamic nature of model quality requirements, offering a more flexible and adaptable solution.
The method involves establishing a CIM-based concept graph and entity graph of the power system model. Li then designs CIM schema consistency shapes and cross-class and cross-property consistency shapes using SPARQL (Simple Protocol and RDF Query Language) for validating the power system model. “The SHACL-based knowledge graph validation for the power system model does not need to hard-code the validation rules,” Li explains. “This improves the flexibility of power system model quality validation and satisfies the dynamic evolution of model quality requirements.”
The implications of this research are vast. As power grids become more complex and distributed energy resources become more prevalent, the ability to validate and ensure the quality of power system models is crucial. Li’s method provides a robust framework that can adapt to the ever-changing landscape of power system modeling, ensuring that models remain accurate and reliable.
This research, published in ‘Zhongguo dianli’ (translated to ‘Chinese Journal of Electric Power’), represents a significant step forward in the field. By leveraging SHACL and SPARQL, Li’s method offers a more dynamic and flexible approach to model validation, paving the way for future developments in power system modeling and analysis. As the energy sector continues to evolve, the ability to adapt and validate models efficiently will be key to maintaining the reliability and efficiency of our power systems.