Efficient State Estimation Through Rapid Topological Analysis Based on Spatiotemporal Graph Methodology - Zhen Dai; Shouyu Liang; Yachen Tang; Jun Tan; Guangyi Liu; Qinyu Feng; Xuanang Li (IEEE Open Access Journal of Power and Energy)
The seamless integration of swift and precise topological analysis with state estimation is crucial for ensuring the dependability, stability, and efficiency of the power system. In response to this need, this paper introduced a novel approach to constructing a spatiotemporal “Power Grid One Graph” model using a graph database, enabling rapid topological analysis and state estimation. Initially, a spatiotemporal power grid model was created by merging grid topology with dynamically updated telemetry and telesignaling data. Subsequently, utilizing the graph model and entity mapping, the spatiotemporal node-breaker graph model was obtained and the corresponding bus-branch model was generated. Based on the node-breaker graph model, topological error identification was conducted, and a fast topological analysis optimization algorithm, considering component functionality, was applied to update the bus-branch graph model, facilitating graph-based state estimation. Finally, the proposed method was validated on a real power system, and its application, along with performance enhancements of the spatiotemporal power grid model considering topological changes, was investigated. The presented method provides both theoretical and practical support for the digital transformation of the power system and the advancement of the digital twin power grid.