By modeling the spatiotemporal data of the power grid

it is possible to better understand its operational status

identify potential issues and risks

and take timely measures to adjust and optimize the system. Compared to the bus-branch model

the node-breaker model provides higher granularity in describing grid components and can dynamically reflect changes in equipment status

thus improving the efficiency of grid dispatching and operation. This paper proposes a spatiotemporal data modeling method based on a graph database. It elaborates on constructing graph nodes

graph ontology models

and graph entity models from grid dispatch data

describing the construction of the spatiotemporal node-breaker graph model and the transformation to the bus-branch model. Subsequently

by integrating spatiotemporal data attributes into the pre-built static grid graph model

a spatiotemporal evolving graph of the power grid is constructed. Furthermore

the concept of the “Power Grid One Graph” and its requirements in modern power systems are elucidated. Leveraging the constructed spatiotemporal node-breaker graph model and graph computing technology

the paper explores the feasibility of grid situational awareness. Finally

typical applications in an operational provincial grid are showcased

and potential scenarios of the proposed spatiotemporal graph model are discussed.