Communication network and source-grid-load-storage transient coupling modeling method for new power systems

To address the issues of reduced system inertia and complex dynamic responses caused by the high proportion of renewable energy and power electronic equipment in new power systems, this article develops a transient coupling modeling method for communication networks and source-grid-load-storage based on a unified time scale and event-driven mechanism, aiming to improve system stability. First, a hybrid system modeling framework with a unified time scale is constructed. Leveraging high-precision global clock synchronization, this approach enables the coordinated solution of continuous power system states and discrete communication system events, achieving precise synchronization of information and energy flows on a microscopic time scale. Second, a dynamic modeling method for the communication network is designed, combining graph topology and queuing theory to accurately describe characteristics such as communication link delay, packet loss, and congestion. Furthermore, cyber-physical interface mapping rules are employed, along with timestamps and adaptive sampling mechanisms, to ensure accurate cross-system data encapsulation, transmission, and execution. Finally, a source-grid-load-storage-based coupled simulation framework is established. Through event-driven and unified time scale mechanisms, continuous integration of power system transient equations and discrete processing of communication events are simultaneously performed. Finally, a bidirectional closed-loop coupled simulation of “power-communication-power” is implemented on a co-simulation platform. Experiments show that the proposed method achieves an average stabilization time of 0.375 s, an average recovery rate of 1.711 Hz/second, a bandwidth utilization rate of 93.38%, and a message success rate of 99.08%. It also demonstrates excellent voltage recovery performance under multiple disturbance scenarios, with a short-circuit recovery time of only 0.12 s. This method effectively addresses the mismatch between information transmission delays and power transients, improving system stability and dynamic response capabilities. It also provides a technical path and theoretical support for the modeling of novel power systems and the deep integration and coordinated control of cyber-physical systems.