Design and Implementation of a Distributed Simulation Architecture for Modern Power Systems Based on Data Distribution Service
The integration of high-penetration renewable energy and power electronic converters has intensified the dynamic complexity of modern power systems, imposing stringent demands on simulation accuracy and computational efficiency. This paper proposes a distributed simulation architecture based on Data Distribution Service (DDS) that leverages dispersed computing resources to enhance scalability and efficiency while preserving numerical fidelity. The power system model is mathematically decoupled into multiple independently solvable basic subsystems, and a generic data transmission interface is designed using DDS. A time-consumption balancing scheme groups and distributes these subsystems across multiple devices, and a two-layer synchronization strategy enables efficient parallel simulation. The architecture is validated on a two-area four-machine system, the IEEE New England 10-machine 39-bus system, and the WECC 29-machine 179-bus system. Compared with centralized simulation, the average error on the two-area four-machine system remains below 1.05%. Simulation efficiency improvement reaches approximately 10% on the 10-machine 39-bus system and about 48% on the 29-machine 179-bus system. The results confirm high accuracy across different system scales and demonstrate that efficiency gains become more pronounced as system size increases, validating the architecture's scalability and compatibility. The proposed framework offers a promising pathway for large-scale power system simulation and supports future integration with edge computing and cross-platform deployment.