Dynamic Aggregation Modeling for Droop Control Inverter Based on Slow Coherency Algorithm

In recent years, coherency-based aggregation method has been widely used in dynamic equivalence in large-scale systems, and the dynamic response of the system can be accurately reflected by the obtained reduced-order model. Among them, the traditional slow coherency algorithm has many advantages, such as being insensitive to the location and severity of the fault and been popular in research. But it is difficult to be applied to the distributed generation network due to the model limitation and poor accuracy. To address above issues, a slow coherency and aggregation method suitable for grid-connected inverter networks based on droop control has been proposed in this paper. A slow coherency model is established and the influence of damping is analyzed based on the singular perturbation theory, and the applicability issue of droop-controlled inverter networks has been solved. In order to identify accurately the coherent power source, the fuzzy C-means spatial clustering algorithm is utilized in the modal matrix. Finally, a reduced-order model is established through the parameter aggregation method, and the simulation results verify the effectiveness of the proposed scheme.