Coherency Identification and Aggregation Algorithms for Parallel DAB Systems in DC Microgrids

ABSTRACT The high complexity and long computation time in simulating dual‐active‐bridge (DAB)‐based parallel DC microgrid systems pose significant challenges. To address this, coherency identification and aggregation algorithms (CIAA) for multi‐DAB parallel DC microgrid systems (MDPDMS) are proposed. First, a correlation model between common DC bus voltage disturbances and measurable DAB output quantities is established. Using output current fluctuation similarity as the coherency criterion, a dynamic similarity index is derived. Coherent DAB groups (CDGs) are then adaptively identified using the K‐Medoids algorithm, with the clustering results refined by a defined cost function. Second, under the core constraints of power conservation and dynamic response equivalence, a mapping is established between the equivalent model (EM) and the internal topology and control parameters of the CDG to accurately aggregate parameter‐heterogeneous DABs. The proposed method maintains high fidelity to the dynamic characteristics of the detailed system (DS) while significantly improving simulation efficiency. The simulation time of the reduced‐order system (ROS) is only 56% of that required by the detailed system.