Impedance-Based Aggregation of Paralleled Power Factor Correction Converters in Data Centers

Abstract

Existing aggregation methods for large-scale data center power systems often overlook disparities in power supply units, leading to reduced accuracy in the small signal dynamics of aggregated model. To fill this gap, this article develops an impedance-based aggregation method for paralleled power factor correction (PFC) converters with heterogeneities in power levels, conduction modes, and line impedances. The closed-loop input admittances of PFC converters operating in continuous conduction mode (CCM) and discontinuous conduction mode (DCM) are presented first. The parametric scaling is then derived to aggregate multiple PFC converters at different power levels and operation modes, including the CCM, DCM, and mixed conduction mode, at the rack level. Furthermore, the aggregation rule and criteria for paralleled PFC converters with unequal line impedances is developed to provide a reduced-order dynamic model for adjacent server racks. The proposed parameter scaling and aggregation method allow efficient interaction analysis and stability assessment for data center power systems. The accuracy and robustness of the impedance-based aggregation are finally validated by simulations and experimental tests.