Coordinated control strategy for multi-DG DC microgrid based on two-layer fuzzy neural network

Conventional coordinated control strategies for DC bus voltage signal (DBS) in islanded DC microgrids (IDCMGs) struggle with coordinating multiple distributed generators (DGs) and cannot effectively incorporate state of charge (SOC) information of the energy storage system, thereby reducing the system flexibility. In this study, we propose an adaptive coordinated control strategy that employs a two-layer fuzzy neural network controller (FNNC) to adapt to varying operating conditions in an IDCMG with multiple PV and battery energy storage system (BESS) units. The first-layer FNNC generates optimal operating mode commands for each DG, thereby avoiding the requirement for complex operating modes based on SOC segmentation. An optimal switching sequence logic prioritizes the most appropriate units during mode transitions. The second-layer FNNC dynamically adjusts the droop power to overcome power distribution challenges among DG groups. This helps in preventing the PV power from exceeding the limits and mitigating the risk of BESS overcharging or over-discharging. The simulation results indicate that the proposed strategy enhances the coordinated operation of multi-DG IDCMGs, thereby ensuring the efficient and safe utilization of PV and BESS.