A neural network-based adaptive power-sharing strategy for hybrid frame inverters in a microgrid - Deng, Wenyang; Zhang, Yongjun; Tang, Yuan; Li, Qinhao; Yi, Yingqi (Frontiers in Energy Research, 2023)
Flexible reactive power condition is vital for a microgrid (MG) system. The power conditioning character of the capacitive-coupling inverter (CCI) based DG unit distinguishes it from the inductive-coupling inverter (ICI) based DG unit. Previous studies indicate that CCI is more cost-effective in reactive power conditioning and enhanced reactive power regulation ability. Thus, to improve the flexibility of reactive power condition for the MG system, a brand-new MG frame with hybrid parallel-connected ICIs and CCIs are proposed. Besides, considering the CCI can work under a lower DC-link voltage, to reduce the total power capacity of the proposed system to decrease the loss, in this paper, an unequal power-sharing method is investigated, to match different inverters. A case study with proposed unequal power-sharing is presented; a BP neural network-based power-sharing control layer that guarantees the rapid and accurate sharing ratio computation is investigated as well. Simulation and experiment results verified the effectiveness of the proposed method.