| Abstrakt: |
This paper proposes a hybrid method for controlling bidirectional power sharing among grids and dc microgrids. The interlinking converter (IC) and current-fed dual active bridge (CFDAB) converters connect the grid and dc microgrid. The proposed approach is the joint implementation of golden eagle optimization and radial basis function neural network, hence, named the GEO-RBFNN approach. The bidirectional power distribution control signal analysis significantly diminishes power distribution deviation and circulating current. This power-sharing control system neglects the need for battery backup since the required amount of power is brought from or handled by an AC utility. The dc microgrid incorporates the dc to dc converter, from which boost converters use sources and buckconverters use supply loads. The control of bidirectional power sharing among the microgrids and the grid is attained with the aid of the GEO-RBFNN algorithm. It delivers certain aids, like higher predictability, highly reliable results, high speed, and less complexity. The outcome is investigated on the MATLAB platform. According to the comparison outcome, the proposed method delivers higher performance than the existing system. The proposed method gives higher comparison outcomes than the current methods, which can conquer the associated problems. The proposed method-based settling time is 3.356 ms, and the rise time is 1.555 ms. The efficiency based on the proposed method is 97.54%, which is higher than the existing methods. [ABSTRACT FROM AUTHOR] |
