Hybrid MVMO based controller for energy management in a grid connected DC microgrid

This paper deals with a grid connected DC microgrid. The DC microgrid which consists of a PV array and DC loads has been integrated into the main grid through a 3-phase inverter to take power from the grid during low generation and feed the grid during high generation. A control scheme to manage the power flow in DC microgrid by tuning the conventional proportional-integral (PI) controllers in the grid side converter using a swarm variant of hybrid mean variance mapping optimization (MVMO-SH) algorithm has been proposed and tested under critical disturbances such as insolation drop and load change. The designed controller has been tuned using two strategic methods - sequential tuning and simultaneous tuning. Additionally, MVMO-SH has been compared with genetic algorithm (GA) to validate better performance owing to the multi-parent crossover strategy of MVMO-SH. The optimal gains have further been tuned to develop a faster inverter control. The results confirm that the designed controller significantly reduces the DC voltage deviations as well as incorporates faster tracking of current during various disturbances.