Virtual-inertia-based power management scheme in fuel cell-battery-supercapacitor-based DC microgrid

The reliability of the microgrid supply is often relying on the energy storage mediums used. Hydrogen is considered as a long-term energy storage solution whereas battery provides the energy for short-term. Fuel cell converts the stored hydrogen energy into electricity. As these storage mediums have low inertia in the system, there can be excessive current stress on the devices, leading to degradation. Virtual inertia can improve the behavior of the devices during load variation. These storage devices can be modeled as virtual machines, and these virtual inertia-based devices can provide a delayed response to the load variation. Therefore, the life of the storage mediums can be improved. In this paper, a DC microgrid system has been studied, having the photovoltaic power generator, battery, supercapacitor, and fuel cell as the other power sources. The photovoltaic generator works in MPPT mode and generates electricity to meet the load demand. The virtual inertia-based control embedded with each kind of storage medium enables the limitation of the sudden variation of power. The fuel cell provides the rated power with a certain delay w.r.t. battery and supercapacitor so that it has less dynamic power stress. The sudden variation in the load demand is met by the supercapacitor, and the battery provides the remaining power owing the high inertia as compared to the supercapacitor. The power allocation among each kind of storage medium takes into account the hydrogen storage state of charge also. The simulation results have been obtained by using the OPAL-RT to verify the effectiveness of the control strategy in real-time. The rate of power change for the fuel cell is achieved as approximate to 160 W/s. Whereas the rate of power change of the battery and supercapacitor are found to be approximate to 321 W/s, and approximate to 626 W/s, respectively. The DC bus voltage is well regulated to the nominal value in the transient load condition.