One of the drawbacks of the virtual inertia emulation process for AC power systems is to not consider the simultaneous effect of DC power control in the DC-link side interfaced power converters in presence of energy storage systems. In this paper, a Hybrid Virtual Machine is proposed to deal with this gap by augmenting the inertia fulfillment of a weak power grid by concurrently introducing a flexible virtual DC inertia. In this regard, the proposed hybrid virtual machine is composed of a virtual AC machine and two virtual DC machines wherein the converter dynamics and real machine swing equation are incorporated altogether using the small-signal linearization technique. Moreover, a multi-objective function is commensurately assigned attempting to meet the desirable responses for virtual machine currents under optimal virtual inertia and damping factors. Before starting optimization process, appropriate constraint areas are achieved for the virtual inertia and damping factor of both virtual AC and DC machines through a comprehensive analysis of second-order transfer functions. In addition, the AC and DC virtual inertia are concurrently altered to distinguish the non-synchronous variation effects of virtual inertia consistent with the optimization process for constraint affirmation and also further stability analysis. The significant performance of the proposed optimized hybrid virtual machine is verified through the simulation of a two hybrid virtual machines-based system in presence of PV unit variations in MATLAB/SIMULINK environment. The simulation results exhibit the stable and robust responses for power sharing, DC-link voltages, and also the frequency and voltage magnitude of the weak power grid. The data times-span of the MATLAB simulation performance will be [0 s, 0.4 s] with the sample time 1 μs wherein the dynamic change occurs at t = 0.2 s. As a future work, authors suggest that the proposed hybrid virtual machine can be extended to the electric vehicles-based microgrids in a multi-bus IEEE standard system in presence of energy storage systems.
