Comparative analysis on the stability mechanism of droop control and VID control in DC microgrid

Abstract

Voltage resonance and fluctuation deteriorate the stability of DC microgrids (DC-MGs) and restrict their popularization. Conventional droop control cannot suppress voltage fluctuation and damp oscillations. Therefore, new control methods, namely, droop+filter control and virtual inertia and damping control, are proposed. These methods differ owing to the addition of low pass filter (LPF) and virtual inertia loop. In this study, the stability of these control methods is investigated comprehensively to understand their differences arising from the use of LPF and inertia loop as well as the underlying dynamic stability mechanism. The leading causes of voltage instability in DC-MGs regulated by droop control are first presented. Subsequently, control methods for solving this issue are compared and their simplified small-signal models are constructed. Based on eigenvalue analysis, the DC-MG is equivalent to a third-order system. Different control effects can be acquired by changing the control parameters and the location of the eigenvalues; furthermore, they can be used to understand the dynamic stability. Eigenvalue analysis can provide parameter design guidelines. Finally, the simulation results verify the validity of the theoretical analysis.

An inertia‐emulation‐based cooperative control strategy and parameters design for multi‐parallel energy storage system in islanded DC microgrids

“…With k damp increasing, a different trend from Figure 18 can be observed in Figure 19 [22]. As k damp increases, the time constant of the inertia component gradually decreases, indicating the reduced inertia.…”

Damping Oscillation and Removing Resonance in a RE Based DC Microgrids

“…is the optimal gain matrix that defines a control signal on the basis of the solution of Riccati differential (RD) equation. The optimal gain and Riccati differential equation are respectively given by ( 10) and ( 11) as (10) (11) Thus, the matrix of the system can be written as (12) In this case, a completely new approach of the multivariable LQR controller is proposed. To minimize the cost function , a cheap control approach is considered; and after tuning (i.e., applying a trial and error method), the value of and are respectively selected as and .…”

“…There are a number of advantages of DC microgrid over the AC counterpart such as the absence of reactive power, skin effect, angular and frequency instability problems [1][2][3][4][5]. On the other hand, in terms of economic prospects, DC microgrid is highly efficient, costeffective, and reliable, compared to the AC microgrid [6][7][8][9][10]. Nevertheless, there are some key technical challenges that need to be resolved for making it practical from the research stage.…”

Improved Dynamic Response of DC Microgrid Under Transient Condition Using Inertia by Virtual Generation

“…The battery is used as a reserve source for inertia. The stability of the system with droop control and with virtual inertia droop control is given in [23]. A coordinated control method is developed in [24] for adaptive virtual inertia in AC/DC microgrid.…”