State-Space Modeling and Stability Analysis for Microgrids with Distributed Secondary Control

Abstract

High penetration of renewable energies in power systems leads to the necessity of comprehensive modelling of a microgrid (MG) for its appropriate control. The distributed secondary control in the MG can be used for complementing the role of primary droop-based control. This paper presents a systematic way of developing a linearized small signal state space model with distributed secondary control as well as stability analysis of an islanded AC MG. The MG considered here, consists of three distributed generations (DGs) represented in the synchronous (DQ) reference frame. To show the effect of controller parameters on system stability, the eigenvalue analysis is presented here. The MATLAB/Simulink model of islanded MG with both primary and secondary control strategies is also developed to verify the outcomes of small-signal analysis. The simulation results show that the voltage controller simultaneously achieves the critical voltage restoration and accurate reactive power sharing.

Fuzzy-Based Distributed Cooperative Secondary Control with Stability Analysis for Microgrids

“…The basics of the consensus algorithm and graph theory are described in [13] and thus not included here. In this research, a DSC system was applied locally by selecting the suitable control inputs g i and h i to adjust the frequency f re f i and voltage magnitude v re f i so that the frequency and voltage magnitude at MG nodes converge to the reference values f n and v n , respectively, while active and reactive power sharing are established.…”

“…There are many methods, studied for the development of the stability of the primary control [11][12][13]. Small-signal stability is now a significant issue in the reliable operation of an MG due to low-inertia and intermittent renewables [14].…”

“…Authors in [15] succeeded in precise power sharing considering a consensus-based droop constant controller. Small-signal stability analysis considering DSC is studied in some recent works [7,8,10,13,16,17]. Additionally, the impact assessment of DSC parameters based on the dynamic model, the requirement of fine tuning of DSC parameters for stability enhancement, and the corresponding suitable solution (i.e., fuzzy-based controller) for that are not considered.…”

“…To resolve this issue, suitable and efficient tuning is a prerequisite is significant to accomplish the system stability and have reliable operation against load change and large disturbance. Computational intelligence algorithms such as fuzzy logic (FL) [4,38,39], genetic algorithm (GA) [40,41] and particle swarm optimization (PSO) [13,42] have been commonly used to resolve difficulty of the power system. However, some deficiencies in GA performance such as the premature convergence have been recorded.…”

A Building Block Method for Modeling and Small-Signal Stability Analysis of the Autonomous Microgrid Operation

“…Further improvements of the microgrid model include the addition of control structures like the Phase-Locked Loop (PLL) model presented in [15] and the internal-model based controllers in [16] or microgrid elements such as DC/DC boost converter and ESD models given in [17,18]. The detailed microgrid model with secondary control included becomes even more complicated for modeling, as shown in [19,20], where the procedure for small-signal analysis is described. An idea of microgrid modeling with fewer variables, parameters, and equations is introduced in the form of a reduced system model in [21][22][23].…”