Microgrids gathered a lot of attention in the last decade and are believed to be the future power systems. The renewable energy sources can be easily integrated into the Microgrid. Renewable energy sources such as PV, wind and fuel cells are usually connected through voltage-source inverters in the Microgrid. In order to share the same loads, these inverters are connected in parallel and to achieve the load sharing the control strategy is a must. In this paper, the master-slave control strategy in the dq frame is presented. The reference current signals are sent from the master to the slave converters. A model for master-slave communication-based Microgrid is presented and the system is modeled as a general time delay system. The maximum time delay that guarantees the stability of the system is calculated using a Lyapunov-Krasovskii based linear matrix inequalities method. The communication delay mimics the scenario when the wireless network or the Controller Area Network are used as a communication medium between the inverters.

In this paper, the robust stabilization for the networked microgrid system is presented. A microgrid implements master-slave control architecture where the communication channel is utilized to exchange the reference current signals. With this structure, a time delay exists in the reference control signal which may lead to instability. The analysis of the control strategy is carried out in dq reference frame. The microgrid is constituted by PV and wind energy sources supplying a load through voltage source inverters. The stochastic nature of renewable energy sources introduces uncertainties which can be represented as fluctuations in the voltage and the current. The main contribution of the paper is formulating the controller design of the microgrid with communication delay and uncertainties in the model as H∞ control problem and Lyapunov–Krasovskii functional is utilized to develop stability criterion in bilinear matrix inequality form. Grey wolf optimizer is used to minimize the performance index and derive the stabilizing controller. The microgrid performance is tested through simulation using the time-varying nonlinear model of the microgrid. The results prove that satisfactory current and power-sharing are attained even with the existence of time delays and uncertainties.