With the wide use of new energy and power electronic devices, the problem of low inertia of microgrid (MG) is becoming more and more prominent. In order to solve the problem, this article proposes an event-triggered secondary control strategy for distributed generalized droop control (GDC) considering time delay. First, a distributed event-triggered active power and frequency controllers are established based on GDC, and a distributed voltage controller is designed based on droop control. Second, due to the different frequency parameters of each distributed generator (DG), the tracking controller of frequency and frequency reference model is established by using heterogeneous multiagent theory. Third, the event-triggered function of communication between DGs is constructed, and the stability of the proposed controller is proved. The complicated Lyapunov equation is avoided in the proof process. Finally, the effectiveness of the controller is verified by simulation. The simulation results show that the controller effectively realizes the secondary adjustment of frequency and voltage, reduces the number of communications, and increases the inertia of MG.

At present, the distributed cooperative control method has been widely adopted in the secondary control of the conventional droop-based microgrid (MG). However, its application in the secondary control of Virtual Synchronous Generator (VSG) is relatively lagging. Based on the conventional virtual governor, this paper designs the frequency distributed secondary control strategy of VSG based on the theory of nonlinear heterogeneous multi-agents and presents the distributed active power sharing control strategy. The frequency will converge to the frequency reference value through the consensus protocol, instead of relying on the virtual frequency modulation coefficient. To reduce the communication burden, a control strategy based on event-triggered is adopted in the distributed secondary control. The distributed control is used in frequency strategy, compared with the VSG secondary control proposed previously, the distributed generations (DGs) can collaboratively work. Compared with the existing conventional droop-based distributed secondary control, the proposed scheme retains the characteristics of VSG and can provide virtual inertia to MG. An islanded microgrid test system was established to verify the proposed control strategy. The results show that the proposed control strategy can restore the frequency to the reference value and accurately share the active power, while greatly reducing the communication burden.

There are some existing power management methods considering economic factors, but these methods are limited by fixed structure of microgrid (MG) and mathematical model, which will be out of effect once the structure changes. In order to obtain the optimal power allocation scheme, this paper proposed the grey wolf optimization (GWO) for the distributed hierarchical control structure of MG, considering the economic dispatching problem. Firstly, the distributed generators (DGs) of MG are considered as multi-agent system, and the secondary controller is constructed. Secondly, the objective function and constraints of GWO are established. Thirdly, the calculation results of GWO are taken as the input of secondary controller, which are called virtual rated power (VRP). Finally, by adjusting VRP dynamically, the on-line real-time optimal power distribution of MG is achieved, and the system stability is proved by multi-agent consensus theory. This power allocation scheme is more flexible to realize the plug-and-play capability. The simulation model is established in Matlab/Simulink environment, and the simulation results show that the method is effective.

A decentralized hierarchical control strategy with communication time-varying delay is designed for microgrid (MG) to enhance the voltage and frequency regulation. Recently, event-triggered consensus algorithm is used to reduce energy consumption. To improve the communication reliability, data loss due to communication interruption is considered in this article. First, each distributed generator (DG) of MG is regarded as an agent. Based on multiagent consistency theory, the distributed secondary controller is established. Second, the event trigger function of the secondary controller is constructed, and the stability of the secondary controller is proved by Lyapunov theorem. Third, a data predictive controller is established to train and learn the historical voltage, frequency, and active power of MG by using the improved extreme learning machine (ELM) algorithm. When communication is interrupted, the ELM controller is triggered and the lost data is compensated in time. Finally, the effectiveness of the control strategy is verified by simulation. Simulation results show that the proposed control strategy effectively adjusts the frequency and voltage, realizes accurate active power sharing, reduces the communication burden, and improves the reliability of MG.