In the Low-Voltage (LV) AC microgrids (MGs), with a relatively high R/X ratio, virtual impedance is usually adopted to improve the performance of droop control applied to Distributed Generators (DGs). At the same time, LV DC microgrid using virtual impedance as droop control is emerging without adequate power flow studies. In this paper, power flow analyses for both AC and DC microgrids are formulated and implemented. The mathematical models for both types of microgrids considering the concept of virtual impedance are used to be in conformity with the practical control of the distributed generators. As a result, calculation accuracy is improved for both AC and DC microgrid power flow analyses, comparing with previous methods without considering virtual impedance. Case studies are conducted to verify the proposed power flow analyses in terms of convergence and accuracy. Investigation of the impact to the system of internal control parameters adopted by distributed generators is also conducted by using proposed method.

In this paper, an economic dispatch problem for total operation cost minimization in DC microgrids is formulated. An operating cost is associated with each generator in the microgrid, including the utility grid, combining the cost-efficiency of the system with demand response requirements of the utility. The power flow model is included in the optimization problem, thus the transmission losses can be considered for generation dispatch. By considering the primary (local) control of the grid-forming converters of a microgrid, optimal parameters can be directly applied to this control level, thus achieving higher control accuracy and faster response. The optimization problem is solved in a heuristic method. In order to test the proposed algorithm, a six-bus droop-controlled DC microgrid is used in the case studies. Simulation results show that under variable renewable energy generation, load consumption and electricity prices, the proposed method can successfully reduce the operating cost by dispatching economically the resources in the microgrid.

In this paper, a multiagent based distributed control algorithm has been proposed to achieve state of charge (SoC) balance of distributed energy storage (DES) units in an AC microgrid. The proposal uses frequency scheduling instead of adaptive droop gain. Each DES unit is taken as an agent and they schedule their own frequency reference given of the real power droop controller according to the SoC values of the other DES units. Further, to obtain the average SoC value of DES, dynamic average consensus algorithm is adapted by each agent. A smallsignal model of the system is developed in order to verify the stability of the control system and control parameters design. Simulation results demonstrate the effectiveness of the control strategy and also show the robustness against communication topology changes.

A dynamic consensus algorithm (DCA)-based coordinated secondary control with an autonomous current-sharing control strategy is proposed in this paper for balancing the discharge rate of energy storage systems (ESSs) in an islanded AC microgrid. The DCA is applied for information sharing between distributed generation (DG) units to regulate the output power of DGs according to the ESS capacities and state-of-charge (SoC). Power regulation is achieved by adjusting the virtual resistances of voltage-controlled inverters with an autonomous current-sharing controller. Compared with existing methods, the proposed approach can provide higher system reliability, expandability, and flexibility due to its distributed control architecture. The proposed controller can effectively prevent operation failure caused by over-current and unintentional outage of DGs by means of balanced discharge rate control. It can also provide fast response and accurate current sharing performance. A generalizable linearized state-space model for n-DG network in the z-domain is also derived and proposed in this paper; the model includes electrical, controller, and communication parts. The system stability and parameter sensitivity have been analyzed based on this model. To verify the effectiveness of the proposed control approach, this study presents simulation results from a ten-node network and a comparison between experimental results obtained from the conventional power sharing control and the DCA-based SoC coordinated control in a setup with three 2.2 kW DG units.

In this paper we present a distributed control method for minimizing the operation cost in DC microgrid based on multiagent system. Each agent is autonomous and controls the local converter in a hierarchical way through droop control, voltage scheduling and collective decision making. The collective decision for the whole system is made by proposed incremental cost consensus, and only nearest-neighbor communication is needed. The convergence characteristics of the consensus algorithm are analyzed considering different communication topologies and control parameters. Case studies verified the proposed method by comparing it without traditional methods. The robustness of system is tested under different communication latency and plug and play operation.