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 MG using virtual impedance as droop control is emerging without adequate power flow studies. In this paper, power flow analyses for both ac and dc MGs are formulated and implemented. The mathematical models for both types of MGs considering the concept of virtual impedance are used to be in conformity with the practical control of the DGs. As a result, calculation accuracy is improved for both ac and dc MG 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 DGs is also conducted by using proposed method.

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 to regulate the active power. Each DES unit is taken as an agent and it schedules its own frequency reference given of the real power droop controller according to the SoC values of all other DES units. Further, to obtain the average SoC value of DES, the dynamic average consensus algorithm is utilized by each agent. A generalized small-signal model of the proposed frequency scheduling for the proposed frequency scheduling is developed in order to verify the stability of the control system and to guide control parameters design. The convergence characteristics for the dynamic consensus adopted in the multiagent system are also analyzed to choose the proper control parameter. Experimental results verified the effectiveness, the robustness against communication topology changes, and capability of “plug & play” for the proposed multiagent system through different case studies.

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.

This paper summarizes the technical endeavors undertaken by the Task Force (TF) on Cyber-Physical Interdependence for Power System Operation and Control. The TF was established to investigate the cyber-physical interdependence of critical power system elements and their influence on the operation and control of energy systems. State-of-the-art analysis techniques, including co-simulation and digital twin technologies, are employed to address various layers of interdependence between cyber and physical systems, facilitating the identification of potential threats and vulnerabilities. The paper examines prospective trajectories for resilient cyber-physical systems and outlines the educational and workforce training imperatives for addressing cybersecurity threats in contemporary power systems. Furthermore, concluding remarks and future recommendations are provided to mitigate the inherent vulnerabilities within the extensively interoperable grid infrastructure.

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, a distributed multiagent based algorithm is proposed to achieve SoC balance for DES in the DC microgrid by means of voltage scheduling. Reference voltage given is adjusted instead of droop gain. Dynamic average consensus algorithm is explored in each agent to get the required information for scheduling voltage autonomously. State-space analysis on a single energy storage unit and simulation verification shows that the proposed method has two advantages. Firstly, modifying the reference voltage given has less impact on system stability compared to gain scheduling. Secondly, by adopting multiagent methodology, the proposed distributed control has less communication dependence and more reliable during communication topology changes.