The global warming problem together with the environmental issues has already pushed the governments to replace the conventional fossil‐fuel vehicles with electric vehicles (EVs) having less emission. This replacement has led to adding a huge number of EVs with the capability of connecting to the grid. It is noted that the presence of such vehicles may introduce several challenges to the electrical grid due to their grid‐to‐vehicle and vehicle‐to‐grid capabilities. In between, the power quality issues would be the main items in electrical grids highly impacted by such vehicles. Thus, this study is devoted to investigating and reviewing the challenges brought to the electrical networks by EVs. In this regard, the current and future conditions of EVs along with the recent research works made into the issue of EVs have been discussed in this study. Accordingly, the problems due to the connection of EVs to the electrical grid have been discussed, and some solutions have been proposed to deal with these challenges.

In this paper, a robust energy management system is proposed for islanded microgrids, which at the same time considers static modeling of system frequency. The aim of this paper is to manage frequency excursions produced from load and renewable generation fluctuations. In microgrids, the use of inertialess and small-scale energy resources risks the frequency stability. In order to overcome this problem, first, the frequency-dependent behavior of the distributed energy resources is formulated precisely within the centralized hierarchical energy and reserve management context of a microgrid. Then, in order to handle microgrid uncertainties in a robust way, information gap decision theory (IGDT) technique is proposed. Furthermore, to address a robust hierarchical energy and frequency reserve management architecture, the problem is transmitted into a single-level mixed integer linear programming model and solved appropriately over a 24-h scheduling time horizon. Numerical simulation results obtained on a typical islanded smart microgrid are presented, including the demand response mechanism. The IGDT can help microgrid central controller (MGCC) to make operational decisions in front of major uncertainties. The obtained results verify that through the proposed IGDT-based energy management system, the MGCC can effectively stabilize the microgrid frequency along with its economic targets while considering severe uncertainties.