The topic of microgrids (MGs) is a fast-growing and very promising field of research in terms of energy production quality, pollution reduction and sustainable development. Moreover, MGs are, above all, designed to considerably improve the autonomy, sustainability, and reliability of future electrical distribution grid. At the same time, aspects of MGs energy management, taking into consideration distribution generation systems, energy storage devices, electric vehicles, and consumption components have been widely investigated. Besides, grid architectures including DC, AC, or hybrid power generation systems, energy dispatching problems modelling, operating modes (islanded or grid connected), MGs sizing, simulations and problems solving optimization approaches, and other aspects, have been raised as topics of great interest for both electrical and computer sciences research communities. Furthermore, the United Nations Framework Convention on Climate Change and government policies and incentives have paved the way to massive electric vehicle (EV) deployment. Hence, several research studies have been conducted to investigate the integration of EVs in national power grid and future MGs. Specifically, EV charging stations’ bi-directional power flow control and energy management have been considerably explored. These issues index challenging research topics, which are in most cases still under progress. This paper gives an overview of MGs technology advancement in recent decades, taking into consideration distributed energy generation (DER), energy storage systems (ESS), EVs, and loads. It reviews the main MGs architecture, operating modes, sizing and energy management systems (EMS) and EVs integration.

Motor current signature analysis (MCSA) is a well-proven technique for electrical and mechanical faults detection in induction motors. The appearance of stator current components or increase of magnitude of some components at characteristic frequencies indicates a motor fault condition. In this paper, we propose a new MCSA fault detector based on a matched subspace technique. The proposed detector consists of three steps. First, the influence of the fundamental supply frequency is removed from the current signal using an interference cancellation technique based on oblique projection. Then, the fault-related frequency is estimated from the interference-free signal using the maximum likelihood principle. Finally, the fault detection is performed using a generalized likelihood ratio test. Simulation and experimental results illustrate the effectiveness of the proposed approach for eccentricity fault, bearing faults, and broken rotor bars detection.

Neodymium-boron (NdFeB) permanent magnets (PMs) have been widely studied in the past years since they became the material of choice in permanent magnet synchronous machines (PMSMs). Although NdFeB PMs have a better energy density than other types of magnets and are cost-effective, their magnetization is very sensitive to the PMSM operating conditions, in particular temperature, where the irreversible demagnetization degree increases over time. Therefore, it is important to characterize and diagnose demagnetization at an early stage. In this context, this paper proposes a two-step analysis study dealing with both uniform and partial demagnetization. A 2D finite element method-based (FEM) approach is used for demagnetization characterization, and then a PMSM motor current signature analysis (MCSA) approach, based on fast Fourier transform (FFT), is considered where fault cases harmonics are considered as faults indices to detect demagnetization. In some situations, the proposed two-step approach achieved results that clearly allow distinguishing and characterizing demagnetization. Indeed, a local demagnetization introduces specific sub-harmonics while a uniform demagnetization leads to the current amplitude increase for a given torque.

The vehicle-to-grid concept emerged very quickly after the integration of renewable energy resources because of their intermittency and to support the grid during on-peak periods, consequently preventing congestion and any subsequent grid instability. Renewable energies offer a large source of clean energy, but they are not controllable, as they depend on weather conditions. This problem is solved by adding energy storage elements, implementing a demand response through shiftable loads, and the vehicle-to-grid/vehicle-to-home technologies. Indeed, an electric vehicle is equipped with a high-capacity battery, which can be used to store a certain amount of energy and give it back again later when required to fulfill the electricity demand and prevent an energy shortage when the main-grid power is limited for security reasons. In this context, this paper presents a comparative study between two home microgrids, in one of which the concept of vehicle-to-home is integrated to provide a case study to demonstrate the interest of this technology at the home level. The considered microgrid is composed of renewable energy resources, battery energy storage, and is connected to the main grid. As the vehicle is not available all day, in order to have consistent results, its intervention is considered in the evening, night, and early morning hours. Two case studies are carried out. In the first one, the vehicle-to-home concept is not taken into account. In this case, the system depends only on renewable resources and the energy storage system. Subsequently, the electric vehicle is considered as an additional energy storage device over a few hours. Electric vehicle integration brings an economic contribution by reducing the cost, supporting the other MG components, and relieving the main grid. Simulation results using real weather data for two cities in France, namely Brest and Toulon, show the effectiveness of the vehicle-to-home concept in terms of cost, energy self-sufficiency, and continuity of electrical service.

With the need for more environmentally friendly transportation and the wide deployment of electric and plug-in hybrid vehicles, electric vehicle (EV) charging stations have become a major issue for car manufacturers and a real challenge for researchers all over the world. Indeed, the high cost of battery energy storage, the limited EV autonomy and battery lifespan, the battery charging time, the deployment cost of a fast charging infrastructure, and the significant impact on the power grid are the origin of several research projects focused on advanced power electronics topologies and the optimization of the EV charging stations in terms of power transfer and geographical location. Three charging levels can be distinguished, which differ in terms of output power and charging time. The higher the level of charging, the faster the charging process, as more power is delivered to the vehicle at the expense of power quality issues and disturbances. Moreover, three types of charging systems can be distinguished, which are inductive recharging (contactless power transfer), conductive charging systems, and battery swapping. Additionally, EVs encompass fuel cell (FC) EVs, which uses hydrogen as primary energy resources, which is nowadays under extensive research activities in academia and industry. This review paper aims at presenting a state of the art review of major advances in power electronics architectures for EVs traction drives, and battery-based EVs charging stations. Specifically, the focus is made on light-duty electric vehicles drivetrain power electronics and charging stations specifications, the proposed power electronics solutions, the advantages and drawbacks of all these technologies, and perspectives for future research works in terms of smart EV charging and up-to-date solutions for power system disturbances mitigation.