Micro-Grid (MG), a paradigm shift in conventional distribution power systems, facilitates the integration of many Renewable Energy Resources (RERs), storage units, and loads. The key catalyst behind this emerging paradigm is the increased attention to environment-energy sustainability nexus. This novel concept exhibits various attractive features such as sustainability, reliability, resilience, improved power quality, energy security, and liberalization of electric service industries. However, the integration of RER units and load participation into the MG brings various challenges to the stability and operation of the system. These challenges arise as a consequence of the intermittent nature of RERs due to their stochastic behavior and increased level of non-linearity associated with smart load participation. Furthermore, in recent years, the development and deployment of RER in MG networks have demonstrated exponential growth. Therefore, in order to achieve a holistic analysis, a comprehensive review study about various aspects of MG should be investigated. In this regard, this rigorous survey paper presents the meticulous study of various aspects, historical evolution, and key enabling yet transdisciplinary technologies of MG, such as various components, generation resources, load classification, communication infrastructure, energy management, control and optimization, operational modes, and various frameworks, configurations, architectures, and topologies-including the emerging concept of Networked MG with flexible boundaries. This study also reviewed various storage and protection systems in MG, considering the attention to their contributions to the stability of the system. This review also underscores many key issues, challenges, and factors related to the sustainable development of the MG system. Lastly, an all-inclusive cross-sectoral analysis that includes cyber-physical systems, power quality, information and data management, conversion systems, synthetic inertia, and some governance issues has been provided, along with the future directions, progression, and latest development in the field of MG. This survey, therefore, greatly assists and enables researchers to study and analyze the development and prospect of MG technology conveniently.

In this paper, direct model predictive control (DMPC) of the noninverting buck-boost DC-DC converter with magnetic coupling between input and output is proposed. Unlike most of the other converters, the subject converter has the advantage of exhibiting minimum phase behavior in the boost mode. However, a major issue that arises in the classical control of the converter is the dead zone near the transition of the buck and boost mode. The reason for the dead zone is practically unrealizable duty cycles, which are close to zero or unity, of pulse width modulation (PWM) near the transition region. To overcome this issue, we propose to use DMPC. In DMPC, the switches are manipulated directly by the controller without the need of PWM. Thereby, avoiding the dead zone altogether. DMPC also offers several other advantages over classical techniques that include optimality and explicit current constraints. Simulations of the proposed DMPC technique on the converter show that the dead zone has been successfully avoided. Moreover, simulations show that the DMPC technique results in a significantly improved performance as compared to the classical control techniques in terms of response time, reference tracking, and overshoot.

This article proposes a segmented and double stator flux switching linear hybrid excited machine (SDSFSLHEM). To reduce the machine’s iron loss and overall cost, the proposed SDSFSLHEM utilizes a segmented stator. At both ends of the mover, assistant teeth compensate for the unbalance in the three-phase flux, which is a common problem in linear machines. Field excitation (FE) is used, which adds flux regulation capability to the proposed machine and allows it to operate at a wide range of speeds. A magnetic equivalent model (MEM) is used to find the best coil combination and no-load flux linkage, to reduce computational time. The leading design parameters of the machine are globally optimized by multiobjective genetic global optimization, while keeping the slot area, electric, and magnetic loadings constant. The optimization improved peak-to-peak flux linkage by 12%, thrust force by 34.7%, thrust ripples by 17.97%, and detent force by 10.07%. Compared to the flux switching permanent magnet (PM) machine proposed in the literature, the proposed machine reduces the volume of the PM by 39.18% and provides 31.2% higher thrust force and thrust density.

In the complex environment of microgrid deployments targeted at geographic regions, the seamless integration of renewable energy sources meets a variety of essential challenges. These include the unpredictable nature of renewable energy, characterized by intermittent energy generation, as well as ongoing fluctuations in load demand, the vulnerabilities present in distribution network failures, and the unpredictability that results from unfavorable weather conditions. These unexpected events work together to disturb the delicate balance between energy supply and demand, raising the alarming threat of system instability and, in the worst cases, the sudden advent of damaging blackouts. To address this issue, a fuzzy logic-based energy management system has been developed to monitor, manage, and optimize energy consumption in microgrids. This study focuses on the control of diesel generators and utility grids in a grid-connected microgrid which manages and evaluates numerous energy consumption and distribution features within a specified system, e.g., building or a microgrid. An energy management system is suggested based on fuzzy logic as a swift fix for complications with effective and competent resource management, and its presentation is compared with both the grid-connected and off-grid modes of the microgrid. In the end, the results exhibit that the proposed controller outclasses the predictable controllers in dropping sudden variations that arise during the addition of sources of renewable energy, supporting the refurbishment of the constant system.

Axial flux permanent magnet (AFPM) machines are good candidates for electric vehicle applications due to their high torque density, improved efficiency, and better flux distribution; thus, they are often used. A dual-rotor single-stator AFPM machine with four differently shaped permanent magnet (PM) rotors is investigated. The main aim of this paper is to enhance the average torque while minimizing the cogging torque and torque ripples at the expense of low PM volume. The proposed machines are analyzed in terms of flux linkage, back-EMF, cogging torque, average torque, and torque ripples. The analysis reveals that the machine with an arc-shaped PM rotor performs better than the others. In addition, the trapozoidal arc-shaped PM used in the AFPM machine outperforms the hexagonal, skew arc, and traditional trapezoidal PMs. The torque density of the trapezoidal-shaped PM machine is 40.23 (KNm/${\mathrm{m}}^3$), while that of the hexagonal shape is 32.46 (KNm/${\mathrm{m}}^3$), that of the skew arc shape is 39.78 (KNm/${\mathrm{m}}^3$), and that of the arc shape is 50.38 (KNm/${\mathrm{m}}^3$).