Microgrids consisting of photovoltaic (PV) power plants and wind farms have been widely accepted in power systems for reliability enhancement and power loss reduction. Microgrids are capable of providing voltage and frequency support, improving power quality, and achieving proper power-sharing. To achieve such goals and deal with the nonlinear behavior in such systems, appropriate robust control strategies are required to be adopted. This article presents a comprehensive review of robust control methods for microgrids, including AC, DC, and hybrid microgrids, with different topologies and different types of interconnection to conventional power systems based on recently published research studies. The main control objectives, along with proposed control methods, are comparatively discussed for different types of microgrids. Furthermore, several research gaps in this area related to the scalability, robustness assessment, and evaluation approach are discussed. Recommendations are made that can potentially open new research lines to enhance the effectiveness of robust controllers for AC, DC, and hybrid microgrids.

High voltage direct current (HVDC) systems are now well integrated into AC systems in many jurisdictions. The integration of renewable energy sources (RESs) is a major focus and the role of HVDC systems is expanding. However, the protection of HVDC systems against DC faults is a challenging issue that can have negative impacts on the reliable and safe operation of power systems. Practical solutions to protect HVDC grids against DC faults without a widespread power outage include: 1) using DC circuit breakers (CBs) to isolate the faulty DC-link, 2) using a proper converter topology to interrupt the DC fault current, and/or 3) using high-power DC transformers and DC hubs at strategic points within DC grids. The application of HVDC CBs is identified as the best approach that satisfies both DC grids and connected AC grids' requirements. This article reports a comprehensive review of HVDC CBs technologies, including recent significant attempts in the development of modern HVDC CBs. The functional analysis of each technology is presented. Additionally, different technologies based on information obtained from literature are compared. Finally, recommendations for the improvement of CBs are presented.

Since the discovery of Photovoltaic (PV) effect, numerous ways of utilizing the energy that can be generated by the free everlasting solar radiation using solar panels were put forward by many researchers. However, the major disadvantage of solar panel to date is its low efficiency, which is affected by the panel temperature, cell type, panel orientation, irradiance level, etc. Though there are certain multi-junction solar panels that offer higher efficiencies, their application is very minimal due to high manufacturing cost. With the growing demand for the reduction of carbon footprint, there is a need to use and manufacture these panels in the most effective way to harness the maximum power and increase their efficiency. Another major concern is the availability of land/space for the installation of these panels. Several authors have focused on discussing the different technologies that have evolved in the manufacturing of the PV cells along with their architectures. However, there exists a gap that needs to be addressed by combining the latest PV technologies and architectures with a focus on PV applications for increasing the efficiency. Due to the technical limitations on the efficiency of PV panels, applications are to be designed that can extract the maximum power from the PV systems by minimizing the technical difficulties. Considering all these factors, this paper presents an overview of the types of silicon based solar cell architectures with efficiencies of at least 25%, and different integration methods like Building integrated PVs (BIPV), floating PVs, which can increase the efficiency by harnessing more power from a limited space. An extensive bibliography on the PV cell structures and methods of maintaining the efficiencies in real world installations are presented. The challenges with the integration of solar panels and the future work are also discussed. This work benefits the readers and researchers and serves as a basis to understand the solar panel efficiency structure and ways to improve the efficiency and associated challenges to come over in the successful implementation of these systems.

In the near future the conventional fuel-based transportation system is expected to be entirely replaced by Electric Vehicles (EVs) due to their significant environmental benefits. While contemporary charging technologies demonstrate great potential to accelerate the growth of the EV market, several challenges remain to be addressed for their widespread advancement. The primary concerns of EV charging technology include charging time, speed, cost, reliability, power converter performance, and its impact on the utility grid. With this background, this study provides a detailed overview of various charging topologies used in EVs, which encompass the charging methods, power levels, as well as unidirectional and bidirectional AC-DC and DC-DC converters. Each analysis is carried out according to the viewpoints, effects, efficiency, power density, transfer speed, reliability, and limitations of charging converters, for both slow and fast-charging phenomena. It explores diverse EV charging methods, including CC, WC, and swapping stations, focusing on on-board and off-board charging, as well as advanced wireless technologies like inductive, capacitive, and optical charging. Moreover, EV charging impacts on the electrical grid are discussed, focusing on waveform distortion, voltage fluctuations, grid stability, frequency regulation, reactive power compensation, and load management. It emphasizes how EV helps balance out grid oscillations brought on by the unpredictability of the power grid. To explore the current charging techniques and suggest modern solutions, a deep literature assessment is undertaken to identify exciting research gaps. This research bridges gaps in the current model and opens possibilities for future solutions by thoroughly examining EV interactions with the smart grid. Ultimately, this review will aid academics in driving further research and development while offering industry professionals valuable guidance for optimizing and implementing reliable and efficient EV charging solutions.

As grid-connected wind farms become more common in the modern power system, the question of how to maximize wind power generation while limiting downtime has been a common issue for researchers around the world. Due to the complexity of wind turbine systems and the difficulty to predict varying wind speeds, artificial intelligence (AI) and machine learning (ML) algorithms have become key components when developing controllers and control schemes. Although, in recent years, several review papers on these topics have been published, there are no comprehensive review papers that pertain to both AI and ML in wind turbine control systems available in the literature, especially with respect to the most recently published control techniques. To overcome the drawbacks of the existing literature, an in-depth overview of ML and AI in wind turbine systems is presented in this paper. This paper analyzes the following reviews: (i) why optimizing wind farm power generation is important; (ii) the challenges associated with designing an efficient control scheme for wind farms; (iii) a breakdown of the different types of AI and ML algorithms used in wind farm controllers and control schemes; (iv) AI and ML for wind speed prediction; (v) AI and ML for wind power prediction; (vi) AI and ML for mechanical component monitoring and fault detection; and (vii) AI and ML for electrical fault prevention and detection. This paper will offer researchers and engineers in the wind energy generation field a comprehensive review of the application of AI and ML in the control methodology of offshore and onshore wind farms so that more efficient and robust control schemes can be designed for future wind turbine controllers.

The major problem associated with the grid-connected solar photovoltaic (PV) system is the integration of the generated DC power into the AC grid and maintaining the stability of the system. With advancements in research on these PV inverters, artificial intelligence (AI)-based control models are replacing the existing linear methods. These smart PV systems are prone to a variety of attacks, ranging from physical attacks on the PV plants to data integrity attacks and communication-based attacks. This paper provides an overview of the cybersecurity issues with smart PV inverters, their impacts on the grids, and control methods that exist to detect and identify cyber-attacks on a smart PV grid system. An extensive bibliography is provided on grid-forming and grid-following inverters with a variety of control techniques like Proportional–Integral–Derivative (PID) control, fuzzy-based control, and their performances under different fault situations. Multi-level inverter design approaches with various intelligent control techniques to overcome switching failures and other system faults are reviewed. Moreover, some recommendations for future research on intelligent inverters for grid-connected PV systems are proposed. This work will benefit researchers, scientists, and engineers who are working in the field of intelligent inverters for the grid-connected PV system.