The strengthening of electric energy security and the reduction of greenhouse gas emissions have gained enormous momentum in previous decades. The integration of large-scale intermittent renewable energy resources (RER) like wind energy into the existing electricity grids has increased significantly in the last decade. However, this integration poses many operational and control challenges that hamper the reliable and stable operation of the grids. This article aims to review the reported challenges caused by the integration of wind energy and the proposed solutions methodologies. Among the various challenges, the generation uncertainty, power quality issues, angular and voltage stability, reactive power support, and fault ride-through capability are reviewed and discussed. Besides, socioeconomic, environmental, and electricity market challenges due to the grid integration of wind power are also investigated. Many of the solutions used and proposed to mitigate the impact of these challenges, such as energy storage systems, wind energy policy, and grid codes, are also reviewed and discussed. This paper will assist the enthusiastic readers in seeing the full picture of wind energy integration challenges. It also puts in the hands of policymakers all aspects of the challenges so that they can adopt sustainable policies that support and overcome the difficulties facing the integration of wind energy into electricity grids.

World leaders and scientists have been putting immense efforts into strengthening energy security and reducing greenhouse gas (GHG) emissions by meeting growing energy demand for the last couple of decades. Their efforts accelerate the need for large-scale renewable energy resources (RER) integration into existing electricity grids. The intermittent nature of the dominant RER, e.g., solar photovoltaic (PV) and wind systems, poses operational and technical challenges in their effective integration by hampering network reliability and stability. This article reviews and discusses the challenges reported due to the grid integration of solar PV systems and relevant proposed solutions. Among various technical challenges, it reviews the non-dispatch-ability, power quality, angular and voltage stability, reactive power support, and fault ride-through capability related to solar PV systems grid integration. Also, it addresses relevant socio-economic, environmental, and electricity market challenges. Finally, it highlights the proposed solution methodologies, including grid codes, advanced control strategies, energy storage systems, and renewable energy policies to combat the discussed challenges. The findings of this article assist the power system scholars and researchers in conducting further research in this field. Furthermore, it helps the decision-makers to choose the appropriate technologies to deal with the anticipated challenges associated with the grid integration of PV systems.

Several issues have been reported with the expansion of the electric power grid and the increasing use of intermittent power sources, such as the need for expensive transmission lines and the issue of cascading blackouts, which can adversely affect critical infrastructures. Microgrids (MG) has been widely accepted as a viable solution to improve grid reliability and resiliency, ensuring continuous power supply to loads. However, to ensure the effective operation of the Distributed Energy Resources (DER), Microgrids need to have Energy Management and Control Systems (EMCS). Therefore, considerable research has been conducted to achieve smooth profiles in grid parameters during operation at optimum running cost. This paper aims to provide a review of EMCS techniques that have evolved in recent years. Firstly, the fundamentals of microgrids are discussed for a general overview of the field. Then, a critical literature review is undertaken for the various methods applied for EM optimization in microgrid applications. Multiple factors have been explored in the objective functions throughout this review, including MG daily operational costs, energy storage degradation, revenue through trading with the grid or other parties, and Greenhouse Gas (GHG) emissions. A review of control systems has been conducted next by categorizing them based on the different applications in MGs for stable operation. This paper also focuses on IEEE standards related to MG operation and control to facilitate other researchers to build upon a standardized set of rules and to enhance the interoperability of the diverse EMCS techniques.

A significant growth in solar photovoltaic (PV) installation has observed during the last decade in standalone and grid-connected power generation systems. The solar PV system has a non-linear output characteristic because of weather intermittency, which tends to have a substantial effect on overall PV system output. Hence, to optimize the output of a PV system, different maximum power point tracking (MPPT) techniques have been used. But, the confusion lies while selecting an appropriate MPPT, as every method has its own merits and demerits. Therefore, a proper review of these techniques is essential. A “ Google Scholar ” survey of the last five years (2015-2020) was conducted. It has found that overall seventy-one review articles are published on different MPPT techniques; out of those seventy-one, only four are on uniform solar irradiance, seven on non-uniform and none on hybrid optimization MPPT techniques. Most of them have discussed the limited number of MPPT techniques, and none of them has discussed the online and offline under uniform and hybrid MPPT techniques under non-uniform solar irradiance conditions all together in one. Unfortunately, very few attempts have made in this regard. Therefore, a comprehensive review paper on this topic is need of time, in which almost all the well-known MPPT techniques should be encapsulated in one paper. This article focuses on classifications of online, offline, and hybrid optimization MPPT algorithms, under the uniform and non-uniform irradiance conditions. It summarizes various MPPT methods along with their mathematical expression, operating principle, and block diagram/flow charts. This research will provide a valuable pathway to researchers, energy engineers, and strategists for future research and implementation in the field of maximum power point tracking optimization.

Drones, also known as unmanned aerial vehicles (UAVs), have gained numerous applications due to their low cost, ease of use, vertical takeover and landing, and ability to operate in high-risk or hard-to-reach areas. The contribution of this review is that of building the bridge between drone technology and its application and advancements in the field of Geographic Information System (GIS). The integration of drones and GIS is valuable as it reduces costs and improves accessibility for geospatial data collection. Traditional methods involving aircraft for aerial photography are expensive, requiring the hiring of aircraft, pilots, and photographers. Drones equipped with advanced cameras and artificial intelligence software can replace the conventional technique and at the same time, be economical and time-efficient. The integration of drones and GIS is expected to bring revolutionary benefits in the fields of precision agriculture, urban planning, emergency health response, disaster management, the development of smart cities, food delivery, etc. In this paper, a state-of-the-art review of the deployment of drone-integrated GIS applications in different fields is presented. Numerous techniques and associated challenges related to their development, formulation, implementation, and regulation are highlighted. It has been concluded that drone-integration solutions in GIS improve efficiency and accuracy, enhance the decision-making process, and facilitate better real-time monitoring. The findings of this review paper are intended to help and benefit researchers, business developers, emergency service providers, industrialists, and policymakers.

Detection and classification of any anomaly at its commencement are very crucial for optimal management of assets in power system grids. This paper presents a novel hybrid approach that combines S-transform (ST) and feedforward neural network (FFNN) for the detection and classification of distribution grid faults. In this proposed strategy, the measured three-phase current signals are processed through ST with a view to extracting useful statistical features. The extracted features are then fetched to FFNN in order to detect and classify different types of faults. The proposed approach is implemented in two different test distribution grids modeled and simulated in real-time digital simulator and MATLAB/SIMULINK. The obtained results justify the efficacy of the presented technique for both noise-free and noisy data. In addition, the developed technique is independent of fault resistance, inception angle, distance, and prefault loading condition. Besides, the comparative results confirm the superiority and competitiveness of the developed technique over the available techniques reported in the literature.