Power quality (PQ) monitoring and detection has emerged as an essential requirement due to the proliferation of sensitive power electronic interfacing devices, electric vehicle charging stations, energy storage devices, and distributed generation energy sources in the recent smart grid and microgrid scenarios. Even though, to date, the traditional approaches play a vital role in providing a solution to the above issue, the limitations, such as the requirement of significant human effort and not being scalable for large-scale power systems, force us to think of alternative approaches. Looking at a better perspective, deep-learning (DL) has gained the main attraction for various researchers due to its inherent capability to classify the data by extracting dominating and prominent features. This manuscript attempts to provide a comprehensive review of PQ detection and classification based on DL approaches to explore its potential, efficiency, and consistency to produce results accurately. In addition, this state-of-the-art review offers an overview of the novel concepts and the step-by-step method for detecting and classifying PQ events. This review has been presented categorically with DL approaches, such as convolutional neural networks (CNNs), autoencoders, and recurrent neural networks (RNNs), to analyze PQ data. This paper also highlights the challenges and limitations of using DL for PQ analysis, and identifies potential areas for future research. This review concludes that DL algorithms have shown promising PQ detection and classification results, and could replace traditional methods.

Electric vehicles (EVs) are considered as the leading-edge form of mobility. However, the integration of electric vehicles with charging stations is a contentious issue. Managing the available grid power and bus voltage regulation is addressed through renewable energy. This work proposes a grid-connected photovoltaic (PV)-powered EV charging station with converter control technique. The controller unit is interfaced with the renewable energy source, bidirectional converter, and local energy storage unit (ESU). The bidirectional converter provides a regulated output with a fuzzy logic controller (FLC) during charging and discharging. The fuzzy control is implemented to maintain a decentralized power distribution between the microgrid DC-link and ESU. The PV coupled to the DC microgrid of the charging station is variable in nature. Hence, the microgrid-based charging is examined under a range of realistic scenarios, including low, total PV power output and different state of charge (SOC) levels of ESU. In order to accomplish the effective charging of EV, a decentralized energy management system is created to control the energy flow among the PV system, the battery, and the grid. The proposed controller’s effectiveness is validated using a simulation have been analyzed using MATLAB under various microgrid situations. Additionally, the experimental results are validated under various modes of operation.

Electric transportation will assist in lowering emissions of greenhouse gases and mitigating the impact of rising petrol prices. To promote the widespread adoption of electric transportation, a diverse range of charging stations must be established in an atmosphere that is friendly to users. Wireless electric vehicle charging systems are a viable alternative technology that can charge electric vehicles (EVs) without any plug-in issues. Wireless power transfer (WPT), which involves the transmission of electricity via an electromagnetic field despite the presence of an intervening area, holds out the possibility of new prospects for EVs to increase environmentally responsible mobility. This review article examines the WPT technology and how it might be applied to electric vehicles from both a technical and safety standpoint. The prime aim of this review is (1) to illustrate the current state of the art in terms of technological advances as well as research limitations in the field of WPT development and use within the field of transportation; (2) to organise the experimental the deployment of WPT EV systems in the actual world; and (3) to analyse the results over a sustainable period and to identify limitations as well as chances for growth. From a technical point of view, the progress that has been made on the selection of material for designing coils, different types of coils with a specific focus on the overall performance of the system. As a result, this study aims to provide an extensive overview focusing on the magnetic materials and the architectures of the transmitter and receiver pads.

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