Solar Photovoltaic (PV) systems have been in use predominantly since the last decade. Inverter fed PV grid topologies are being used prominently to meet power requirements and to insert renewable forms of energy into power grids. At present, coping with growing electricity demands is a major challenge. This paper presents a detailed review of topological advancements in PV-Grid Tied Inverters along with the advantages, disadvantages and main features of each. The different types of inverters used in the literature in this context are presented. Reactive power is one of the ancillary services provided by PV. It is recommended that reactive power from the inverter to grid be injected for reactive power compensation in localized networks. This practice is being implemented in many countries, and researchers have been trying to find an optimal way of injecting reactive power into grids considering grid codes and requirements. Keeping in mind the importance of grid codes and standards, a review of grid integration, the popular configurations available in literature, Synchronization methods and standards is presented, citing the key features of each kind. For successful integration with a grid, coordination between the support devices used for reactive power compensation and their optimal reactive power capacity is important for stability in grid power. Hence, the most important and recommended intelligent algorithms for the optimization and proper coordination are peer reviewed and presented. Thus, an overview of Solar PV energy-fed inverters connected to the grid is presented in this paper, which can serve as a guide for researchers and policymakers.

Deep learning (DL) is an exciting field of interest for many researchers and business. Due to a massive leap in DL based research, many domains like Business, science and government sectors make use of DL for various applications. This work puts forward the importance of DL and its application in a few critical electrical segments. Initially, an introduction to Artificial Intelligence (AI) and Machine Learning (ML) is presented. Then the need for DL and the popular architectures, algorithms and frameworks used are presented. A summary of different techniques used in DL is outlined, and finally, a review on the application of deep learning techniques in some popular electrical applications is presented. Five critical electrical applications, namely identification of bearing faults, hot spots on the surface of PV panels, insulator faults, an inspection of power lines and Electric vehicles have been considered for review in this work. The primary aim of this work is to present chronologically, a survey of different areas in which it applies DL along with their architectures, frameworks and techniques to provide a deeper understanding of DL for widespread use in real-time applications.

The multidimensional purposes of grid-tied hybrid renewable system such as tracking of maximum power, increasing the power conversion efficiency, reducing the harmonic distortions in the injected current and control over power injected into the grid are presented in this paper by developing a laboratory-scale setup. To ensure continuous current operation at the shoot through mode of grid connected inverter, a switched Z-source converter is utilized at the PV side. The PWM rectifier connected with the wind turbine transforms AC power into dc. Individual power converters with conventional PI controllers have been dedicated for each power source, and control strategy uses only one reference voltage so as to increase the maximum power tracking speed from both PV and wind sources. The battery energy management is performed by artificial neural network (ANN) to enhance the stable power flow and increase the lifespan of the storage system. Finally, the voltage at the point of common coupling is fed to ANN-based space vector-modulated three-phase inverter and the converted AC power is injected to the grid. The overall system performance is measured by estimating the quality of injected power. A stable operation of the proposed microgrid system is verified by varying input and load at the grid. A continuous-time simulation model is realized in MATLAB and is validated using experimental prototype. This benchmark system provides various research scopes for the future smart grids.

This paper deals with simulation analysis of Selective Harmonic Elimination (SHE) for PV operated Quasi Impedance Source Inverter (q-ZSI) drive system. Electricity generation using Photovoltaic cells is a promising form of sustainable energy. A quasi-Z source inverter (q-ZSI) can minimize the power fluctuations from the electric energy generated by a PV panel. In the existing system, during the discharge of energy stored battery Harmonic Distortion is more. The proposed topology describes an improved ability to compensate power while maintaining a constant dc-link peak voltage with minimum harmonics. It is promising to note that the THD level decreases significantly with the introduction of a closed loop controller with Selective Harmonic Elimination technique. Thus the proposed system provides an efficient means of PV power generation.

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