Energy extraction from renewable sources and its utilization in Electric Vehicles (EVs) have paved the way for greener transportation options. Battery charging is the present-day challenge in EVs. Constant Current (CC) and Constant Voltage (CV) charging methods have many advantages over other EV battery charging techniques. A fuel cell, being one of the ways of producing DC energy, can be directly used to charge batteries in EVs. With the fuel cell being the DC source, the on-board fast charging can be easily achieved by various power converters, but the Single-Ended Primary Inductor Converter (SEPIC) would serve most efficiently for the aforementioned scenario. In CC method, battery may overcharged if battery reaches full charge mode as current is constant and similarly in CV method in initial stages current drawn by battery is high which may cause temperature to rise to undesired values. To overcome these disadvantages the CC-CV charging can be switched according to the requirements using automated Fuzzy Logic Controller (FLC). The CC-CV charging of the EV battery using SEPIC with the help of a fuel cell through FLC has been proposed and simulated using MATLAB/Simulink software, and the results have been discussed.

The efficiency of a nation’s progress is determined by a variety of factors; however, transportation plays a critical role in boosting progress because it facilitates trade and communication between countries. The majority of transportation is powered by fossil fuels such as gasoline or diesel, which will be depleted in less than 50 years. Another option is to operate transportation systems after replacing conventional vehicles with electric vehicles (EV). Powering these vehicles with green electricity contributes zero carbon emissions from production to the final product. Together with the controller, an efficient charger ensures that the entire system is reliable and stable. The current work focuses on charging an off-board EV from greener energy sources (both a fuel cell and PV array forming a micro-grid) based on their availability via an efficient converter controlled by an adaptive multi-objective controller. A novel multi-output-based adaptive neuro fuzzy inference system (ANFIS) controller for charging the off-board EV at a constant current and voltage for both line and load regulations is proposed, in the current work. A comparison study of grid partitioning and subtractive clustering was conducted in order to select an optimized algorithm for generating FIS. Novelty is achieved by ensuring closed-loop stability is the main aim of the work. The entire work was created with the MATLAB/Simulink software.

Due to advances in the renewable energy technology, solar street lights are emerging as the new technology in smart cities. The solar street lights are powered by solar panels which generally light using LED’s connected in different combinations. These street lights are provided with rechargeable batteries which are charged by solar panel. Being an intermittent source, the idea of integrating the two renewables which could work when any of the sources is unavailable to produce energy is the notion of this work. By integrating solar with piezo electricity could reduce the emphasis on solar power and improve the overall efficiency of charging of battery. The integration of renewables has been done through connecting these sources with Dual Input Single Output (DISO) buck converter. A few modifications have been done on the DISO converters design and modelling which are present in the literature and achieved a new configuration. An automated (Embedded C programmed) switches have been provided parallelly to the sources as to provide path when any source is unavailable. The whole system has been simulated in MATLAB/Simulink and its respective results has been discussed. A hardware prototype for similar idea has been discussed. An extension of this work to state health monitoring (SHM) based Solar Impulse jet plane has been proposed and discussed the same.

With increasing electric power demands, the fossil fuels cannot be continuously burnt, which will adversely affect the mother earth. The conventional ways of producing electric power should be renewed by moving towards the new greener ways of electric power production. In this paper, the discussion of the various types of wave energy converters with emphasis on Pelamis wave energy alongside stating the related works in the grid integration studies, energy storage, control efficiency, and the life cycle assessment of the Pelamis machine is depicted. Greener energy includes all renewable sources that nature provides us with like wave, wind, solar, hydro energies. This should be done with scientific temper and dedication. In this work, the chief aspect covered is ocean waves as an energy source. Several details of this magnum opus have been listed such as different types of WEC, power quality, challenges faced. And one of the successful models under this category is Pelamis WEC, which is discussed in great detail.

Electrical energy extraction from non-conventional energy sources such as solar, wind, etc., is very essential nowadays due to the huge electricity demand. The integration of these sources into the grid/electrical loads face many technical challenges like grid synchronization, power oscillations, etc., The modern wind power plants use Doubly Fed Induction Generator (DFIG) based WTGs as it has embedded Rotor Side Converter (RSC) and Stator Side Converter (SSC). This paper focuses on the performance analysis of standalone Doubly Fed Induction Generator (DFIG) based Wind Turbine using a new control strategy at RSC side. The RSC control is developed with the use of a linear regression algorithm under the Machine Learning (ML) technique. The effectiveness of the controller is validated using MATLAB/Simulink for the different operating conditions such as varying wind speed and load variations etc., The experimental setup of RSC is implemented in hardware and the results are discussed.

Blackouts could occur due to various faults and in order to keep the power stations running constantly to avoid consumers losing power a backup plan is necessary. Black start is the process of restoring power to the electric power stations. The Modular Multilevel Converter (MMC) topology has been propitious technology in High Voltage DC (HVDC) system. The research in MMC technology has significantly increased. The MMC based HVDC system has many advantages when compared to the other technology based HVDC system. In this paper, Black Start Operation using a MMC Based HVDC system is proposed to provide continuous power to the load for a certain period of time within which alternative methods of power generation can be made ready. The paper also provides a mathematical model of a continuous equivalent circuit of the MMC Phase Leg. The efficiency of the proposed idea has been verified by MATLAB/Simulink Software and discussed.