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The current needs of more nonlinear loads and the frequent usage of single-phase loads in three-phase system drastically create power quality issues in the grid-connected system. As a consequence, it creates an undesirable power quality issue (PQI) in the form of a change in the nature of voltage and current magnitude and waveforms in the power system. The voltage-related PQI leads to a huge disturbance in the system when compared with the current-related PQI. The hybrid series active power filter provides grids with the required voltage in series and suppresses the voltage-related harmonics caused by grid-connected nonlinear loads. The present work deals with an adaptive neurofuzzy inference system controller for the generation of a reference voltage signal that uses a reduced active filter rating. The simulation study was done in the MATLAB 2020b/Simulink environment and the experimental effectiveness of the proposed ANFIS controller was compared with that of a conventional controller. In the grid-connected system, this system prevents voltage quality problems such as voltage sag, flickering, voltage swell, neutral currents, and reactive power. The renewable energy sources interfaced into the DC-link minimize short and long voltage challenges so that they improve the overall performance of the system. In accordance with IEEE standard 519-1992, a prototype model was proved to demonstrate that the power delivery system works effectively under different conditions and reduces the total harmonic distortion by approximately 30%, which is less than the 5% acceptable limit.

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Concerns about pollution, climate change, limited fossil fuel supplies, and the desire to eliminate energy dependency have sparked a surge in interest in electric vehicles (EVs). EV requirements have resulted in a variety of difficulties and remedies in EV technology. One of them is the use of DC-DC converters to transfer the level of voltage from the battery in an EV to other needed voltage levels. An independent converter for each operating voltage might be used as a remedy. On the other hand, single input multiple output (SIMO) converters can be utilized to decrease costs, reduce switching loss, and thus enhance the system efficiency. In this paper, a nonisolated step-up converter with the integration of the Luo network is proposed for multiple outputs (24 V and 48 V). In electric vehicles, 48 V is utilized for battery backup, while 24 V is utilized for the horns, headlights, telematics, or the microcontroller. The experimental observations of a 36 V, 600 mA, 24 W prototype confirm the theoretic examination and demonstrate the advantages of the proposed converter over other multioutput converters. The STM microcontroller, based on an ARM cortex microprocessor, is linked into the Luo network for making pulses. The proposed converter achieves 94.2% efficiency at full power. The proposed converter’s performance is evaluated through MATLAB/SIMULINK software, and the results are validated experimentally.

As World Health Organization (WHO) recommends to prevent infection spread includes regular hand washing, wearing a mask in public places, covering mouth and nose when coughing and sneezing, avoid close contact with anyone showing symptoms of respiratory illness. According to a study, people touch their faces more than 20 times an hour on average, which involves contact with the eyes, nose, or mouth. In India people often wear the same mask repeatedly without disinfecting them and a majority of the population do not wear a mask or follow social distancing protocols, which leads to further spread of the virus. This paper discusses a cost effective and smart solution for citizen in the form of a smart kit which contains multiple Internet of Things (IoT) devices with shared connectivity, each addressing a particular problem, which makes following the pandemic protocols easier and effective for the average citizen and the frontline workers.