A comprehensive comparison of advanced metaheuristic photovoltaic maximum power tracking algorithms during dynamic and static environmental conditions.

This study introduces a novel technique for achieving the global peak (GP) in solar photovoltaic (PV) systems under partial shadowing conditions (PSC) using the Dandelion Optimizer Algorithm (DOA), inspired by the dispersal of dandelion seeds in the wind. The proposed approach aims to enhance the power generation efficiency of PV systems across various scenarios, including dynamic uniform, dynamic PSCs, static uniform irradiances, and static PSCs. The proposed approach improves tracking efficiency, provides non-oscillatory steady-state responses, and reduces transients as well as enhancing the dynamic performance of the whole system.

Predicting carbon dioxide emissions in the United States of America using machine learning algorithms.

Carbon dioxide (CO) emissions result from human activities like burning fossil fuels. CO is a greenhouse gas, contributing to global warming and climate change. Efforts to reduce CO emissions include transitioning to renewable energy.

Maximum power extraction and DC-Bus voltage regulation in grid-connected PV/BES system using modified incremental inductance with a novel inverter control.

Low ripples and variations in the DC-Bus voltage in single-phase Photovoltaic/Battery Energy Storage (PV/BES) grid-connected systems may cause significant harmonics distortion, instability, and reduction in power factor. The use of short-life electrolytic capacitor on the DC-Bus is considered a standard way for reducing these ripples and variations because of its large capacitance but results in short lifetime of the inverter. Replacing large electrolytic capacitors with small film capacitors can extend the lifetime of a PV/BES grid-connected system because small film capacitors have longer lifetime than large electrolytic capacitors.