Maximizing solar power generation through conventional and digital MPPT techniques: a comparative analysis

Abstract

A substantial level of significance has been placed on renewable energy systems, especially photovoltaic (PV) systems, given the urgent global apprehensions regarding climate change and the need to cut carbon emissions. One of the main concerns in the field of PV is the ability to track power effectively over a range of factors. In the context of solar power extraction, this research paper performs a thorough comparative examination of ten controllers, including both conventional maximum power point tracking (MPPT) controllers and artificial intelligence (AI) controllers. Various factors, such as voltage, current, power, weather dependence, cost, complexity, response time, periodic tuning, stability, partial shading, and accuracy, are all intended to be evaluated by the study. It is aimed to provide insight into how well each controller performs in various circumstances by carefully examining these broad parameters. The main goal is to identify and recommend the best controller based on their performance. It is notified that, conventional techniques like INC, P&O, INC-PSO, P&O-PSO, achieved accuracies of 94.3, 97.6, 98.4, 99.6 respectively while AI based techniques Fuzzy-PSO, ANN, ANFIS, ANN-PSO, PSO, and FLC achieved accuracies of 98.6, 98, 98.6, 98.8, 98.2, 98 respectively. The results of this study add significantly to our knowledge of the applicability and effectiveness of both AI and traditional MPPT controllers, which will help the solar industry make well-informed choices when implementing solar energy systems.

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“…On the other hand, articles on sustainability [71][72][73][74][75][76][77][78][79][80] explore a wide range of topics, from maximizing solar energy generation to managing waste associated with respiratory treatment. These studies demonstrate the growing interest in sustainable solutions and innovations in various areas, including renewable energy, air quality, and sustainable agricultural practices.…”

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“…The algorithm uses the approach of continually changing the reference value which leads to an MPPT optimal point [15][16][17][18].…”

“…MPPT is a process that continuously studies the point where a solar panel works to generate the maximum electrical power at which their panels operate around their maximum power point. This magnifies output, maximizes energy capture, and decreases system price [17]. ANNs, which is a technique of machine learning, can provide the MPPT system accurate modeling of the link between the environmental factors and the PV panels output.…”