Optimizing Solar Power Extraction in Water Pumping: A Comparison of Fuzzy Logic and INC MPPT Control

Renewable energy sources specifically, conventional solar panels fitted in commercial spaces exhibit very low efficiency compared to fossil fuels and cannot independently provide entire electricity needs of the commercial space or housings. It becomes important to provide independent Solar cell support for the pump at the same time providing high efficiency. This paper presents a comparative analysis of water pumping system powered by solar cells, controlled by a fuzzy network and a direct incremental decremental (INC) algorithm. The solar water pumping design addresses the urgent need for renewable energy solutions in commercial and industrial spaces. Traditional energy sources are rapidly depleting, creating an impending crisis. Transportation and industries consume vast amounts of energy, further compounding the issue. Fortunately, the world is transitioning towards renewable alternatives like solar power. This proposed system leverages solar cells for efficient solar energy conversion. A fuzzy network controls the system, optimizing performance and maximizing power extraction at the same time an MPPT Algorithm without a fuzzy network, optimizing performance and maximizing power extraction. An intermediate Zeta converter ensures optimal power extraction from the solar array. This approach is validated through simulations using MATLAB/Simulink software, showcasing the system's effectiveness. Effortlessly efficient and reliable, the BLDC motor excels with low maintenance, thanks to its superior cooling, strong torque, and minimal radio noise. By integrating cutting-edge technologies like solar cells, fuzzy network control, Standard INC MPPT Control, and Zeta converters, this water pumping system offers a promising solution for sustainable water management and a step towards a greener future.