Optimized MPPT model for different environmental conditions to improve efficacy of a photovoltaic system

• Published in: Soft computing (Berlin, Germany) Vol. 28; no. 3; pp. 2161 - 2179
• Main Authors: Hai, Tao, Aksoy, Muammer, Nishihara, Kentaro
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2024; Springer Nature B.V
• Subjects: Algorithms; Alternative energy sources; Artificial Intelligence; Clean energy; Computational Intelligence; Control; Energy resources; Energy storage; Engineering; Fuzzy control; Fuzzy logic; Irradiance; Mathematical Logic and Foundations; Maximum power tracking; Mechatronics; Neural networks; Optimization; Photovoltaic cells; Return on investment; Robotics; Search algorithms; Solar arrays; Solar collectors; Solar energy; System effectiveness; FLC system; MPPT; Modified sparrow search; PV; Battery
• ISSN: 1432-7643; 1433-7479
• DOI: 10.1007/s00500-023-09195-5

Photovoltaic (PV) technology exhibits significant potential as a form of energy due to its green characteristics. Nevertheless, the modeling of PV modules is subject to unpredictability due to the fluctuating levels of heat and irradiance. To optimize efficiency and reduce the return on investment of a PV system, it is necessary to keep the PV panels at the highest possible power point (MPP). The application of fuzzy logic control-based intelligent maximum power point tracking (MPPT) approach is found to be more appropriate than traditional techniques in PV systems for addressing the issue of unpredictability. The study presents an investigation of an isolated PV system that utilizes a push–pull converter in conjunction with a fuzzy logic-based MPPT technique. To address the previously mentioned issues, this research proposes the utilization of a fuzzy logic controller (FLC) that is centered on a modified sparrow search algorithm (MSSA) as a means to enhance the performance of the current MPPT controllers. The findings demonstrated the efficacy of the recommended approach in precisely following the global maximum power point (GMPP) with improved convergence rates and reduced power fluctuations when compared to alternative methods. The PV system, which incorporates the MSSA-MPPT algorithm, has been developed with MATLAB/SIMULINK program. The mathematical evaluation of the proposed approach, which increases the tracking effectiveness of PV systems to 99.7%, is well validated by the system findings. In instances where the solar array fails to generate sufficient energy to satisfy the required demand, the Battery Energy Storage (BES) system is activated to ensure continuous power within the test system.