The Maximum Power Point Tracking (MPPT) control system is a method that can bring a photovoltaic (PV) system closer to its maximum achievable efficiency. Given the various algorithms and classifications available, comparing methods in a specific situation can help select the appropriate algorithm. This paper first provides a comprehensive categorization of MPPT methods and then tracks the maximum power point using three algorithms: P&O, IC, and Fuzzy-PI, in the presence of Boost and SEPIC converters. The P&O, IC, and Fuzzy-PI algorithms are executed once with the Boost converter and once with the SEPIC converter. In both cases, the accuracy and speed of tracking the algorithms and the impact of the converters on output power are examined. By comparing oscillations around the desired point and the settling time in each scenario, the use of a PI algorithm, with coefficients calculated by the Fuzzy method and applied to the SEPIC converter, demonstrates better performance than others. Analysis and simulation of the system were conducted using the Simulink unit in MATLAB software.
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Azadian,A. (2020). Comparison of Maximum Power Point Tracking Algorithms in the Presence of Boost and SEPIC Converters. Transactions on Machine Intelligence, 3(3), 165-175. doi: 10.47176/TMI.2020.165
MLA
Azadian,A. . "Comparison of Maximum Power Point Tracking Algorithms in the Presence of Boost and SEPIC Converters", Transactions on Machine Intelligence, 3, 3, 2020, 165-175. doi: 10.47176/TMI.2020.165
HARVARD
Azadian A. (2020). 'Comparison of Maximum Power Point Tracking Algorithms in the Presence of Boost and SEPIC Converters', Transactions on Machine Intelligence, 3(3), pp. 165-175. doi: 10.47176/TMI.2020.165
CHICAGO
A. Azadian, "Comparison of Maximum Power Point Tracking Algorithms in the Presence of Boost and SEPIC Converters," Transactions on Machine Intelligence, 3 3 (2020): 165-175, doi: 10.47176/TMI.2020.165
VANCOUVER
Azadian A. Comparison of Maximum Power Point Tracking Algorithms in the Presence of Boost and SEPIC Converters. Trans. Mach. Intell., 2020; 3(3): 165-175. doi: 10.47176/TMI.2020.165
