Jellyfish Search Algorithm for MPPT in Photovoltaic Systems Under Partial Shading Conditions - Karthikeyan, M.; Manimegalai, D. (Fluctuation and noise letters, 2023)
In photovoltaic systems, maximum power point tracking (MPPT) methods are used to get the maximum power out of them. The presence of several peaks in a PV array’s power-voltage characteristics is due to partial shadowing conditions that increase the complexity of the tracking operation. In this paper, the Global Maximum Power Point (GMPP) is calculated using latest meta-heuristic optimization algorithm known as Jellyfish Search (JS). This unique MPPT approach is used to reduce PV module tracking time and improve the tracking efficiency. Using MATLAB/SIMULINK, the effectiveness of the suggested JS algorithm is assessed by contrasting it with the traditional P&O approach in terms of tracking speed and precision. The simulation findings indicate that the JS algorithm’s tracking ability is better than that of the conventional P&O method. In the experimental results, the JS algorithm reduces convergence time by 56.6% when compared to the PSO algorithm. Also, the proposed JS algorithm generates output power higher than the PSO MPPT algorithm using the duty cycle ratio value at the expected peaks.