Jellyfish Search Algorithm for MPPT in Photovoltaic Systems Under Partial Shading Conditions

• Published in: Fluctuation and noise letters Vol. 22; no. 2
• Main Authors: Karthikeyan, M., Manimegalai, D.
• Format: Journal Article
• Language: English
• Published: Singapore World Scientific Publishing Company 01.04.2023; World Scientific Publishing Co. Pte., Ltd
• Subjects: Algorithms; Cycle ratio; Heuristic methods; Maximum power tracking; Optimization; Photovoltaic cells; Search algorithms; Photovoltaic systems; global peak; jellyfish search algorithm; partial shading conditions; tracking time; tracking efficiency
• ISSN: 0219-4775; 1793-6780
• DOI: 10.1142/S021947752350013X

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.