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A comparison of different global MPPT techniques based on meta-heuristic algorithms for photovoltaic system subjected to partial shading conditions

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS
卷 74, 期 -, 页码 377-386

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2017.02.051

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Particle swarm optimization; Cuckoo Search; Global MPPT; Partial shading

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The characteristics of photovoltaic array under partial shading comprises multiple local MPPs and one global. The classical maximum power point tracking (MPPT) algorithms can't reach to global MPP. Accordingly, this work aims to study the behavior performance of two optimization techniques. They have been developed for extracting the global MPP from the partially shaded PVPS. The two studied techniques include Particle Swarm Optimization (PSO) and Cuckoo Search (CS). A comprehensive assessment of the two techniques has been carried out against a conventional algorithm of INR-based tracker. The tracking performances of PSO and CS based trackers are evaluated for different partial shading patterns based on MATLAB software. Results confirm that PSO and CS based trackers guarantee the convergence to the global MPP. Furthermore, they have the best performance in comparison with the conventional one. Additionally; the obtained results show that the CS-based tracker has superiority compared with PSO. The tracking time in case of CS-tracker is reduced compared to PSO in all the studied cases.

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