Summary of the novel MPPT (maximum power point tracking) algorithm based on few intelligent algorithms specialized on tracking the GMPP (global maximum power point) for photovoltaic systems under partially shaded conditions

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Abstract
Energy efficient conversion is always a hot topic in the field of photovoltaic power generation. Contract to traditional algorithm, the lasted research showed intelligent algorithms have remarkable advantages in multiple-peak output power characteristics affected by partial shading. This article presents some popular intelligent algorithms such as particle swarm optimization(PSO), genetic algorithm(GA), ant colony optimization (ACO), etc. When PV systems are affected by partial shading, these GMPPT (global maximum power point tracking) algorithm is required to increase the energy harvesting capability of the system. By analyze and discuss the search efficiency and convergence property of several intelligent optimization methods mentioned above, multiple problem still exist and the GMPP can not usually be tracked exactly and quickly. Thus, this article point out it is great significance that several hybrid intelligent algorithms are put forward to compensate the deficiency of single algorithms, and modified the optimization is also required.

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