Photovoltaic Global Maximum Power Tracking Based on Improved Dragonfly Algorithm

doi:10.11930/j.issn.1004-9649.202010137

Abstract

Abstract: A multi-peak phenomenon can be observed on the power-voltage (P-U) characteristic curve of a photovoltaic (PV) array under partially shaded conditions (PSCs). In this case, conventional maximum power point tracking (MPPT) algorithms tend to fall into local extremums, and swarm intelligence algorithms would spend much time in tracking. Thus, this paper proposes an improved MPPT algorithm based on the dragonfly algorithm (DA) and the perturbation and observation (P & O) algorithm. The convergence rate and global search ability of the algorithm are improved by optimizing particle roles and introducing the Lévy flight model. With the P & O algorithm, the concept of population density is put forward and an optimal local search strategy is formulated to modify the population search efficiency and precision. Finally, comparisons with the P & O algorithm, particle swarm optimization (PSO) algorithm, and the original DA through simulation verify the validity of the proposed algorithm.

Key words: photovoltaic system, maximum power point tracking, multi-peak characteristic, dragonfly algorithm, perturbation and observation algorithm

XUE Fei, MA Xin, TIAN Bei, WU Hui. Photovoltaic Global Maximum Power Tracking Based on Improved Dragonfly Algorithm[J]. Electric Power, 2022, 55(2): 131-137.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202010137

https://www.electricpower.com.cn/EN/Y2022/V55/I2/131

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