Abstract

In photovoltaic power generation, where output uncertainty is high, traditional methods tend to fall into local maximum power points and miss global maximum power points(GMPP) when identifying the maximum power point(LMPP), resulting in poor tracking results. Therefore, we proposed a strategy to realize MPPT tracking based on a gray wolf optimization algorithm, enhancing MPPT global development and local search ability. Then, through the experiment under the condition of uniform illumination, the advantages and disadvantages of different algorithms in MPPT are compared. The results reveal that our proposed algorithm can quickly and stably find the global maximum power point.

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