Abstract: In the case of partial shading, the output power of photovoltaic arrays has multi-peak characteristics. In practical applications, the maximum power point tracking algorithm has slow convergence speed, low efficiency, and is easy to fall into local power extremes. For the problem, the Fast cuckoo search (FCS) algorithm, which takes into account the convergence speed, accuracy and power stability, is applied to the maximum power tracking of photovoltaic arrays. The FCS algorithm adopts adaptive step size and chance factor to avoid premature convergence. It has strong global search and jump out of local search capabilities, fast convergence speed, strong local development ability in the later stage of the algorithm, small power oscillation, stable power output, and high maximum power tracking accuracy. The simulation shows that under static shadow and dynamic shadow conditions, the FCS algorithm has faster convergence speed and higher convergence accuracy than the GWO algorithm and the PSO algorithm, and has good stability, which can effectively improve the output efficiency of the photovoltaic array.

Key words: photovoltaic array, FCS algorithm, local shadow, maximum power tracking