基于FCS算法的光伏阵列最大功率追踪

Maximum Power Point Tracking of Photovoltaic Array Based on FCS Algorithm

局部阴影情况下,光伏阵列输出功率具有多峰值特性,针对最大功率点跟踪(Maximum power point tracking,MPPT)算法在实际应用中存在着收敛速度较慢,效率较低,且容易陷入局部功率极值的问题,将兼顾收敛速度、精度、功率稳定性的快速布谷鸟搜索(Fast cuckoo search,FCS)算法应用于光伏阵列最大功率追踪。FCS算法采用自适应步长和机会因子可避免过早收敛,全局搜索和跳出局部搜索能力强,收敛速度快,算法后期局部开发能力强,功率振荡小,功率输出稳定,最大功率追踪精度高。仿真表明,在静态阴影、动态阴影条件下,FCS算法较灰狼算法(Grey wolf optimizer,GWO)、粒子群算法(Particle swarm optimization,PSO)具有更快地收敛速度和更高的收敛精度,且稳定性好,有效地提升光伏阵列的输出效率。

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.