基于改进花授粉算法的光伏MPPT研究

Photovoltaic MPPT research based on improved flower pollination algorithm

局部遮阴情况下,光伏阵列的P-V曲线存在多个极值,传统最大功率跟踪方法容易陷入局部最优而追踪失败。针对多峰值P-V曲线,提出一种改进型花授粉算法来实现全局最大功率跟踪。该算法在标准花授粉算法的基础上引入了自适应转化概率来平衡全局和局部搜索,同时用Jaya算法的位置更新公式替代原算法的局部搜索公式,有效避免了原局部搜索策略易陷入局部最优的不足。通过MATLAB/Simulink进行仿真验证,并与粒子群算法、花授粉算法进行比较,结果表明改进花授粉算法具有更高的追踪精度和更快的追踪速度。

In the case of partial shading,the P-V curve of the photovoltaic array has multiple extreme values,and the traditional maximum power tracking methods are easy to fall into the local optimum and the tracking fails.Aiming at the multi-peak P-V curve,an improved flower pollination algorithm was proposed to achieve global maximum power tracking.Based on the standard flower pollination algorithm,the adaptive transformation probability was introduced to balance the global and local search,and the local search formula of the original algorithm was replaced with the position update formula of the Jaya algorithm,effectively avoiding the disadvantage that the original local search strategy is easy to fall into the local optimum.The simulation verification was carried out through MATLAB/Simulink,and the algorithm was compared with the flower pollination algorithm and particle swarm optimization.The results show that the improved flower pollination algorithmhas higher tracking accuracy and faster tracking speed.