基于LTSO-VP&O算法的光伏系统MPPT控制

MPPT control of photovoltaic system based on LTSO-VP&O algorithm

针对局部遮阴条件下光伏阵列功率多峰值造成的传统最大功率点跟踪算法易陷入局部最优等问题,提出一种基于莱维改进金枪鱼算法与变步长扰动观测法的混合优化算法。引入莱维飞行改进金枪鱼群优化算法的实时位置更新律,减小陷入局部最优的可能性;设计随功率特性斜率变化而变化的步长更新律对常规扰动观测法进行改进,提高最大功率跟踪速度;融合莱维改进金枪鱼算法与变步长扰动观测法构建混合优化算法,进一步提高跟踪精度与速度,并抑制扰动信号影响。仿真实验结果表明,本文所提出的算法在均匀全光照、静态局部遮阴、动态局部遮阴3种光照条件下的寻优时间和跟踪误差分别为0.036 s和0%、0.04 s和1.06%、0.05 s和1.06%,均优于其他对比算法,并且更加精准且快速的实现光伏系统的最大功率跟踪。

A hybrid optimization algorithm based on Levy-flight improved tuna swarm optimization and variable step size perturbation observation method is proposed to solve the problem that the traditional maximum power point tracking algorithm is prone to local optimality due to the multi-peak power of photovoltaic arrays under local shade conditions.The real-time position update law of Levy-flight improved tuna swarm optimization algorithm is introduced to reduce the possibility of falling into local optimal.A new step change law which changes with the slope of power characteristic is designed to improve the conventional perturbation observation method and increase the maximum power tracking speed.Combining Levy-flight improved tuna swarm optimization and variable step size perturbation observation method,a hybrid optimization algorithm is constructed to further improve tracking accuracy and speed,and suppress the influence of disturbance signals.Simulation results show that the optimization time and tracking error of the proposed algorithm are 0.036 s and 0%,0.04 s and 1.06%,and 0.05 s and 1.06%,respectively,under the three lighting conditions of uniform full illumination,static local shading and dynamic local shading,which are superior to other comparison algorithms.And more accurate and fast to achieve the maximum power tracking of photovoltaic systems.