基于细菌觅食算法的光伏阵列 MPPT 控制方法
摘 要:针对光照不均匀条件下光伏阵列 P-V 输出特征呈现多波峰,传统算法无法摆脱局部最优值的缺点,该文提出了一种
基于细菌觅食的优化算法,并首次应用于光伏阵列的最大功率点跟踪(MPPT)。算法引入了趋向性操作,用以进行局部范围内的
最
优寻找;引入了复制操作,用以避免种群更新盲目随机性,加快了算法的收敛速度;引入了迁徙操作用以避免算法陷入局部最优解
。
分析了光伏阵列在遮挡条件下输出功率的变化特性,然后使用细菌觅食算法进行了最大功率点跟踪控制方法实验。实验表明,该算
法能够成功摆脱局部最优值的约束,快速寻找到全局最大功率点,控制精度高,为光伏阵列最大功率点跟踪提供了一种新的实现方
法。
关 键 词:光伏阵列;最大功率点跟踪;细菌觅食算法;部分遮挡
Abstract:In view of presenting multiple peak points of the P-V output characteristic carve of photovoltaic array when it is partially shaded
which makes traditional MPPT algorithms work improperly, a novel MPPT algorithm based on bacteria foraging optimization (BFO) is
proposed and applied in MPPT for the first time. Thealgorithm introduces the Chemotaxis operation for optimum seeking within the scope of
local, the reproduction operation to avoid population blind randomness and to speed up the convergence speed of the algorithm, the
elimination and dispersal operation to avoid algorithm trapped in local optimal solution. Based on the analysis of the output characteristic of
photovoltaic array under partial shaded, the BFOA is used in the MPPT. The simulation results show that the proposed algorithm succeeds in
tracking the global maximum power point quickly in 15 steps. It proves that BFOA is an effective method for MPPT getting rid of the local
optimums and with good searching precession,it provides a new way to solve the MPPT problem.
Key words: Photovoltaic Array; Maximum Power Point Tracking(MPPT); Bacteria Foraging Optimization Algorithm(BFOA); Partially
Shaded
1 引 言
目前太阳能以其清洁性和可再生性等特点而得
到广泛应用
[1]
。在局部遮挡情况下,会造成光伏阵
列的功率损失高达 70%
[2]
。由于遮挡的原因,整个
找到真正的全局最大功率点,造成这些算法失效
[3]
。
针对该问题已经提出了使用启发式算法来解决该问
题,比如粒子群算法
[4]
、遗传算法
[5 ]
和免疫算法
[6]
光伏阵列上的光照不均匀,会导致 P-V 曲线呈现出 等。
多个波峰,常规的最大功率点跟踪(maximum Power
Point Tracking, MPPT)算法会陷入局部峰值,无法
Passino 于 2002 年提出了模拟人类大肠杆菌觅
食行为的细菌觅食优化算法(Bacteria Foraging