﻿ 复杂遮蔽条件下光伏多峰出力特征及GMPPT控制<sup>*</sup>
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Photovoltaic multi-peak output characteristics and GMPPT control under complex shaded condition
CHEN Mingxuan, WU Jianwen, MA Suliang, HUANG Lian
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
Received: 2016-06-03; Accepted: 2016-09-21; Published online: 2016-11-02 12:04
Foundation item: National Natural Science Foundation of China (51377007); Specialized Research Fund for the Doctoral Program of Higher Education of China (20131102130006)
Corresponding author. WU Jianwen, E-mail:wujianwen@vip.sina.com
Abstract: Aimed at solving the failure problem of the maximum power point tracking (MPPT) algorithm caused by partially shaded condition in the photovoltaic power generation system, a global maximum power point tracking (GMPPT) algorithm based on δ-potential well is proposed. Based on the photovoltaic multi-peak output characteristics when the illumination intensity is changing, the reason of searching blind spot in conventional MPPT algorithm is analyzed in terms of maximum power point transition, and the necessity of GMPPT optimization is explained. A quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to improve the particle diversity and increase the search speed and convergence accuracy. The algorithm was verified by MATLAB/SIMSCAPE and compared with the standard particle swarm optimization (PSO) algorithm. The results show that the proposed algorithm can track the global maximum power point effectively with fast searching speed, reducing the dependency on parameters and avoiding premature convergence of the algorithm.
Key words: photovoltaic power generation     photovoltaic array     partially shaded     global maximum power point tracking (GMPPT)     quantum-behaved particle swarm optimization (QPSO) algorithm

1 局部阴影条件下的光伏阵列模型与GMPPT实现电路 1.1 局部阴影条件下的光伏阵列模型

 图 1 光伏阵列结构 Fig. 1 Structure of photovoltaic array

 (1)

1.2 光伏阵列GMPPT的电路实现

Boost电路的原理图如图 2所示。Boost电路由开关管Q1、电感L，电容C组成。Boost电路的作用是将电压UPV升压到UcUPV为光伏阵列的输出电压，Uc为Boost电路的输出电压。

 图 2 Boost电路原理 Fig. 2 Principle of Boost circuit

 (2)

 (3)

2 局部阴影条件下的GMPPT算法实现 2.1 局部阴影条件下常规方法失效分析

 图 3 不同光照条件下，光伏输出U-I和U-P曲线 Fig. 3 Photovoltaic output U-I and U-P curves under different illumination conditions

 光照模式 光照强度/(W·m-2) 标准光照 遮蔽1 遮蔽2 G11 1 000 1 000 1 000 G12 1 000 1 000 1 000 G21 1 000 500 800 G22 1 000 300 500 G31 1 000 200 200 G32 1 000 200 200

1) 当光照条件由标准光照条件变为遮蔽2时，对应功率点将从A变换到E，此时若采用传统优化算法，如观察扰动法、爬山法等，可以寻优找到此光照条件下的最大功率点C

2) 当光照条件由标准光照条件变为遮蔽1时，对应的功率点将从A变化到F，若此时采用传统的寻优算法，难以跟踪到最大功率点B

2.2 基于δ势阱的量子粒子群算法

 (4)

 图 4 基于δ势阱的QPSO算法流程图 Fig. 4 Flowchart of QPSO algorithm based on δ-potential well

Step 1  令迭代次数g=0，初始化参数及粒子群中每一个粒子所代表的当前占空比Di(0)，并记录粒子的最优位置Pi(0)= Di(0) 和全局最优占空比Gi(0)。

Step 2  根据式(5) 计算粒子群中平均最优占空比为

 (5)

Step 3  根据式(6)，更新每一个粒子所代表的占空比Di(g)。

 (6)

Step 4  计算更新后的粒子适应度(即光伏电池输出功率值)，利用式(5) 更新每一个粒子自身历史最优占空比Pi(g)以及当前全局最优占空比G(g)。

 (7)

Step 5  分析搜索结果是否满足截止条件，若满足转入Step 6，否则令g=g+1再转入Step 2(本文设置最大迭代次数为截止条件)。

Step 6  输出最优占空比G, 终止寻优过程。

3 算例分析

 参数 数值 Uoc/V 37.67 Isc/A 8.81 Pm/W 254.9 Um/V 31.8 Im/A 8.18

3.1 仿真工况及参数说明

Boost电路参数及算法参数如表 3所示。

 参数 数值 负载电阻R/Ω 200 粒子数N 5 迭代次数Gmax 20 收缩-扩张系数β 1.2 自变量范围[Dmin, Dmax] [0, 1]

3.2 算例结果及分析

 图 5 标准PSO和QPSO算法在遮蔽1下的搜索轨迹对比 Fig. 5 Comparison of search trajectories between standard PSO and QPSO algorithms under shaded 1
 图 6 QPSO和标准PSO算法在遮蔽1下的搜索结果对比 Fig. 6 Comparison of search results between QPSO and standard PSO algorithms under shaded 1
 图 7 QPSO和标准PSO算法在遮蔽1下的全局最优值曲线对比 Fig. 7 Comparison of global optimum curves between QPSO and standard PSO algorithms under shaded 1

 算法 σ/% 标准光照 遮蔽1 遮蔽2 QPSO 100 95 100 标准PSO 100 80 90

 图 8 QPSO和标准PSO算法GMPPT效果图 Fig. 8 Effect pictures of GMPPT by QPSO and standard PSO algorithms

4 结论

1) 光伏局部阴影条件下的GMPPT问题，是典型的多峰值寻优问题。需采用全局搜索能力强的优化算法，如群智能优化算法。

2) 引入量子行为的改进粒子群算法，可以很好地解决上述多峰问题，寻优准确程性、快速性以及多样性均优于标准粒子群算法，适用于解决局部阴影下的GMPPT问题。

3) 本文提出的QPSO算法，参数少，搜索快，全局搜索能力强，防早熟效果明显，适用于GMPPT实现。

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#### 文章信息

CHEN Mingxuan, WU Jianwen, MA Suliang, HUANG Lian

Photovoltaic multi-peak output characteristics and GMPPT control under complex shaded condition

Journal of Beijing University of Aeronautics and Astronsutics, 2017, 43(6): 1141-1148
http://dx.doi.org/10.13700/j.bh.1001-5965.2016.0478