[1]沈 磊,徐岸非,黄晴宇,等. 基于GWO-P&O算法的局部阴影光伏MPPT研究[J].湖北工业大学学报,2022,(2):25-29+43.
　SHEN Lei,XU Anfei,HUANG Qingyu,et al. Research on MPPT of Photovoltaic Under Partial Shading Condition Based on GWO-P&O Algorithm[J].,2022,(2):25-29+43.
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 基于GWO-P&O算法的局部阴影光伏MPPT研究()
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《湖北工业大学学报》[ISSN:1003-4684/CN:42-1752/Z]

卷:
期数:
2022年第2期
页码:
25-29+43
栏目:
湖北工业大学学报
出版日期:
2022-04-29

文章信息/Info

Title:
 Research on MPPT of Photovoltaic Under Partial Shading Condition Based on GWO-P&O Algorithm
文章编号:
1003-4684(2022)02-0025-05
作者:
 沈 磊;  徐岸非;  黄晴宇;  余嘉川
 湖北工业大学太阳能高效利用及储能运行控制湖北省重点实验室，湖北 武汉 430068
Author(s):
 SHEN Lei; XU Anfei; HUANG Qingyu; YU Jiachuan
 Hubei Key Laboratory for High Efficiency Utilization of Solar Energy and OperationControl of Energy Storage System, Hubei Univ. of Tech., Wuhan, 430068, China
关键词:
 ; 最大功率点跟踪;  局部阴影;  灰狼算法;  扰动观察法
Keywords:
 ; maximum power point tracking;  partial shading condition;  grey wolf optimization;  perturbation &;  observe
分类号:
TM914
文献标志码:
A
摘要:
 针对局部阴影条件下光伏阵列最大功率点跟踪，提出了一种灰狼算法与扰动观察法相结合的复合控制算法—GWO-P&O算法。首先利用灰狼算法的全局搜索能力定位最大功率点的范围，然后采用小步长的扰动观察法进行局部搜索，找到精确的最大功率点。采用MATLAB/Simulink构建了完整的系统仿真模型，仿真结果表明，扰动观察法在局部阴影条件下陷入了局部最优解，没有追踪到最大功率点。与灰狼算法相比，该复合算法在局部阴影条件下，追踪效率达100%，提高了1.11%，其收敛时间由0.8 s缩短至0.52 s, 收敛时间提高了35%，因此，该算法兼顾了最大功率点追踪的速度和精度。系统仿真验证了该算法的正确性和有效性。
Abstract:
 In practical photovoltaic system engineering, due to the influence of changes in light intensity, the output power voltage curve of photovoltaic array often presents multi-peak phenomenon. The traditional maximum power point tracking (MPPT) algorithm is easy to be trapped in the local optimal solution and cannot accurately track the maximum value. Aiming at the maximum power point tracking of photovoltaic array under partial shading condition (PSC), a composite control algorithm GWO P&O algorithm combining grey wolf optimization (GWO) and perturbation & observe (P & O) is proposed. Firstly, the global search ability of Gray Wolf algorithm is used to locate the range of maximum power point, and then the small step disturbance observation method is used to find the accurate maximum power point. A complete system simulation model is constructed by Matlab / Simulink. The simulation results show that the disturbance observation method falls into the local optimal solution under partial shading conditions and does not track the maximum power point. Compared with the grey wolf algorithm, the tracking efficiency of the composite algorithm reaches 100 % under local shadow conditions, which increases by 1.11%. The convergence time is shortened from 0.8s to 0.5s, and the convergence time is increased by 35 %. Therefore, the algorithm takes into account the speed and accuracy of the maximum power point tracking. System simulation verifies the correctness and effectiveness of the algorithm.

参考文献/References:

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备注/Memo

备注/Memo:
［收稿日期］ 2021-09-23
［基金项目］ 湖北省技术创新专项重大项目（2019AAA018）
［第一作者］ 沈 磊（1996-），男，河南漯河人，湖北工业大学硕士研究生，研究方向为电力电子装置及电能质量优化
［通信作者］ 徐岸非（1981-），男，湖北崇阳人，湖北工业大学副教授，研究方向为电力电子装置及电能质量优化
更新日期/Last Update: 2022-04-28