摘要
当光伏阵列被建筑物、云层等遮挡时,光伏阵列的P-V输出特性曲线由单个峰值变为多个峰值,传统算法极易陷入局部的峰值点。采用智能优化算法进行光伏最大功率点跟踪,虽然相比传统算法具有更好的全局搜索能力,但在最大功率点跟踪时仍然存在收敛速度慢、收敛的精度不够和振荡过程较大等问题。为了解决上述问题,提出了一种基于改进的蝗虫优化算法(Grasshopper Optimisation Algo‐rithm,GOA)和扰动观察法相结合的复合控制方法,利用改进的GOA算法进行全局搜索,当算法搜索到全局最优解附近时,切换为扰动观察法精准地跟踪到全局最优解,从而实现最大功率点跟踪。在MATLAB/Simulink中搭建光伏MPPT模型,验证了该方法在MPPT控制中的优越性。
When the photovoltaic array is obscured by buildings,clouds,etc.,the P-V output characteristic curve of the photovoltaic array changes from a single peak to multiple peaks,and the traditional algorithm is very easy to fall into the local peak point.The intelligent optimization algorithm is used to track the maximum power point of the photovoltaic,although it has better global search ability compared to the traditional algorithm,there are still problems such as slow convergence speed,insufficient accuracy of convergence and large oscillation process when tracking the maximum power point.In order to solve the above problems,this paper proposes a composite control method based on the combination of the improved Grasshopper Optimisation Algorithm(GOA)and the perturbation observation method,first use the improved GOA algorithm for global search,then switch to the perturbation observation method to accurately track to the global optimal solution when finding the global optimal solution,so as to achieve maximum power point tracking.The photovoltaic MPPT model was built in MATLAB/Simulink,verifing the superiority of the method in MPPT control.
作者
彭俊伟
陈众
PENG Junwei;CHEN Zhong(Key Laboratory of Smart Grid Operation and Control,Changsha University of Science and Technology,Changsha 410000,China)
出处
《电工材料》
2025年第1期98-104,共7页
Electrical Engineering Materials
关键词
光伏阵列
最大功率点跟踪
蝗虫优化算法
photovoltaic array
maximum power point tracking
grasshopper optimisation algorithm
