基于改进蚁群算法的光伏阵列组件选配方法

Photovoltaic Array Module Selection Method Based on Improved Ant Colony Algorithm

太阳能发电采用光伏阵列将太阳能转化为电能,光伏阵列是由若干性能一致或相近的光伏组件串、并联而成。光伏组件间存在天然的不一致性,工作过程中会产生失配损失。失配的大小取决于光伏电池性能参数的离散性,且随着使用时间推移,失配将会不断累积,导致光伏组建性能不断衰减,甚至功能失效。光伏组件和光伏阵列装配工艺控制是消除光伏组件间不一致性的重要手段。结合最大功率选配法和伏安特性曲线选配法,提出一种基于带约束的改进蚁群算法智能选配方法,将光伏组件最大功率作为选配依据,将综合偏差衡量值作为约束条件。利用MATLAB软件进行蚁群寻优过程仿真实验,该方法能够相对准确地装配出性能一致性的光伏组件,且在寻优过程中并没有陷入局部最优困局,能在短时间内寻到较优解,收敛速率较快,且算法鲁棒性较高,寻优过程较稳定。

Solar power generation uses photovoltaic(PV)array to convert solar energy into electric energy.The photovoltaic array is composed of several photovoltaic modules with the same or similar performance in series and parallel.There is natural inconsistency between PV modules,which may cause mismatch loss during operation.The size of the mismatch depends on the dispersion of the performance parameters of the PV cell,and the mismatch will continue to accumulate with the use of time,resulting in the continuous degradation of the performance of the PV cell,and even the function failure.PV module and PV array assembly process control is an important means to eliminate the inconsistency between PV modules.Combining the maximum power selection method and the voltage-ampere characteristic curve selection method,the author proposes an improved ant colony algorithm intelligent selection method based on constraints,taking the maximum power of PV modules as the selection basis and the comprehensive deviation measurement value as the constraint condition.The ant colony optimization process simulation experiment is carried out by using MATLAB software.This method can relatively accurately assemble PV modules with consistent performance,and does not fall into the local optimization dilemma during the optimization process.It can find the optimal solution in a short time,with fast convergence rate,high robustness of the algorithm,and stable optimization process.