为解决光伏电池双二极管五参数模型中参数辨识准确度低的问题, 提出了一种人工蜂群算法.该方法采用曲线拟合来求取参数, 用求出的电流计算值来比较标准化的均方根误差百分比.采用变量替换法, 使双二极管模型方程中指数因子只含一个变量, 通过编程求解电流的计算值.运用蜂群算法和牛顿-拉夫逊法求得标准化的均方根误差百分比为0.011 7%和6.35%.实验及分析表明蜂群算法的优化准确度明显优于牛顿-拉夫逊解析法、遗传算法、模式搜索算法和模拟退火算法, 为光伏电池参数辨识提供了一种新的思路.

In order to solve the low accuracy of the parameter identification of photovoltaic cell five-parameter double-diode model, a artificial bee swarm algorithm was proposed.The method is to use the idear of the cure fitting to calculate parameters.In order to make a comparison of the normalized root mean square error percentage,the calculation of current value must be identified.In order to make double-diode model equation contain only one variable in index factors,the method of variable substitution is adopted.Through the programming,the calculation of current values can be identified.The normalized root mean square error percentages of artificial bee swarm and New-Raphson method are 0.011 7% and 6.35%.The experiment and analysis show that the accuracy of artificial bee swarm algorithm is better than New-Raphson method,genetic algorithm,pattern search algorithm and simulated annealing algorithm to solve the accuracy of parameters,which can be considered as a new method to provide for parameter identification of photovoltaic cell.