为提升太阳电池模型参数辨识的准确率,该文提出基于Jaya算法与蜻蜓算法相融合的辨识方法,运用Jaya算法进行初步全局搜索,并结合蜻蜓算法进行局部搜索最优解,使算法收敛精度得到有效提升。研究结果表明：运用Jaya-DA算法求得太阳电池模型的电流均方根误差为9.861×10-4,相较于单一使用Jaya算法、蜻蜓算法、人工蜂群算法、粒子群算法,该方法所得结果均方根误差更小,可更准确地确定太阳电池模型参数。
Abstract
In order to improve the accuracy of solar cell model parameter identification, this paper proposed an identification method based on the combination of Jaya algorithm and dragonfly algorithm in which using Jaya algorithm to carry out preliminary global search and combining with dragonfly algorithm to carry out local search for the optimal solution, to improve the convergence accuracy of the algorithm. The results show that the root mean square error of the solar cell model obtained by Jaya-Da algorithm is 9.861 × 10-4. Compared with Jaya algorithm, dragonfly algorithm, artificial bee colony algorithm and particle swarm algorithm, the root mean square error of this method is smaller and it can be used to identify the solar cell model parameters more accurately.
关键词
太阳电池 /
模型 /
参数辨识 /
Jaya算法 /
蜻蜓算法
Key words
solar cells /
model /
parameter identification /
Jaya algorithm /
dragonfly algorithm
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基金
国家自然科学基金（62002016; 71801031）; 北京市自然科学基金（9204028）; 北京市优秀人才培养资助专项（BJSQ2020008）
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