The critical worldwide revolution towards clean energy has prompted the improvement of studies on the fabrication of high-performance solar cells. In this regard, rendering an accurate model of the solar cell for performance evaluation in the simulation could be essential. So far, several models have been proposed for the solar cell, including single-diode model (SDM), double-diode model (DDM), and three-diode model (TDM). By increasing the number of diodes considered in the equivalent circuit in order to deliver a more accurate model, the number of unknown parameters which must be identified will be increased as well. Therefore, presenting an efficient algorithm to estimate these parameters becomes an interesting issue in recent years. In this study, an improved optimization algorithm, called springy whale optimization algorithm (SWOA), is proposed to estimate the model parameters of solar cells. SWOA is a generalization of the WOA and has the advantages of high convergence speed, global search capability, and high robustness over it. In order to inquire the efficiency of SWOA, this algorithm is posed to estimate the parameters of models of solar cells and photovoltaic (PV) modules as well; the simulation results authenticate the supremacy of the proposed algorithm. Furthermore, the effectiveness of SWOA algorithm in the practical application has been evaluated using commercial modules, including polycrystalline (SW255), multi-crystalline (KC200GT), and monocrystalline (SM55). This assessment is carried out for various operating conditions under different irradiance and temperature conditions, which yield variations in the parameters of the PV model. The results obtained from various experimental setups confirm the high performance and robustness of the proposed algorithm.

全球范围内向清洁能源的重大革命推动了高性能太阳能电池制造研究的改进。在这方面，为仿真中的性能评估提供一个准确的太阳能电池模型可能是必不可少的。到目前为止，已经提出了几种用于太阳能电池的模型，包括单二极管模型（SDM），双二极管模型（DDM）和三二极管模型（TDM）。通过增加等效电路中考虑的二极管数量以提供更准确的模型，必须识别的未知参数的数量也将增加。因此，近年来提出一种有效的算法来估计这些参数成为一个有趣的问题。在这项研究中，一种改进的优化算法称为弹性鲸鱼优化算法（SWOA），建议估算太阳能电池的模型参数。SWOA是WOA的一种概括，它具有收敛速度快，全局搜索能力强且具有较高的鲁棒性的优点。为了查询SWOA的效率，提出了该算法来估计太阳能电池和光伏（PV）模块的模型参数。仿真结果验证了该算法的优越性。此外，SWOA算法在实际应用中的有效性已使用商业模块进行了评估，其中包括多晶（SW255），多晶（KC200GT）和单晶（SM55）。针对在不同辐照度和温度条件下的各种运行条件进行此评估，这会导致PV模型的参数发生变化。