This paper addresses the problem of parametric estimation in solar cells considering manufacturer datasheet information regarding open-circuit, short-circuit, and maximum power points from the point of view of mathematical optimization. To represent this problem a single-objective function is formulated associated with the minimization of the mean square error of the single-diode model evaluated in the operational points reported by the manufacturer. The solution of this nonlinear non-convex optimization model is addressed with a metaheuristic optimization technique known in specialized literature as a vortex search algorithm (VSA). This metaheuristic optimization method works with Gaussian distribution functions and variable radius to explore and exploit the solution space by generating hyperspheres that move through the solution space as a function of the best current solution. The VSA is implemented in MATLAB environment by using commercial photovoltaic module information, where numerical results demonstrate the efficiency of this optimization method with objective functions lower than 1times10-25 and processing times around 6.13s.

中文翻译：

---

考虑制造商数据表信息的涡旋搜索算法应用于光伏电池参数估计


本文从数学优化的角度考虑了有关开路、短路和最大功率点的制造商数据表信息，解决了太阳能电池的参数估计问题。为了表示这个问题，制定了与在制造商报告的操作点中评估的单二极管模型的均方误差最小化相关的单目标函数。这种非线性非凸优化模型的解决方案是通过元启发式优化技术来解决的，该技术在专业文献中称为涡搜索算法（VSA）。这种元启发式优化方法与高斯分布函数和可变半径配合使用，通过生成作为当前最佳解的函数在解空间中移动的超球面来探索和利用解空间。 VSA利用商业光伏组件信息在MATLAB环境下实现，数值结果证明了该优化方法的效率，目标函数低于1×10-25，处理时间约为6.13s。