Abstract The accuracy of extracting the unknown parameters of photovoltaic models is closely related with the effectiveness of modeling, simulating, and controlling photovoltaic systems. Metaheuristics have been widely used for improving the accuracy of extracting the unknown parameters of photovoltaic models. Despite the success of such techniques in this application area, they require parameter adjustment, which will restrict their applications especially for non-expert users. This is the motivation of this work, in which a novel metaheuristic is proposed called generalized normal distribution optimization, the proposed method is inspired by the generalized normal distribution model; each individual uses a generalized normal distribution curve to update its position. Unlike the majority of metaheuristics, the proposed method only needs the essential population size and terminal condition to solve optimization problems. In order to benchmark the performance of the proposed method, it is employed to extract the unknown parameters of three photovoltaic models including single diode model, double diode model and photovoltaic module model. The solutions obtained by the proposed method are compared with those of ten state-of-the-art metaheuristic algorithms and some recent reported solutions. Experimental results demonstrate the excellent performance of the proposed method for parameter extraction of the applied photovoltaic models in terms of quality and stable of the obtained solutions. 1

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广义正态分布优化及其在光伏模型参数提取中的应用

摘要 光伏模型未知参数提取的准确性与光伏系统建模、仿真和控制的有效性密切相关。元启发式已被广泛用于提高提取光伏模型未知参数的准确性。尽管此类技术在该应用领域取得了成功，但它们需要调整参数，这将限制它们的应用，尤其是对于非专家用户。这就是这项工作的动机，其中提出了一种称为广义正态分布优化的新元启发式算法，该方法受到广义正态分布模型的启发；每个个体使用广义正态分布曲线来更新其位置。与大多数元启发式算法不同，所提出的方法只需要基本人口规模和终端条件来解决优化问题。为了对所提出方法的性能进行基准测试，采用了提取三种光伏模型的未知参数，包括单二极管模型、双二极管模型和光伏组件模型。通过所提出的方法获得的解决方案与十种最先进的元启发式算法和一些最近报道的解决方案的解决方案进行了比较。实验结果证明了所提出的用于参数提取应用光伏模型的方法在获得的解决方案的质量和稳定性方面的优异性能。1 用于提取单二极管模型、双二极管模型和光伏组件模型三种光伏模型的未知参数。通过所提出的方法获得的解决方案与十种最先进的元启发式算法和一些最近报道的解决方案的解决方案进行了比较。实验结果证明了所提出的用于参数提取应用光伏模型的方法在获得的解决方案的质量和稳定性方面的优异性能。1 用于提取单二极管模型、双二极管模型和光伏组件模型三种光伏模型的未知参数。通过所提出的方法获得的解决方案与十种最先进的元启发式算法和一些最近报道的解决方案的解决方案进行了比较。实验结果证明了所提出的用于参数提取应用光伏模型的方法在获得的解决方案的质量和稳定性方面的优异性能。1 实验结果证明了所提出的用于参数提取应用光伏模型的方法在获得的解决方案的质量和稳定性方面的优异性能。1 实验结果证明了所提出的用于参数提取应用光伏模型的方法在获得的解决方案的质量和稳定性方面的优异性能。1