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Differential Evolution with Dual-mode mutation for parameter estimation of different photovoltaic models

机译:不同光伏模型参数估计的双模突变的差分演变

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In order to design a photovoltaic (PV) system having superior performance, it is necessary to ensure that the PV system parameters are estimated properly. In the recent past, it is perceived that several authors have given emphasis to the estimation of PV parameters. The problem of PV parameter estimation is formulated in the form of a single objective function expressed as root mean square error (RMSE) between the experimental current and the estimated current values of the PV model under consideration. This objective function is intended to be minimized by evolutionary approach. Although different variants of the Differential Evolution (DE) were proposed in the past, but here Differential Evolution with dual-mode mutation (DEDMM) is projected. This mutation strategy brings improvement in exploration and exploitation capability of DE resulting in better solutions. The experimental I-V datasets are taken into consideration for estimating the parameters of single-diode and double-diode based PV cell models and PV module model. The results portray the effectiveness of DEDMM as compared to other methods suggested recently for parameter estimation of different PV models.
机译:为了设计具有优异性能的光伏(PV)系统,有必要确保估计PV系统参数。在最近的过去,它被认为是几位作者强调估计光伏参数。 PV参数估计的问题以单个物镜函数的形式配制,以在考虑的实验电流和PV模型的估计电流值之间表示为均方误差(RMSE)。该目标函数旨在通过进化方法最小化。虽然过去提出了差分进化(DE)的不同变体,但是在这里投射了双模突变(DIDMM)的差异演化。这种突变策略带来了DE勘探和开发能力的提高,导致了更好的解决方案。考虑了实验I-V数据集以估计基于单二极管和基于双二极管的PV电池模型和PV模块模型的参数。结果描绘了DEDMM的有效性与最近有关不同PV模型的参数估计的其他方法相比。

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