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Extraction of Efficient Electrical DC Parameters of Solar Photo-voltaic Model by Analytical and Numerical Techniques

机译:通过分析和数值技术提取太阳能光伏模型的高效电直流参数

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Determining the exact and accurate parameters from the Solar Photo-Voltaic (SPV) model by analytical or numeric technique is still a challenging task for researchers. This paper examines the investigation of parameter extraction strategies which are basically dependent on the maker's datasheets. An investigation is done for different advanced models of Solar PV, utilizing the seven DC unknown parameters from Double Diode Model (DDM) of SPV. Extraction of accurate DC parameters is done by Trust-Region-Dogleg (TRD) numerical iterative technique with suitable input from the analytic technique for DDM method. Simulation results in the form of I-V characteristics for different SPV models are obtained. An improved parameter extraction technique is suggested in this work. The efficacy of the proposed technique is justified by comparing the performance of the proposed technique with two other different techniques reported in the literature, under varying irradiation and temperature conditions. Interesting results are observed in terms of reduced Root Mean Square Error (RMSE) and Execution time, particularly during the low irradiation conditions.
机译:通过分析或数字技术确定来自太阳能光伏(SPV)模型的精确和准确参数仍为研究人员的一项具有挑战性的任务。本文研究了基本上取决于制造商的数据表的参数提取策略的调查。为SPV的双二极管模型(DDM)的七个DC未知参数,为不同的高级模型进行了调查。精确DC参数的提取是通过信任区域 - Dogleg(TRD)数值迭代技术完成,具有来自DDM方法的分析技术的合适输入。获得了不同SPV型号的I-V特性的模拟结果。在这项工作中提出了一种改进的参数提取技术。通过在不同的照射和温度条件下比较了所提出的技术的性能,通过比较了提出的技术的提出技术的性能,所提出的技术的性能是合理的。在减少的根均方误差(RMSE)和执行时间方面,特别是在低辐照条件下,观察到有趣的结果。

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