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An Accurate and Fast Computational Algorithm for the Two-diode Model of PV Module Based on a Hybrid Method

机译:基于混合方法的光伏组件两二极管模型精确快速计算算法

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This paper proposes an improved hybrid method to compute the parameters of the two-diode model of photovoltaic (PV) module. Unlike previous methods, it attains the speed of the analytical approach by utilizing only datasheet information. Furthermore, its accuracy is not compromised as it does not require simplifications in its computation. Four parameters are determined analytically, while the remaining three are optimized by using an evolutionary algorithm, i.e., the differential evolution. The speed is improved because the parameters are optimized only once, i.e., at standard test condition, while the values at other conditions are computed analytically. Furthermore, a procedure to guide the initial conditions of the Newton–Raphson iteration is introduced. For validation, the algorithm is compared to other established computational methods for mono-, polycrystalline, and thin film modules. When evaluated against the experimental data, the mean absolute error is improved by one order of magnitude, while the speed is increased by approximately threefold. The standard deviation of the decision parameters over 100 independent runs is less than 0.1—which suggests that the optimization process is very consistent. Due to its speed and accuracy, the method is envisaged to be useful as a computational engine in PV simulator.
机译:本文提出了一种改进的混合方法来计算光伏(PV)模块的二二极管模型的参数。与以前的方法不同,它仅利用数据表信息即可达到分析方法的速度。此外,它的准确性不会受到影响,因为它不需要简化计算。通过解析确定四个参数,而其余三个则通过使用进化算法(即差分进化)进行优化。由于仅对参数(即在标准测试条件下)进行了一次优化,而对其他条件下的值进行了解析计算,因此提高了速度。此外,介绍了指导牛顿-拉夫逊迭代初始条件的过程。为了进行验证,将该算法与其他已建立的单,多晶和薄膜模块的计算方法进行了比较。当对照实验数据进行评估时,平均绝对误差提高了一个数量级,而速度提高了大约三倍。 100个独立运行中决策参数的标准偏差小于0.1,这表明优化过程非常一致。由于其速度和准确性,该方法被认为可用作PV模拟器中的计算引擎。

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