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New Approach for PV Systems Performance Analysis Reduction

机译：减少光伏系统性能分析的新方法

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For a good study of PV systems performance, it is necessary to have a data measured at a fine time step. However, such data are not always available, especially in the remote sites because of the economic costs involved by the acquisition of such data. To reduce these costs, we propose in this article a new approach based on the results of the fractal classification we have already developed. This approach allows the construction of typical days for each class obtained, then comparing the results of long-term performance to the ones obtained while using typical cases resulting from daily solar irradiances classification. The approach has been applied to 2 stand-alone PV systems and 1 PV system connected to the grid. The comparison of the results obtained for long-term performance and typical cases shows a good agreement which demonstrates that our approach leads to data compression which may reduce the PV systems performance analysis.
机译：为了更好地研究光伏系统的性能，有必要在一个很好的时间步长上测量数据。但是，由于获取此类数据会涉及经济成本，因此此类数据并不总是可用，尤其是在远程站点中。为了降低这些成本，我们在本文中提出了一种基于我们已经开发的分形分类结果的新方法。这种方法允许为每个获得的类别构建典型的天数，然后将长期性能的结果与使用每日太阳辐照度分类所产生的典型情况下获得的结果进行比较。该方法已应用于2个独立光伏系统和1个连接至电网的PV系统。将长期性能和典型案例的结果进行比较，可以很好地达成共识，这表明我们的方法导致了数据压缩，从而可能会降低光伏系统的性能分析。

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