The simulation of multi-annual time series of photovoltaic electricity generation in high temporal resolution using reanalysis data has become a common approach. These time series are crucial to assess the viability of electricity systems with high shares of variable renewable generation. Our work combines the new ERA5-land reanalysis data set and PV_LIB to generate hourly time series of photovoltaic electricity generation for several years and validates the results using individual data of 23 large photovoltaic plants located in Chile. We use a clustering algorithm to differentiate between fixed and tracking systems, as meta-information on installation type was not available. Results are compared with photovoltaic output for these locations calculated using MERRA-2, a global reanalysis with five times lower spatial resolution, which is one established source for modelling photovoltaic generation time series. Accuracy and bias indicators are satisfactory for all plants, i.e. correlations are above 0.75 for all installations and above 0.9 for more than half of them, while the mean bias error is between -0.05 and 0.1 for all instalations. However, the improvements in simulation quality over results obtained with MERRA-2 are minor. From our assessment of generation data quality, we conclude that efforts towards availability and standardization of data of individual installations are necessary to improve the basis for future validation studies.

使用重新分析数据以高时间分辨率模拟光伏发电的多年时间序列已成为一种常用方法。这些时间序列对于评估具有大量可变可再生能源的电力系统的生存能力至关重要。我们的工作结合了新的ERA5-land再分析数据集和PV_LIB，以生成几年的每小时光伏发电时间序列，并使用位于智利的23家大型光伏电站的单独数据来验证结果。由于没有有关安装类型的元信息，因此我们使用聚类算法来区分固定系统和跟踪系统。将结果与使用MERRA-2计算的这些位置的光伏输出进行比较，MERRA-2是全球再分析，空间分辨率低五倍，这是建立光伏发电时间序列模型的一种可靠来源。精度和偏差指标对于所有工厂均令人满意，即，对于所有安装，相关系数均高于0.75，对于一半以上而言，相关系数均高于0.9，而对于所有安装，平均偏差误差均在-0.05至0.1之间。但是，与使用MERRA-2获得的结果相比，仿真质量的改善很小。从对发电数据质量的评估中，我们得出结论，为提高未来验证研究的基础，有必要努力提高单个设备的数据的可用性和标准化。而所有安装的平均偏差误差在-0.05至0.1之间。但是，与使用MERRA-2获得的结果相比，仿真质量的改善很小。从对发电数据质量的评估中，我们得出结论，为提高未来验证研究的基础，有必要努力提高单个设备的数据的可用性和标准化。而所有安装的平均偏差误差在-0.05至0.1之间。但是，与使用MERRA-2获得的结果相比，仿真质量的改善很小。从对发电数据质量的评估中，我们得出结论，为提高未来验证研究的基础，有必要努力提高单个设备的数据的可用性和标准化。