Simulation of multi-annual time series of solar photovoltaic power: Is the ERA5-land reanalysis the next big step?

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.