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No matter how good the software is, the use of highly validated and accurate input data is very important for having the best simulation results.

The use of data with low accuracy and with fewer sites for validation will lead to highly uncertain results and this, in turn, affects the bankability of the project. Therefore, it is very important to consider highly reliable and accurate weather data from Solargis for simulation using third-party software.

At the design phase, using reliable data lead to the proper selection of components and system layout.

At the operation phase, the integration of consistent and widely available recent data in solar monitoring platforms will help the proper management of the solar power asset by making performance monitoring cost-effective and transparent.

 

Effect of data aggregation

In case of PV systems, module's response is depending on radiation and temperature values at each point of time. So depending on the data input we use as an input for the calculations we can find two cases: 

Using monthly aggregated values. In this case, synthetically generated hourly profiles need to be generated in the third-party software, since that is the typical granularity of most of the tools used for PV yield simulation. Monthly averages can be downloaded from Prospect app. 

Using hourly or sub-hourly values. The electricity yield will be simulated from real values hence improving the accuracy of the results. Using sub-hourly values will improve the calculation of PV losses when compared to using hourly values. Hourly or sub-hourly files are available through climData.

The data are provided by Solargis in a suitable format so it is easily integrated by any user in the most popular applications used in the solar industry. When required by the software developers, automatic import of Solargis data is possible via web service. Know more about how to import Solargis data in PVsyst, PV*SOL and NREL SAM and take a look at this list of integration partners with a direct connection with Solargis data.