SolarAnywhere® average year summary files provide a quick summary into the solar resource, weather, and estimated losses due to snow and soiling at your site. They can be downloaded with both SolarAnywhere Typical Year and Sites licenses. These files contain long term monthly sums or averages for each of the selected irradiance or weather data fields. The years included in calculating the long-term monthly sums/averages are dependent upon the geographic data region:
Select a tile location for downloadTo download average year summary files:
- Click “Edit Settings”
- Check the box next to “Avg. Year Summary” under “Typical year options”
Figure 1. Selecting the Average Year Summary file option in the SolarAnywhere data website
Users can demo average year files with SolarAnywhere Public.
Average Year Albedo
The 12 monthly, long-term average-albedo values provided in the average-year summary file are useful in PV performance modeling. These values are calculated from the full available time series of SolarAnywhere albedo at each location, meaning they account for long-term snow conditions.
The long-term average monthly albedos can be input directly into the project settings of your PVsyst simulations.
Figure 2. Example average year summary file
Figure 3. PVsyst project settings
Average Year Snow and Soiling Losses
The 12-month, average snow and soiling loss values provided in the average-year summary file are useful in PV performance modeling. These values are calculated using open-source pvlib snow and soiling loss models with the full historical time-series SolarAnywhere weather data such as precipitation and particulate matter at the project location.
The years included in calculating the average snow and soiling loss estimates are dependent upon the geographic region:
Average snow losses are generated using the NREL model (also commonly referred as the ‘Marion’ model) for a representative PV system with a fixed-axis (latitude-tilt) and a tracking PV system. Average soiling losses are generated using the Humboldt State University (HSU) soiling model for a tracking PV System. SolarAnywhere uses the latest version of the pvlib PV performance models available in SolarAnywhere Energy Modeling Services at the time of Average Year Summary file generation.
To include soiling and snow loss estimates in your Average Year Summary file, select the Average Snow Losses and Average Soiling Losses checkboxes under Datasets as shown in Figure 4.
Figure 4: Selecting Average Snow and Soiling Losses in the SolarAnywhere Data Website
The accumulation of snow and particulate matter is cumulative and time-dependent by nature. Using full historical time-series data can improve the reliability of average snow and soiling loss estimates, and account for the effect of inter-annual variability on losses. In addition to local weather data, the PV system’s configuration (such as tracking and tilt) and site-specific loss parameters (such as amount of rain that is enough to clean PV panels of accumulated soiling completely, also known as cleaning_threshold) can further affect the magnitude of losses.
Average loss estimates included in the SolarAnywhere average year summary file are generated using default values for loss parameters such as cleaning_threshold. The complete list of loss parameters and default values used in SolarAnywhere can be found in the SolarAnywhere API Documentation for snow and soiling losses.
To learn more about the SolarAnywhere loss methodology, validation and applicability of the data , visit these support center pages:
Average monthly snow and soiling loss estimates can be input into third-party PV performance models such as PVsyst and PlantPredict to make PV production estimates more site-specific.
Figure 5: Example Snow and Soiling Loss Data in the Average Year Summary File