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Surface Albedo – most frequent questions

Due to the impact that surface albedo has on PV yield calculations, particularly for bifacial systems, there has been an increased interest in learning about this parameter. These are the most typical questions we are receiving and their corresponding answers:

Why are solar developers thinking about bifacial modules for their projects?

Bifacial PV modules is not a new technology, but it is gaining popularity amongst project developers. Bifacial modules offer several advantages in comparison with monofacial modules:

  1. Bifacial gain – with no system change you can expect higher yields. Design modification (increased height, row spacing, type of construction….) is required for the optimisation of the gain.
  2. Price – bifacial are only slightly more expensive than monofacial modules. However, bifacial gain usually outweighs the increased cost of panels

Which factors influence the bifacial gain?

There are a few major factors that influence the bifacial gain. To get the most out of your bifacial modules you should consider:

  • Surface albedo (discussed further in detail)
  • Installation height of the panels – the higher the better. NREL recommends at least 0.5m above ground. Over 3m there is very little impact. This, however, increases the costs of the installation
  • Spacing of the panels – the wider the better but again more expensive and unpopular
  • Tilt angle – slightly higher tilt angle than what is optimal for monofacial depending on local conditions

What does surface albedo represent?

Surface albedo (from the Latin word albus, which means white) is the measure of diffuse reflection of solar radiation from the ground back to space of incidence. It is dimensionless and measured on a scale from 0 (a black surface that absorbs all radiation) to 1 (a surface that reflects 100% of received radiation to space of incidence). So, for instance, a surface albedo value of 0.2 means that the surface reflects 20% of the received radiation.

This seemingly simple definition has relatively complex physical implications. Albedo is not a constant surface property of a particular surface. It is also dependent on atmospheric parameters and illuminating conditions. Albedo values vary in different temporal scales: minute, daily, seasonal and even interannual.

Typical daily variation of albedo (purple line) as measured at the clear-sky day of the 2nd of January 2011, in BSRN Bondville station, US:

Since albedo values are not constant, a typical range of values can only serve as a first preliminary estimate:

  

How to characterize the surface albedo for a particular site?

The historical values of surface albedo are a critical input for accurate yield simulation of bifacial PV projects. There are two main ways of obtaining historical albedo values at any location globally:

  • Climate reanalysis provides data on the recent history of the atmosphere, land surface, and oceans by combining numerical weather prediction (NWP) models with observations. These datasets are constantly updated and can provide globally gridded data with a high temporal resolution. They provide data with no gaps, but the spatial resolution is low.
  • Satellite-based models use inputs from sensors installed on satellites, which continuously provide new information. One of the best-known sensors and whose derived data are widely used, is called Moderate Resolution Imaging Spectroradiometer (MODIS), an instrument able to cover the globe every 1 to 2 days while making measurements in 36 spectral bands (7 for albedo). The spatial resolution achieved is noticeably higher than on the reanalysis, but the data contains gaps due to the presence of persistent clouds and/or fails in the detection of snow.

Why is it usual to find gaps in the time series of Albedo?

Weather events are often accompanied by clouds and satellites cannot "see" the Earth’s surface in the presence of clouds. In particular, data gaps due to snow events are especially challenging. We have observed under-detection and over-detection of snow albedo in all the sources we have checked. The reasons for this are:

  • Cloud-screening algorithms are not perfect and they present difficulties some times to accurately distinguish between clouds and snow.
  • Change in the snow properties along the time: fresh snow is very bright (albedos over 0.8), but it may smelt and become dirty in the short term and the albedo can be as low as 0.5 or even lower.

To solve this, the strategy to generate (daily) albedo is based on a weighted average of 16-days time window centred on the day of interest. This approach, followed by satellite-based MODIS products, allows to partially fill the gaps.

However, in some regions and moments of the year, this is not possible to do because of the strong cloud persistence. In such cases, for running a complete gap-filling we need to consider additional sources such as:

  • complementary satellite-based products
  • additional data from reanalysis

When combining different sources, we want to reach an optimum balance between both accuracy and spatial representation.

Any recommendations for a full albedo characterization and validation of the satellite-based estimations?

Several years of data is required to capture the full temporal variability of the surface albedo of a particular site. Having information about the land use on that particular site is also of great interest to interpret any changes in the data and assess the representativeness of the area covered.

Surface albedo can be measured with an albedometer, a combination of two individual pyranometers -optimally identical- facing up to the sky in the horizontal position, as usual for measuring GHI (Global Horizontal Irradiance), and facing down to the ground for the GRI (Global Reflected Irradiance). The quotient of both magnitudes is the surface albedo.

Hukseflux SRA11 albedometer

Although installing the sensor in the POA (plane-of-array) is useful to know the GTI (Global Tilted Irradiance) that is received on the backside of the panels, surface albedo cannot be measured in such position.

Ground-based albedo measurements, covering only a few days is not enough for having a robust one-to-one comparison between albedometers and satellite-based data. To cover full seasonal behaviour, we recommend measuring albedo for at least one-year period. A slightly shorter measurement period can be considered depending on the location.

Does Solargis provide surface albedo values?

Yes, Solargis has prepared an albedo database that is tailored to the needs of the solar power industry.  The database has been prepared by filtering available sources (coming from both satellite-based sources like MODIS and NWP like ERA5), properly combining them, applying downscaling methods, and running additional corrections. The data are available via Solargis products Prospect (as a new feature in the Professional Plan) and Evaluate (as an add-on to the Professional time series):

On the left, representation of surface albedo database in lower resolution with gaps. On the right, representation of Solargis albedo database:

Table with a description of the albedo data products offered by Solargis:

You can know more about technical specification of Albedo products in Solargis here: https://solargis.com/docs/methodology/albedo

How accurate is Solargis albedo database?

The Solargis albedo database has been validated using ground measurements. At the date of publication of this text, we have validated the database at8 sites across the USA belonging to AMERIFLUX and SURFRAD ground stations networks. The period of evaluation we have used was five years, from 2011 to 2015.

After running the comparison, the validation results of Solargis albedo versus ground measured data are (in terms of the estimated uncertainty):

Solargis database obtained the lowest bias in comparison to other sources of data (some of them used as an input for the database). Additional validation and local adjustment of the values provided by the database can be done if there are sufficient ground measurements available at the project site.

Are there differences between Solargis Albedo monthly averages (Prospect) and the averages calculated from Solargis Albedo time series (Evaluate)?

The averages of the Solargis Albedo time series (Evaluate) may not be coincident with Solargis Albedo monthly averages (Prospect). The reasons for this are:

  • In the daily time-series product, gaps in the data are not filled
  • In the monthly averages product, gaps are filled before calculating the averages to have a better statistical representation; we have also used different satellite-based MODIS product and the final resolution is lower.

Representation of Solargis monthly averages of Albedo for a sample location in Plataforma Solar de Almería, Spain:

Representation of Solargis time series of Albedo for the same sample location in Plataforma Solar de Almería, Spain:

If you want to request your sample of Solargis albedo data, or you have any questions please contact us 

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