Satellite-Derived Data for Assessing PV Asset Performance
Global deployed solar energy production is expected to surpass 1 Terawatt within the next year. Who is in charge of monitoring and database management to ensure the performance of all these photovoltaic assets? And what solar data are they using to determine how much an asset should really generate?
Bigger assets have irradiance monitors for use in measuring performance. However, they are prone to failures, deficiencies, and calibration concerns. Smaller photovoltaic systems even often have no irradiance monitoring.
Satellite-derived Irradiance Projections
There are four basic processes in contemporary approaches for determining solar radiation from geostationary satellite systems.
- Using Albedo to Detect Cloud Formation
The imagery supplied by satellites in geostationary orbits above the Earth is the main tool used for spotting clouds from afar. The most recent satellites can provide full-disk images of the planet’s surface with resolutions as fine as 500m. Imaging systems record a variety of recognizable light wavelengths as well as a few other infrared wavelengths.
The satellite image covers land and ocean textures, as well as cloud elements. A closer look reveals areas of exceptionally brilliant land surfaces, such as beaches, as well as snow cover. To separate the land surface information from the cloud cover characteristics, an approximation of the ‘albedo,’ or the look of the backdrop when no clouds are evident, must be computed.
Albedo estimations are generated by scanning satellite photos from the recent past that do not contain cloud cover and storing them in memory. With Albedo, you can see how the surface would seem in the absence of clouds. A deviation from the typical look reveals the whereabouts of a cloud.
Interestingly, you’ll notice snow cover in some regions on the map, as well as several regions of brilliant sands in Northern Africa. These characteristics might easily be mislabeled as cloud cover if a proper albedo computation is not used.
- Classifying Cloud Cover Using Cloud Opacity
After applying the albedo estimation to the original visible data, the next step is to determine the density of the cloud cover that is exposed to solar light. Cloud opacity refers to the permeability of a certain cloud cover pattern to solar light.
Cloud opacity is estimated in some ways, some of which are confidential and not publicly disclosed. Nonetheless, the difference between unprocessed visible imagery and computed Albedo will be used as the primary input to estimate cloud opacity by the vast majority, if not all, of the models.
These and the formulas for predicting the connections between cloud opacity and solar radiation are then measured using surface radiation data from pyranometers in the satellite service zone.
When examining a cloud opacity calculation, take note of how the ground surface elements have already been totally erased, leaving only the cloud components. The opacity of the cloud is then determined using a scale of 0 to 100.
- Using Clear-sky Approach to Calculate Solar Radiance
There is one more step to determining the solar radiation that reaches the Earth’s surface, and that is to compare the projected cloud opacity estimate to an assumption of how much solar light would be obtainable under sunny conditions. This is best conceived of as the quantity of solar that would hit the Earth’s surface when it is not cloudy.
In principle, these models depend on a few input factors to be computed:
- Solar geometry
- The distance between the Earth and the sun
- The ratio of aerosols to turbidity
To begin with, the higher the sun is, the more cosmic irradiance a specific portion of the Earth receives. Second, the amount of sunlight hitting the Earth varies by a few percentages as its elliptical orbit moves it closer and closer to the sun. Finally, water vapor and other aerosols reduce some of the solar energy that might hit the surface if there was no atmosphere.
- Obtaining Solar Irradiance Data from Satellites
When the clear-sky radiance has been reliably calculated using a particular model, a quick conversion is used to create a spatially prolonged estimate of the available solar irradiance at each area covered by the geostationary meteorological satellite data.