Snow Modelling

Snow Modelling

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Output Parameter available within the Solcast API

Part of the output parameters within the Solcast Irradiance and Weather Forecast product endpoints

What snow related parameters are available from Solcast?

Solcast offers four snow related parameters across its range of products being those: snow depth, snow soiling for rooftops, snow soiling for utility scale sites and snow water equivalent.

Snow depth refers to how tall the physical snowpack on the ground would be and its given in centimeters. Snow soiling is an estimation of how much energy would be lost due to the photovoltaic (PV) panel being partially or completely blocked by a snowpile. Snow water equivalent is an estimation of the water volume contained in the snowpack if it were to melt.

What are the differences between the parameters?

Snow depth and water equivalent are physical estimates of snow being the first an estimate of the height of the snowpack on the ground and the latter is the snow depth liquid water equivalent (i.e., the depth of the water in a columns if you melted the snowpack in its entirety).

Snow soiling on the other hand accounts for percentage losses in PV modules due to these surfaces being covered in snow. Snow soiling for rooftops consider static solar panels that are commonly found in rooftops while snow soiling for ground based panels consider the effects of tilting systems. This difference becomes important when factoring in how quickly the amount of snow slidage and how quickly the soiling clears.

How does Solcast model snow soiling losses (2-3 sentences)?

The solcast algorithm calculates the amount of snow that will remain in the panel based on its volume and slidage. In the words of the author, “A model was developed that uses daily snow depth to identify the presence of new snow; an hourly plane-of-array irradiance and air temperature relationship to identify when snow slides down the PV array; the PV array tilt angle to determine how far the snow slides; and the extent of snow coverage on the PV array to determine the fractional energy output of the PV array”.

How are snow_soiling_rooftop and snow_soiling_ground different?

Snow soiling for rooftops consider static solar panels that are commonly found in rooftops while snow soiling for ground based panels consider the effects of tilting systems the possibility that their tilts can vary over time. This difference becomes important when factoring in how quickly the amount of snow slidage snowpack and how quickly the soiling clears.would slide across the panel surface unblocking its access to sunlight.

Does Solcast take into account snow soiling losses?

Yes and no. The API by default includes snow soiling losses (snow_soiling_rooftop, snow_soiling_fround) in all power modeling. Advanced PV power users can override these parameters with their own estimates or even set it to zero to disregard snow losses. So snow losses are taken into account but the advanced users may override these values.

Additionally, you can directly request the estimated losses due to snow soiling by requesting the parameters through the API.

What if I don’t want to use your snow soiling losses?

Solcast allows users to override its estimates of snow soiling losses in Advanced PV Power estimates. However some caution is suggested when taking this approach as completely ignoring potential losses due to soiling can lead to large overestimation of power generation.

Why might I override the Solcast snow soiling loss?

Solcast can predict the amount of expected snow and how it soils a solar panel. However we cannot account for actions taken at the site that would impact the total soiling. The most common of these is where manual clearing is performed, in which we would suggest you override the snow soiling losses with a 0% value.

What products/parameters include snow losses?

All Solcasts products that provide estimates of PV power have the capability of including the effects of  snow soiling. This is regardless of time range e.g. historic estimates or forecasts and includes grid aggregations.