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Hi @oscarmenz, what you need is a decomposition/separation model that estimates DNI and DHI from GHI. Then you can use those component estimates with a transposition model to get POA. pvlib has several decomposition models; see here: https://pvlib-python.readthedocs.io/en/stable/api.html#dni-estimation-models Edit: in the latest docs, this is the correct link: https://pvlib-python.readthedocs.io/en/stable/reference/irradiance.html#dni-estimation-models |
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You can use one of the decomposition models in pvlib/irradiance.py, e.g., Erbs, to get DHI and DNI from GHI. There are several choices, see documentation here. |
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The GHI to POA Transposition example here requires DNI and DHI - not common measurements taken in the field.
Suppose I have a dataset of only GHI data - how could I use this function to convert to POA given only these points, facility location, and time of year?
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