I intend to use PVlib for a high-level urban study. (Being an architect I am now learning this world's terminology - apologies for any technical mistakes)
I manage to get a very detailed output from the library using the various tutorials, however, the emphasis is in the study is simplification and I would be happy to compromise the preciseness of the analysis results set. i.e, the ability to perfectly anticipate PV gains is not of crucial-importance for the work and more generic outcome is required.
is there a way to receive a more generic analysis relying on a very basic input?
For example, given a location and desired system size in kWp, the output would be a reasonable set of hourly generation values. I do not wish to go into the specifics of modules and inverters, as the user may wish to simulate situations where a specific kit would make no sense or be invalid.
For this application, I'd specify the PVSystem using PVWatts parameters and I'd use ModelChain. See the last couple paragraphs of the modelchain documentation for an example (code reproduced below).
In [30]: pvwatts_system = PVSystem(module_parameters={'pdc0': 240, 'gamma_pdc': -0.004})
In [31]: mc = ModelChain(pvwatts_system, location,
....: aoi_model='physical', spectral_model='no_loss')
In [32]: print(mc)
ModelChain:
name: None
orientation_strategy: None
clearsky_model: ineichen
transposition_model: haydavies
solar_position_method: nrel_numpy
airmass_model: kastenyoung1989
dc_model: pvwatts_dc
ac_model: pvwatts_inverter
aoi_model: physical_aoi_loss
spectral_model: no_spectral_loss
temp_model: sapm_temp
losses_model: no_extra_losses
In [33]: mc.run_model(times=weather.index, weather=weather);
In [34]: mc.ac
Out[34]:
2017-04-01 12:00:00-07:00 198.519999
dtype: float64