Reputation: 61
I would like to calculate daily PV system energy output in Python and PVLIB from Daily global solar exposure data so I can monitor the performance of a solar PV system i.e. I want to be able to compare the actual energy output of the PV system with a value calculated from the solar exposure data to make sure it is performing well.
Here is an example of the data: http://www.bom.gov.au/jsp/ncc/cdio/wData/wdata?p_nccObsCode=193&p_display_type=dailyDataFile&p_stn_num=056037&p_startYear=
I've been playing around with PVlib but I can't work out which functions to use.
I was hoping I would be able to enter in all the parameters of the PV system into a function along with the solar exposure data and it would give me the predicted energy output.
Upvotes: 1
Views: 2479
Reputation: 944
Well it really depends on how precise you want to be. It's a full time job to design a good algorithm to estimate produced power from only the Global Horizontal Irradiance (GHI - the data you gave).
It depends on the geographical position, the temperature, the angle of your panels, their orientation, their type, the time of day/year, even the electrical installation etc...
However if you're not looking for too much precision, a simple model would be :
Power = Efficiency * GHI * Area
You could then refine the model accounting for the angle between you panels and the sun, for example using pvlib.solarposition.get_solarposition().
A few references:
Computing global tilted irradiance from GHI
PvLib's cool ModelChain to model precisely you installation
A good overview of most factors impacting you efficiency
PvLib's doc is pretty good, have a look at the PvSystem, ModelChain etc...
PS : not enough reputation to add a comment, though I know it doesn't really deserve an answer :/
Upvotes: 4