“First Solar will assimilate RayTracker’s nine employees and clients with the purchase, the Tempe, Arizona-based company said today in a statement. Tracking systems let solar panels follow the sun’s movements, increasing output from solar panels.”
Thanks to the California Energy Commission we can see what a real inverter efficiency curve looks like, and compare it to the pvwatts model.
It turns out that the pvwatts model doesn’t match reality very well. The pvwatts nominal efficiency of 92% is well below the average of current inverters, and the 4th order polynomial is a rather poor fit to the shape of the efficiency curve.
The plot below shows the measured efficiency curve for a SatCon PVS-135 (green) and the pvwatts model (blue). Clearly there’s quite a bit of room improvement.
I’ve created a log function to model the inverter and plotted that in red. Substituting the improved model in pvwatts calculations results in about a 4.5% increase in annual energy.
Even if you don’t know what inverter will be used in a particular case, just increasing the nominal efficiency inside pvwatts from 92% to something around 95% seems reasonable given the test data on the CEC site.
This is a plot of the pvwatts inverter model. Nominal efficiency is 92%, but if the input power is between 10 and 100%, a 4th order polynomial is used to calculate efficiency, and convert dc power to ac. If this is accurate (I haven’t yet found any efficiency curves published by inverter manufacturers), then there are some clear implications for string sizing.
Just about everyone in the solar energy world is familiar with pvwatts, but how many of them have actually had a chance to examine the source code? I’m just digging into it now, and I’ve already found several areas that could use some improvement. Considering how widely accepted this calculator is, the code is quite a shock. The algorithms make sense, but the implementation is a bit frightening.
More to come.