@brettabailey,
One more discovery as I try to sort out my solar production vs. NREL PVWatts. Realize that the production year that PVWatts outputs is all based on standard time. That’s not an issue WRT to the lost and added hours of production time since both DST adjustments (spring forward, fall back) are during the nighttime (production=0). But it does mean that when you do a production prediction or a comparison against previous production, one has to offset data for spring to fall months by 1 hour. Not surprisingly, that’s what I had to do above to coerce my production vs. NREL PVWatts into something nearer the expected straight line.
Looking at my hourly 2019 (Sense) solar production vs. PVWatts data with data colored by month, you notice two things:
- My charted production data contains very little standard time data (Nov-March).
- Where there is production data from standard time (lavender and pink), it is scattered all over the chart. Nov-Mar in my area is the cloudy rainy season. That’s the place where PVWatts is really taking wild statistical guesses at which hours and days are going to be cloudy while local weather does it’s own thing, unlike the far clearer Apr-Oct.
So there is really a good reason for the data to match up when I offset my production vs. NREL PVWatts by one hour. That’s something you also need to take into account when you use PVWatts as a solar production predictor.
If I look at a linear model for my offset production data vs. NREL PVWatts for just the period during DST (Apr-Nov 2, 2019), I get:
Sense Production = 0.002550468 + 0.855212926 x NREL PVWatts
with fits of - Multiple R-squared: 0.8623, Adjusted R-squared: 0.8623.
sense_process_edits5.R (3.7 KB)