Recently, ISO New England issued a dataset showing Solar Production for 2018 in New England, which provided me a wonderful opportunity to look for useful insights about the region’s solar power. We know what a duck curve looks like from load curves posted by the CAISO, which is directly caused by solar generating supply resources on nice, bright, sunny days. Step one; whip up an R script to graph the solar production data to see the inverse duck curve, i.e. Solar Production Supply Curve, by hour, over all of 2018. Sure enough it’s just what I was expecting:
Step two; Create a second graphic showing Solar Production by Month:
What’s this: April had the highest hourly Solar Power output for all of 2018! I surely expected June to be the peak power output winner with the Summer Solstice and all, but it did finish in second place. July takes first place for total energy produced, not too surprising. And, what’s the story behind those outliers in November and February.
Next steps: Examine weather and outage data to see if that might provide some useful insights into why April beats June and July in the race to produce the highest solar power output. As Mark Twain once said, “It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so”. Maybe it’s the April showers of bright sunshine that bring the May flowers, based on this chart, unlike what the Song tells us. But, as we all know, Causality is difficult to establish in statistics.