OK, I managed to muscle my way through a calculation using my Sense hourly net usage (Total Usage - Solar Production) for as much of 2019 as I have (Apr. 6 - Dec 31), for ALL 67 active PG&E tariffs. I have also done a comparison against my my matching 2019 billings, though there are still some ambiguities given I use a separate CCA (Community Choice Aggregation) supplier for generation.
So comparison first. For 2019, I was on the EV-A EV Time of Use plan, but with a different generation supplier so I was subject to PG&E’s Power Indifference Adjustment fee. I also chose a premium plan, ECO100, that is 100% renewable. That hybrid rate structure (separate generation + premium ECO100) isn’t in the OpenEI database so I had to emulate it by adding my PG&E NEM charges to my PCE charges, then subtracting off the ECO100 premium fees. Generally the numbers were close on a monthly basis though they occasionally did differ by more than 10% of the total bill. I’ll have to look a little bit more closely, but there isn’t an easy way to peek inside the highly variable PG&E “indifference charge”.
The upshot is that I think the calculator script is working though I’m going to have to do the hard work of confirming everything this weekend.
For those of you who want to see the broader comparison, here’s the whole spreadsheet kicked out by the R script. It’s clear that there are some rate plans that might be better for me, but I would really need to look over a whole year. I can see that my move from E1 for Region T, to EV-A has saved me around 1300$ for 2/3 of year, or maybe 2000$ over the course of year.
The Partial Start and Partial End columns reflect the partial months, in Apr’19 before the first full billing period, and the remainder of Dec’19, after the last full billing period in the year. The other thing that occurs to me is that this comparison is not very “diagnostic”. It really doesn’t give you a good view of why your bill is so high or so low. It probably would be useful highlighting billing periods where you spent the highest % of the time in the higher pricing tiers or pricier TOU periods.
Results.xlsx (20.1 KB)
Anyway, after doing a little more checking, it’s going to be time to expand to other utilities.
For anyone who wants to look at some junky but operational code, here’s a look. No attempt to functionalism, though I did work hard to use R parallel computations whenever possible.
PGEbilling.R (5.4 KB)