2021 October

Lockdown version 2.0 came to an end at the very end of October. The split system was off for most of the month (six days with heat and one day with cooling) and the HRV slid in and out of 'cooling season' and neutral modes of operation more times that I could keep track of. The HRV did a great job of keeping the house in the comfort zone. The kids went back to school for the last week of the month and the parents are were in the office a few days at the end of the month, but we were mostly at home... again.

Temperature from inside and outside the house as the percentage of hours in 0.5 °C bins. I've scaled the temperature in hopes that they will be comparable across months.

October temperatures (inside and out)


Methods: I have taken the 5 minutely data from the wirelessTag sensors and calculated the median temperature for each hour and determined the proportion of hours falling inside of the 20 - 25 °C target temperature (using the R functions 'aggregate' and 'hist'). Inside includes data from the wirelessTag sensors spread across nearly every room of the house. Outside is the data from the wirelessTag sensors outside near the cubby house and HRV intake. The water wall and door data are not included.

Energy production and consumption: 1. total daily consumption daily energy production, 2. daily net energy production, and 3. energy independence (which is the percentage of our daily consumption that is met directly by our solar panels).


October energy consumption & production

Methods: Data are taken from the Enphase Enlighten system. This reports solar generation and electricity consumption as well as import from and export to the grid in 15 minute intervals. The R function 'aggregate' is used to create daily values and the function 'vioplot' to create the plots. The plots show individual days as points, with the vertical black bar covering the middle 50% of the data, the big white circle is the middle of the data (median), the whiskers extend to the farthest points from the median that are not more than 1.5 times the interquartile range, and the grey 'violin' shows the distribution of the datapoints where the narrow portions indicates few datapoints and a wide portion indicates more commonly occurrence... much like a histogram.


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