Thornleigh Passive House

We've recieved three water bills since moving in (how time flies)... for about half that time we have been working from home and even had the kids at home for six weeks. Even with all that we've done really well.  City water: the quarterly bill from the "old normal" was 172L/day, the lock down quarter was 198L/day, and the working from home quarter was 180L/day. So not too much variance really, and 183L/day over three quarters is good and puts us at 46L per person per day... about 20% of the typical Sydney resident.  Rain water: Since moving in we have been able to supply our laundry, toilet and garden needs for all but one week in January... without having to water some of the new plants we probably could have made it 100% on rain water for those needs. I plotted rain fall (from the NetAtmo rain gauge which is excellent) and water level in the rain water tank (using a Vegetronix AquaPlumb sensor, which the individual measurements (hou

It took many more tries than I care to admit, but I finally managed to put the GoPro on the tripod to capture some timelapse photos capturing the performance of the fixed shading on the exterior of the house as well as the sunlight coming in through the water tanks across the day. 1. Outside - sun on the northern face of the house . 2. Inside sun on the translucent tubes .

Another month of house data... The weather is getting down right cold, with lots of modest rainfall. Of course the big news this month was still COVID-19 (2 adults working from home except for a couple of days towards the end of the month), but the kids were back to school all month. We have even run the heater a fair bit to bring the house temperature up just a bit. We were using the ERV core all month as our part of data collection on the two cores in the Sydney climate. Percentage of hours in below, within, above the 20 - 25 °C target temperature range for the month. Inside / Outside % < 20 °C % 20 - 25 °C % > 25 °C Inside 14% 85% 1% Outside 100% 0% 0% Methods: I have taken the 5 minutely data from the wirelessTag sensors and calculated the median temperature of each sensor 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