Export your Hildebrand Bright/Glow data by:
visiting https://glowmarkt.com/pages/property/energy-data,
choosing 30 minutes for granularity,
and hitting download.
Copy the downloaded CSV to the same folder as this repo and rename it to "hildebrand_output.csv".
Run each Python file in order and filling in any questions:
1_strip_year.pyand answer the question(s):What year would you like to strip down to?2_remove_outliers.py(no other input needed)3_final_average.py(no other input needed)
Then just open final_weekday_averages.csv in your standard spreadsheet editor (google docs, excel, libreoffice, etc).
Now you can do anything with this data. ie: Use our Calculator Template to compare the cost between suppliers.
because i (seb) am getting a new ev and ev charger (well i mean my parents are) and need to know what tarrif is best for our energy usage and for charging my (parents) new car.
stop asking questions and run the damn scripts.
| Day | Avg. Day Use (kWh) | Avg. Night Use (Midnight-5AM) (kWh) |
|---|---|---|
| Monday | 0.295 | 0.194 |
| Tuesday | 0.274 | 0.198 |
| Wednesday | 0.306 | 0.189 |
| Thursday | 0.31 | 0.194 |
| Friday | 0.307 | 0.196 |
| Saturday | 0.353 | 0.194 |
| Sunday | 0.342 | 0.201 |
this is exported as a .csv file which most spreadsheet apps can read.
PS: this is actually my final data after running my glow export through these scripts.