🧵17/19
All of this data also feeds into a “Home Dashboard” which shows various current stats.
The most useful one on here is the table in the top row. This shows, for various lengths (1, 2, 3 hours) when the best time to use the energy will be, and how long from now that time is. We use this when setting the washing machine, for example.

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🧵15/19
I’ve mentioned our car occasionally above. The main script determines when the car should be charged based on the current battery level and energy prices. This graph is from a couple of weeks ago after we’d been on a longer journey (also on a day when prices were regularly at or below £0.
I have a config file that specifies what time the car should be charged to, and what percentage (usually 80%, but occasionally if we’re travelling further, 100% - in this case, I really didn’t need 100%, but had mis-calculated how much we’d need)

As with the house battery, the blue background is “hold”, and the red is “charge”. The yellow bar at the bottom shows when the car is plugged in.

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🧵14/19
I pull carbon intensity data for my region of the UK. This is currently only used for the calculation of the cumulative CO2 for the day. I could use it for more in future, allowing me to, for example, prioritise minimising CO2 instead of cost.

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🧵13/19
A similar, by slightly different comparis that I also do is how much power and CO2 equivalent I am importing, exporting, generating with solar, and also what this would be with only the load power.

The key thing that I wanted to track with both these and the previous graph was that net (blue) is constantly significantly lower than load (orange)

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🧵12/19
I also keep track of what the cost would have been in various other scenarios, including other Octopus tariffs (Flux, Agile import/export, Fixed), as well as what my cost would be if I were only paying for the load.

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🧵11/19
The first graph here shows the import (blue) and export (yellow) power per period.
The second shows the cost for import (red) and value for export (green), as well as the net cost (blue).
The third graph shows the cumulative import/export/net cost across the day.
(my cumulative calculations are currently based on UTC, hence it starting at 1am local time)

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🧵9/19
When calculating what the inverter should be doing, I look at the energy prices, the 70th percentile of the load, and the 30th percentile of the solar generation (calculated from the 10th, 90th and 50th percentiles as reported by Solcast.
I keep track of what I consider the value (per kWh) of energy in the battery (the blue line) as well as the actual current battery level (purple solid) and predicted battery level (purple dashed). I run a few steps to determine the best inverter mode for each half-hour period. This is shown with the background colour in this graph.
Red: charge the battery
Blue: hold the battery (use energy from the grid)
Green: use the battery (but don’t charge from solar - export all excess solar power)

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🧵8/19
Here is the equivalent averages graph for the load power that we’re using in the house. The high points in here would be related to us charging the car. The median house load is below 0.8 kWh across the whole day.

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