I’m fascinated by numbers (logging my exercise, monitoring the weather, logging fuel consumption) and started logging how much electricity we use at home by reading the meter. We recently installed a solar hot water system and recent turmoil in Botswana’s power supply got me thinking about solar electricity – so how much energy do we use, and what do we do with it?
After much surfing of the internet and eBay browsing I discovered the OpenEnergyMonitor project, soon afterwards there was a box of goodies in the mail to me: a few emonTx v3s, Raspberry Pis, current transformers, temperature probes and an emonGLCD.
A couple of months ago I managed to sort out the installation (bit of a faff, but that’s another story), and now I can see how much power is being used at home from anywhere with an internet connection (as long as Orange Botswana keeps our Flybox online and the emoncms connection live). The nice thing about emoncms is that you can also embed the charts in your own website:
Running Power Use
Graphs show how many watts were being used at a particular moment in time, with a 1 minute resolution (subject to connection, emoncms joins the dots so a period with no readings resolves as a straight line).
Red, yellow and blue correspond to the mains supply (we have a 3-phase power supply), black is the combined total.
You can zoom and scroll using the D|M|Y|+|-|<|> buttons. Unfortunately you have to do it individually on each graph as I haven’t worked out how to synchronise them.
It’s interesting to look at the graphs and workout what’s causing the movements, I have the advantage of knowing what items are connected to each phase.
–live feed currently disabled due to connectivity challenges: if you have knowledge on generating static graphs on the logger side (like the ones here from weewx/sqlite) leave a note in the comments–
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L2
L3
Total: L1 + L2 + L3
Daily Power Use
Each bar show the kWh used per day, i.e. the total electrical energy.
If the connection fails it can cause unusually low totals (no feed for some hours) or missing columns (no feed the whole day). Anomalies can be identified by looking for long straight lines in the graphs above on the day in question.
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L2
L3
Total: L1 + L2 + L3
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