Yes, you are correct 48 values, so .24 is the median.
Of course it isn’t exact as the 48 values do change over time, both with new values being added to the end and the forecast changing as the estimation is more accurate. I could foresee if lots of low values get added to the end, it could delay until those low prices are realised, similarly if lots of high prices are added to the end, it may bring forward the best hours. I have also seen prices jump within the 30 minute interval, so what started out as the a best hour of the day can change dynamically.
I’m going to switch my pool filter over to this now to see how it runs over the next 24 hrs.
This scaleable best hours approach also has utility for other loads which can be time shifted, like the hot water service (run in best 4 hours of the day), heating/ cooling (run in best 6 hours of the day to maintain stable temp, home battery charging (14 kWh battery with max charge rate of 3.68 kW wants best four hours of the day).
EV charging gets very interesting (75 kWh battery with max charge rate of 11 kW), especially as car isn’t always connected to charger, so it will constantly recalculate when car is plugged in. Could integrate with calendar to see how many km are required to drive the next day and ensure that amount of range is added.
- best 7 hours of the day when at 0% state of charge (add 400 km range)
- best 3 hours of the day at 50% state of charge (add 200 km range)
- best 1 hour of the day at 85% state of charge (add 66 km range)
- best x hours of the day at y% state of charge where x=(100 -y)/100 * (75/ 11)