Jun-21-2020, 06:04 PM
Hi,
I am trying to develop a Power Curve / Algorithm that can give me a "Possible Max Power" signal when the Solar Panels on my roof are scaled-down in production.
To make this power curve I fetch data every second where I get a dataset similar to the below (Made with random.randint).
What would be a way I could separate this data into bins (Based on Solar_Radiation) so I can calculate a correlation between production and PV_Cell_Temp in each bin?
I have been looking around on the internet, but there doesn't seem to be anything in Pandas I can use to do this..
Timestamp,PV_Production,Solar_Radiation,PV_Cell_Temp,Ambient_Temp
2020-06-21 13:37:02.934901,0,206,164.8,0
2020-06-21 13:37:02.935898,0,312,124.8,0
2020-06-21 13:37:02.942879,0,234,23.4,0
2020-06-21 13:37:02.943877,0,230,230.0,0
2020-06-21 13:37:02.944874,0,273,218.4,0
2020-06-21 13:37:02.948862,0,317,95.1,0
2020-06-21 13:37:02.951855,0,328,328.0,0
2020-06-21 13:37:02.954847,0,311,0.0,0
I am trying to develop a Power Curve / Algorithm that can give me a "Possible Max Power" signal when the Solar Panels on my roof are scaled-down in production.
To make this power curve I fetch data every second where I get a dataset similar to the below (Made with random.randint).
What would be a way I could separate this data into bins (Based on Solar_Radiation) so I can calculate a correlation between production and PV_Cell_Temp in each bin?
I have been looking around on the internet, but there doesn't seem to be anything in Pandas I can use to do this..
Timestamp,PV_Production,Solar_Radiation,PV_Cell_Temp,Ambient_Temp
2020-06-21 13:37:02.934901,0,206,164.8,0
2020-06-21 13:37:02.935898,0,312,124.8,0
2020-06-21 13:37:02.942879,0,234,23.4,0
2020-06-21 13:37:02.943877,0,230,230.0,0
2020-06-21 13:37:02.944874,0,273,218.4,0
2020-06-21 13:37:02.948862,0,317,95.1,0
2020-06-21 13:37:02.951855,0,328,328.0,0
2020-06-21 13:37:02.954847,0,311,0.0,0