nD-enerserve Forums
Voltage measurement - Printable Version

+- nD-enerserve Forums (https://forum.enerserve.eu)
+-- Forum: SmartPi (https://forum.enerserve.eu/forumdisplay.php?fid=1)
+--- Forum: SmartPi - English (https://forum.enerserve.eu/forumdisplay.php?fid=2)
+--- Thread: Voltage measurement (/showthread.php?tid=1400)



Voltage measurement - anders@rosentorp.nu - 30.07.2020

Hi all!

When I compare the measured voltages in the SmartPi with the real values (by a voltage meter directly on the SmartPi inputs) I can see some differenses.

THe measured voltages are 231-232 on all phases but the SmartPi says:

[img]data:image/png;base64,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[/img]


Is there a problem with my SmartPi or what is expected accuracy?

/Anders