Cause of IterationDiverge error #44
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Hi PGM team, We use PGM for power flow calculation with the following setup: pgm = PowerGridModel(self._topology)
return pgm.calculate_power_flow(
update_data=update_data,
calculation_method=CalculationMethod.newton_raphson,
threading=0,
tap_changing_strategy=TapChangingStrategy.disabled,
)
I have confirmed that this error is deterministic for this specific simulation. I have also tried increasing the
What can be the cause of having divergence here? Is there an error in our grid topology and/or input data? |
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Replies: 1 comment
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Hi @BartSchuurmans , A peculiar thing here is these are only continuous 10 scenarios from 2182 - 2204 which fail. Very likely indicating bad data. All the rest pass which would indicate grid parameters given in |
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Hi @BartSchuurmans ,
Nice job on the preliminary investigation of identifying that this is indeed deterministic.
The reason for diverge can be among many things and you need to go through each failing scenario individually.
A peculiar thing here is these are only continuous 10 scenarios from 2182 - 2204 which fail. Very likely indicating bad data. All the rest pass which would indicate grid parameters given in
input_dataare good. Check theupdate_datacorresponding to the failing scenarios for any unrealistic values. eg if a p_specified got a value of 1000kW instead of 1000W because of bad data or something similar.