Pvsandiainv¶
Wrapper for SAM Simulation Core model: cmod_pvsandiainv.cpp
Input Consistency Warning¶
As described in Possible Problems, some input parameters are interdependent but the equations that enforce consistency are not available in this PySAM module. Therefore, the onus is on the PySAM user to check that interdependencies are correctly handled. The variables which may require additional logic include:
Provided for each of these inputs is a list of other inputs that are potentially interdependent.
Creating an Instance¶
Refer to the Initializing a Model page for details on the different ways to create an instance of a PySAM class.
Pvsandiainv model description
Pvsandiainv
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PySAM.Pvsandiainv.
default
(config) → Pvsandiainv¶ Use default attributes None
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PySAM.Pvsandiainv.
from_existing
(data, optional config) → Pvsandiainv¶ Share underlying data with an existing PySAM class. If config provided, default attributes are loaded otherwise.
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PySAM.Pvsandiainv.
new
() → Pvsandiainv¶
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PySAM.Pvsandiainv.
wrap
(ssc_data_t) → Pvsandiainv¶ Use existing PySSC data
Warning
Do not call PySSC.data_free on the ssc_data_t provided to
wrap
Functions¶
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class
PySAM.Pvsandiainv.
Pvsandiainv
¶ This class contains all the variable information for running a simulation. Variables are grouped together in the subclasses as properties. If property assignments are the wrong type, an error is thrown.
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assign
(dict) → None¶ Assign attributes from nested dictionary, except for Outputs
nested_dict = { 'Sandia Inverter Model': { var: val, ...}, ...}
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execute
(int verbosity) → None¶ Execute simulation with verbosity level 0 (default) or 1
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export
() → dict¶ Export attributes into nested dictionary
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replace
(dict) → None¶ Replace attributes from nested dictionary, except for Outputs. Unassigns all values in each Group then assigns from the input dict.
nested_dict = { 'Sandia Inverter Model': { var: val, ...}, ...}
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unassign
(name) → None¶ Unassign a value in any of the variable groups.
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value
(name, optional value) → Union[None, float, dict, sequence, str]¶ Get or set by name a value in any of the variable groups.
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SandiaInverterModel Group¶
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class
PySAM.Pvsandiainv.Pvsandiainv.
SandiaInverterModel
¶ -
assign
(dict) → None¶ Assign attributes from dictionary, overwriting but not removing values
SandiaInverterModel_vals = { var: val, ...}
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export
() → dict¶ Export attributes into dictionary
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replace
(dict) → None¶ Replace attributes from dictionary, unassigning values not present in input dict
SandiaInverterModel_vals = { var: val, ...}
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c0
¶ Defines parabolic curvature of relationship between ac power and dc power at reference conditions [1/W]
Required: True
Type: float Type: C0
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c1
¶ Parameter allowing Pdco to vary linearly with dc voltage input [1/V]
Required: True
Type: float Type: C1
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c2
¶ Parameter allowing Pso to vary linearly with dc voltage input [1/V]
Required: True
Type: float Type: C2
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c3
¶ Parameter allowing C0 to vary linearly with dc voltage input [1/V]
Required: True
Type: float Type: C3
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dc
¶ DC power input to inverter [Watt]
Required: True
Type: sequence
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dc_voltage
¶ DC voltage input to inverter [Volt]
Constraints: LENGTH_EQUAL=dc
Required: True
Type: sequence
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paco
¶ Max AC power rating [Wac]
Required: True
Type: float
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pdco
¶ DC power level at which Paco is achieved [Wdc]
Required: True
Type: float
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pntare
¶ Parasitic AC consumption [Wac]
Required: True
Type: float
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pso
¶ DC power level required to start inversion [Wdc]
Required: True
Type: float
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vdco
¶ DV voltage level at which Paco is achieved [Volt]
Required: True
Type: float
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Outputs Group¶
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class
PySAM.Pvsandiainv.Pvsandiainv.
Outputs
¶ -
assign
(dict) → None¶ Assign attributes from dictionary, overwriting but not removing values
Outputs_vals = { var: val, ...}
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export
() → dict¶ Export attributes into dictionary
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replace
(dict) → None¶ Replace attributes from dictionary, unassigning values not present in input dict
Outputs_vals = { var: val, ...}
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ac
¶ AC power output [Wac]
Type: sequence
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acpar
¶ AC parasitic power [Wac]
Type: sequence
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cliploss
¶ Power loss due to clipping (Wac) [Wac]
Type: sequence
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eff_inv
¶ Conversion efficiency [0..1]
Type: sequence
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ntloss
¶ Power loss due to night time tare loss (Wac) [Wac]
Type: sequence
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plr
¶ Part load ratio [0..1]
Type: sequence
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soloss
¶ Power loss due to operating power consumption (Wac) [Wac]
Type: sequence
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